From cfa40456e4bf9526cfeeea25128e17be1cef443c Mon Sep 17 00:00:00 2001
From: Rob Harrison <48765695+robjharrison@users.noreply.github.com>
Date: Mon, 12 Aug 2024 14:06:18 +0000
Subject: [PATCH] Data refresh 120824

---
 index.html                                    |    4 +-
 ...ed_childrens_services_inspection_scrape.py |    2 +
 ofsted_childrens_services_overview.xlsx       |  Bin 45497 -> 45507 bytes
 output.log                                    | 8220 +++++++++--------
 4 files changed, 4117 insertions(+), 4109 deletions(-)

diff --git a/index.html b/index.html
index 8a98b47..3616074 100644
--- a/index.html
+++ b/index.html
@@ -26,8 +26,8 @@
         <h1>Ofsted ILACS Summary</h1>
         <p>Summarised outcomes of published short and standard ILACS inspection reports by Ofsted, refreshed daily.<br/>An expanded version of the shown summary sheet, refreshed concurrently, is available to <a href="ofsted_childrens_services_overview.xlsx">download here</a> as an .xlsx file. <br/>Data summary is based on the original <i>ILACS Outcomes Summary</i> published periodically by the ADCS: <a href="https://adcs.org.uk/inspection/article/ilacs-outcomes-summary">https://adcs.org.uk/inspection/article/ilacs-outcomes-summary</a>. <a href="https://github.com/data-to-insight/ofsted-ilacs-scrape-tool/blob/main/README.md">Read the tool/project background details and future work.</a>.</p>
         <p>Disclaimer: This summary is built from scraped data direct from https://reports.ofsted.gov.uk/ published PDF inspection report files. As a result of the nuances|variance within the inspection report content or pdf encoding, we're noting some problematic data extraction for a small number of LAs*.<br/> *LA extraction issues: southend-on-sea, [overall, help_and_protection_grade,care_leavers_grade], nottingham,[inspection_framework, inspection_date], redcar and cleveland,[inspection_framework, inspection_date], knowsley,[inspector_name], stoke-on-trent,[inspector_name]<br/><a href="mailto:datatoinsight.enquiries@gmail.com?subject=Ofsted-Scrape-Tool">Feedback</a> on specific problems|inaccuracies|suggestions welcomed.*</p>
-        <p><b>Summary data last updated: 05 08 2024 09:42</b></p>
-        <p><b>LA inspections last updated: ['80575_warrington - 30 july 2024']</b></p>
+        <p><b>Summary data last updated: 12 08 2024 13:51</b></p>
+        <p><b>LA inspections last updated: []</b></p>
         <div class="container">
     <table border="1" class="dataframe">
   <thead>
diff --git a/ofsted_childrens_services_inspection_scrape.py b/ofsted_childrens_services_inspection_scrape.py
index bc188e6..aea71c3 100644
--- a/ofsted_childrens_services_inspection_scrape.py
+++ b/ofsted_childrens_services_inspection_scrape.py
@@ -78,11 +78,13 @@
 import nltk
 nltk.download('punkt')      # tokeniser models/sentence segmentation
 nltk.download('stopwords')  # stop words ready for text analysis|NLP preprocessing
+nltk.download('punkt_tab')  # added 120824 RH - as work-around fix textblob.exceptions.MissingCorpusError line 1384, in get_sentiment_and_topics
 
 # nlp stuff for sentiment
 try:
     from textblob import TextBlob
     from gensim import corpora, models
+    # sh "/Applications/Python 3.11/Install Certificates.command"
 except ModuleNotFoundError:
     print("Please install 'textblob' and 'gensim' using pip")
 
diff --git a/ofsted_childrens_services_overview.xlsx b/ofsted_childrens_services_overview.xlsx
index da8aae967e37fbb19cbdbf186c8f7159491c25bc..cf0626f28fad3505e2667a7ce266ea1670221f73 100644
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diff --git a/output.log b/output.log
index ca0a838..601ccab 100644
--- a/output.log
+++ b/output.log
@@ -1,4109 +1,4115 @@
-2024-08-05 08:34:41,586 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:34:41,589 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)
-2024-08-05 08:34:41,593 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-08-05T08:34:41.589703', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:41,595 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:34:41,595 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:34:41,595 - using serial LDA version on this node
-2024-08-05 08:34:41,596 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:34:41,596 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:34:41,600 - -8.103 per-word bound, 274.9 perplexity estimate based on a held-out corpus of 1 documents with 2696 words
-2024-08-05 08:34:41,600 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:34:41,602 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"within" + 0.006*"practice" + 0.005*"leaders" + 0.005*"Barnsley" + 0.004*"11" + 0.004*"15" + 0.004*"progress" + 0.004*"September"
-2024-08-05 08:34:41,602 - topic #1 (0.333): 0.018*"’" + 0.008*"needs" + 0.006*"leaders" + 0.006*"Barnsley" + 0.006*"within" + 0.005*"practice" + 0.005*"plans" + 0.004*"response" + 0.004*"senior" + 0.004*"understand"
-2024-08-05 08:34:41,602 - topic #2 (0.333): 0.020*"’" + 0.009*"leaders" + 0.009*"needs" + 0.006*"within" + 0.006*"practice" + 0.006*"Barnsley" + 0.005*"experiences" + 0.005*"plans" + 0.004*"11" + 0.004*"senior"
-2024-08-05 08:34:41,602 - topic diff=0.799144, rho=1.000000
-2024-08-05 08:34:41,603 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1216, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:34:41.603095', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:41,605 - Failed to import jpype dependencies. Fallback to subprocess.
-2024-08-05 08:34:41,605 - No module named 'jpype'
-2024-08-05 08:34:44,316 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:34:44,316 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:44,317 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:34:44,317 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:44,317 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:34:44,317 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:44,317 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:34:44,317 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:44,318 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:34:44,318 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:44,318 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:34:44,318 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:46,222 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:34:46,224 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)
-2024-08-05 08:34:46,224 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-08-05T08:34:46.224763', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:46,225 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:34:46,225 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:34:46,226 - using serial LDA version on this node
-2024-08-05 08:34:46,226 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:34:46,226 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:34:46,230 - -8.019 per-word bound, 259.5 perplexity estimate based on a held-out corpus of 1 documents with 2085 words
-2024-08-05 08:34:46,230 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:34:46,231 - topic #0 (0.333): 0.023*"’" + 0.009*"well" + 0.006*"practice" + 0.006*"effective" + 0.006*"plans" + 0.006*"leaders" + 0.006*"needs" + 0.005*"clear" + 0.005*"Somerset" + 0.005*"Bath"
-2024-08-05 08:34:46,231 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.006*"needs" + 0.006*"practice" + 0.005*"leaders" + 0.004*"plans" + 0.004*"4" + 0.004*"East" + 0.004*"Somerset" + 0.004*"receive"
-2024-08-05 08:34:46,231 - topic #2 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"needs" + 0.005*"plans" + 0.004*"education" + 0.004*"protection" + 0.004*"impact" + 0.004*"East" + 0.004*"North" + 0.004*"receive"
-2024-08-05 08:34:46,232 - topic diff=0.760495, rho=1.000000
-2024-08-05 08:34:46,232 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:34:46.232238', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:47,299 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:34:47,300 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:47,300 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:34:47,300 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:47,300 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:34:47,300 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:47,301 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:34:47,301 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:47,301 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:34:47,301 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:47,301 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:34:47,301 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:49,346 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:34:49,349 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)
-2024-08-05 08:34:49,349 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-08-05T08:34:49.349549', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:49,350 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:34:49,350 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:34:49,351 - using serial LDA version on this node
-2024-08-05 08:34:49,351 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:34:49,351 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:34:49,355 - -8.114 per-word bound, 277.1 perplexity estimate based on a held-out corpus of 1 documents with 2585 words
-2024-08-05 08:34:49,355 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:34:49,357 - topic #0 (0.333): 0.022*"’" + 0.007*"ensure" + 0.007*"needs" + 0.006*"well" + 0.005*"family" + 0.005*"plans" + 0.005*"education" + 0.005*"Bedford" + 0.005*"Borough" + 0.005*"26"
-2024-08-05 08:34:49,357 - topic #1 (0.333): 0.017*"’" + 0.008*"needs" + 0.006*"ensure" + 0.006*"Bedford" + 0.005*"well" + 0.005*"good" + 0.005*"supported" + 0.005*"progress" + 0.005*"need" + 0.004*"15"
-2024-08-05 08:34:49,357 - topic #2 (0.333): 0.016*"’" + 0.006*"plans" + 0.006*"well" + 0.005*"needs" + 0.005*"supported" + 0.005*"ensure" + 0.005*"relationships" + 0.005*"good" + 0.004*"education" + 0.004*"Bedford"
-2024-08-05 08:34:49,357 - topic diff=0.788495, rho=1.000000
-2024-08-05 08:34:49,358 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1202, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:34:49.357990', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:50,250 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:34:50,250 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:50,251 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:34:50,251 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:50,251 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:34:50,251 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:50,251 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:34:50,252 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:50,252 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:34:50,252 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:50,252 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:34:50,253 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:51,871 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:34:51,873 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)
-2024-08-05 08:34:51,873 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-08-05T08:34:51.873950', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:51,875 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:34:51,875 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:34:51,875 - using serial LDA version on this node
-2024-08-05 08:34:51,875 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:34:51,875 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:34:51,879 - -7.972 per-word bound, 251.0 perplexity estimate based on a held-out corpus of 1 documents with 2378 words
-2024-08-05 08:34:51,879 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:34:51,880 - topic #0 (0.333): 0.011*"’" + 0.009*"needs" + 0.005*"Birmingham" + 0.005*"progress" + 0.005*"well" + 0.005*"plans" + 0.005*"effective" + 0.004*"trust" + 0.004*"risk" + 0.004*"March"
-2024-08-05 08:34:51,881 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"effective" + 0.007*"well" + 0.006*"plans" + 0.006*"appropriate" + 0.006*"progress" + 0.006*"Birmingham" + 0.006*"timely" + 0.006*"trust"
-2024-08-05 08:34:51,881 - topic #2 (0.333): 0.013*"’" + 0.009*"needs" + 0.006*"effective" + 0.005*"well" + 0.005*"Birmingham" + 0.005*"plans" + 0.005*"trust" + 0.005*"risk" + 0.004*"3" + 0.004*"March"
-2024-08-05 08:34:51,881 - topic diff=0.817572, rho=1.000000
-2024-08-05 08:34:51,881 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1065, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:34:51.881530', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:52,895 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:34:52,896 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:52,896 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:34:52,896 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:52,896 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:34:52,896 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:52,897 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:34:52,897 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:52,897 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:34:52,897 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:52,897 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:34:52,897 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:54,873 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:34:54,876 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)
-2024-08-05 08:34:54,876 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-08-05T08:34:54.876393', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:54,877 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:34:54,877 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:34:54,877 - using serial LDA version on this node
-2024-08-05 08:34:54,878 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:34:54,878 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:34:54,881 - -7.959 per-word bound, 248.8 perplexity estimate based on a held-out corpus of 1 documents with 2353 words
-2024-08-05 08:34:54,882 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:34:54,883 - topic #0 (0.333): 0.016*"’" + 0.007*"practice" + 0.007*"needs" + 0.007*"Darwen" + 0.007*"impact" + 0.006*"Blackburn" + 0.006*"well" + 0.006*"quality" + 0.005*"means" + 0.005*"receive"
-2024-08-05 08:34:54,883 - topic #1 (0.333): 0.010*"’" + 0.007*"practice" + 0.007*"Darwen" + 0.007*"quality" + 0.007*"impact" + 0.006*"needs" + 0.006*"Blackburn" + 0.005*"well" + 0.005*"effective" + 0.005*"result"
-2024-08-05 08:34:54,883 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.008*"quality" + 0.007*"Blackburn" + 0.006*"practice" + 0.006*"planning" + 0.006*"well" + 0.005*"Darwen" + 0.005*"progress" + 0.004*"result"
-2024-08-05 08:34:54,883 - topic diff=0.810735, rho=1.000000
-2024-08-05 08:34:54,884 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1055, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:34:54.884109', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:55,804 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:34:55,804 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:55,805 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:34:55,805 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:55,805 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:34:55,805 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:55,805 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:34:55,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:55,806 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:34:55,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:55,806 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:34:55,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:57,666 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:34:57,669 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)
-2024-08-05 08:34:57,669 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-08-05T08:34:57.669561', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:57,670 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:34:57,670 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:34:57,670 - using serial LDA version on this node
-2024-08-05 08:34:57,671 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:34:57,671 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:34:57,674 - -7.925 per-word bound, 243.1 perplexity estimate based on a held-out corpus of 1 documents with 2392 words
-2024-08-05 08:34:57,675 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:34:57,676 - topic #0 (0.333): 0.019*"’" + 0.010*"needs" + 0.010*"well" + 0.009*"Blackpool" + 0.006*"practice" + 0.005*"effective" + 0.005*"quality" + 0.005*"16" + 0.005*"progress" + 0.005*"need"
-2024-08-05 08:34:57,676 - topic #1 (0.333): 0.016*"’" + 0.010*"needs" + 0.009*"well" + 0.006*"plans" + 0.006*"effective" + 0.006*"supported" + 0.006*"Blackpool" + 0.005*"understand" + 0.005*"practice" + 0.005*"experiences"
-2024-08-05 08:34:57,676 - topic #2 (0.333): 0.014*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"Blackpool" + 0.005*"5" + 0.005*"effective" + 0.005*"experiences" + 0.005*"plans" + 0.004*"supported" + 0.004*"16"
-2024-08-05 08:34:57,676 - topic diff=0.829670, rho=1.000000
-2024-08-05 08:34:57,676 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1037, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:34:57.676923', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:34:58,707 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:34:58,707 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:58,707 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:34:58,707 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:58,708 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:34:58,708 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:58,708 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:34:58,708 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:58,708 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:34:58,708 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:34:58,708 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:34:58,709 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:00,441 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:00,443 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)
-2024-08-05 08:35:00,443 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-08-05T08:35:00.443726', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:00,444 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:00,444 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:00,445 - using serial LDA version on this node
-2024-08-05 08:35:00,445 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:00,445 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:00,448 - -7.910 per-word bound, 240.4 perplexity estimate based on a held-out corpus of 1 documents with 2055 words
-2024-08-05 08:35:00,449 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:00,450 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.008*"Bolton" + 0.007*"plans" + 0.006*"well" + 0.006*"need" + 0.005*"supported" + 0.005*"11" + 0.005*"15" + 0.005*"response"
-2024-08-05 08:35:00,450 - topic #1 (0.333): 0.018*"’" + 0.009*"plans" + 0.008*"Bolton" + 0.007*"well" + 0.006*"needs" + 0.005*"effective" + 0.005*"strong" + 0.005*"planning" + 0.005*"supported" + 0.005*"good"
-2024-08-05 08:35:00,450 - topic #2 (0.333): 0.020*"’" + 0.011*"needs" + 0.010*"well" + 0.008*"Bolton" + 0.006*"plans" + 0.006*"supported" + 0.005*"planning" + 0.005*"experiences" + 0.005*"timely" + 0.005*"11"
-2024-08-05 08:35:00,450 - topic diff=0.771020, rho=1.000000
-2024-08-05 08:35:00,451 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:00.451028', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:01,407 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:01,407 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:01,408 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:01,408 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:01,408 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:01,408 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:01,408 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:01,408 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:01,409 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:01,409 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:01,409 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:01,409 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:02,982 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:02,985 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)
-2024-08-05 08:35:02,985 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-08-05T08:35:02.985308', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:02,986 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:02,986 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:02,986 - using serial LDA version on this node
-2024-08-05 08:35:02,987 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:02,987 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:02,990 - -8.034 per-word bound, 262.2 perplexity estimate based on a held-out corpus of 1 documents with 2004 words
-2024-08-05 08:35:02,990 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:02,992 - topic #0 (0.333): 0.022*"’" + 0.007*"quality" + 0.007*"practice" + 0.006*"progress" + 0.006*"Poole" + 0.005*"impact" + 0.005*"risk" + 0.005*"Bournemouth" + 0.005*"well" + 0.005*"6"
-2024-08-05 08:35:02,992 - topic #1 (0.333): 0.016*"’" + 0.005*"practice" + 0.004*"However" + 0.004*"time" + 0.004*"quality" + 0.004*"right" + 0.004*"6" + 0.004*"17" + 0.004*"positive" + 0.004*"Bournemouth"
-2024-08-05 08:35:02,992 - topic #2 (0.333): 0.012*"’" + 0.005*"quality" + 0.005*"practice" + 0.005*"Christchurch" + 0.004*"progress" + 0.004*"17" + 0.004*"impact" + 0.004*"time" + 0.004*"positive" + 0.004*"health"
-2024-08-05 08:35:02,992 - topic diff=0.765288, rho=1.000000
-2024-08-05 08:35:02,992 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1035, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:02.992853', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:05,044 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:05,045 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:05,045 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:05,045 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:05,045 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:05,045 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:05,046 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:05,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:05,046 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:05,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:05,046 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:05,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:06,419 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:06,421 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)
-2024-08-05 08:35:06,422 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-08-05T08:35:06.422073', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:06,422 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:06,423 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:06,423 - using serial LDA version on this node
-2024-08-05 08:35:06,423 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:06,423 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:06,426 - -7.855 per-word bound, 231.5 perplexity estimate based on a held-out corpus of 1 documents with 1846 words
-2024-08-05 08:35:06,427 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:06,428 - topic #0 (0.333): 0.015*"’" + 0.008*"risk" + 0.007*"well" + 0.006*"needs" + 0.006*"Bracknell" + 0.006*"progress" + 0.006*"Forest" + 0.006*"effective" + 0.006*"good" + 0.005*"provided"
-2024-08-05 08:35:06,428 - topic #1 (0.333): 0.015*"’" + 0.006*"risk" + 0.006*"quality" + 0.006*"plans" + 0.006*"Forest" + 0.006*"good" + 0.005*"effective" + 0.005*"needs" + 0.005*"Bracknell" + 0.005*"receive"
-2024-08-05 08:35:06,428 - topic #2 (0.333): 0.018*"’" + 0.008*"Bracknell" + 0.008*"Forest" + 0.008*"needs" + 0.007*"quality" + 0.006*"good" + 0.006*"provided" + 0.005*"effective" + 0.005*"progress" + 0.005*"plans"
-2024-08-05 08:35:06,428 - topic diff=0.766512, rho=1.000000
-2024-08-05 08:35:06,428 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=900, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:06.428853', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:07,541 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:07,542 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:07,542 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:07,542 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:07,542 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:07,542 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:07,542 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:07,543 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:07,543 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:07,543 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:07,543 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:07,543 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:09,183 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:09,186 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)
-2024-08-05 08:35:09,186 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)", 'datetime': '2024-08-05T08:35:09.186764', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:09,187 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:09,187 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:09,188 - using serial LDA version on this node
-2024-08-05 08:35:09,188 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:09,188 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:09,192 - -8.090 per-word bound, 272.5 perplexity estimate based on a held-out corpus of 1 documents with 2249 words
-2024-08-05 08:35:09,192 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:09,194 - topic #0 (0.333): 0.018*"’" + 0.007*"well" + 0.005*"needs" + 0.005*"Hove" + 0.005*"relationships" + 0.005*"practice" + 0.005*"family" + 0.004*"PAs" + 0.004*"experiences" + 0.004*"progress"
-2024-08-05 08:35:09,194 - topic #1 (0.333): 0.020*"’" + 0.009*"Hove" + 0.008*"well" + 0.007*"needs" + 0.006*"Brighton" + 0.006*"practice" + 0.006*"relationships" + 0.006*"experiences" + 0.006*"progress" + 0.005*"15"
-2024-08-05 08:35:09,194 - topic #2 (0.333): 0.010*"’" + 0.009*"Brighton" + 0.007*"well" + 0.007*"practice" + 0.007*"needs" + 0.005*"progress" + 0.005*"PAs" + 0.005*"11" + 0.005*"Hove" + 0.005*"experiences"
-2024-08-05 08:35:09,194 - topic diff=0.744463, rho=1.000000
-2024-08-05 08:35:09,194 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:09.194665', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:10,279 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:10,280 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:10,280 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:10,280 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:10,280 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:10,280 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:10,280 - Inspection date None / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:10,281 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:10,281 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:10,281 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:10,281 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:10,281 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:11,908 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:11,913 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)
-2024-08-05 08:35:11,913 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-08-05T08:35:11.913891', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:11,915 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:11,916 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:11,916 - using serial LDA version on this node
-2024-08-05 08:35:11,917 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:11,917 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:11,925 - -8.029 per-word bound, 261.2 perplexity estimate based on a held-out corpus of 1 documents with 2647 words
-2024-08-05 08:35:11,925 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:11,927 - topic #0 (0.333): 0.016*"’" + 0.009*"well" + 0.008*"Bristol" + 0.008*"needs" + 0.007*"good" + 0.006*"progress" + 0.005*"arrangements" + 0.005*"need" + 0.004*"living" + 0.004*"meetings"
-2024-08-05 08:35:11,927 - topic #1 (0.333): 0.025*"’" + 0.009*"good" + 0.008*"needs" + 0.008*"well" + 0.007*"Bristol" + 0.005*"leaders" + 0.005*"health" + 0.005*"27" + 0.005*"progress" + 0.005*"always"
-2024-08-05 08:35:11,928 - topic #2 (0.333): 0.014*"’" + 0.009*"well" + 0.007*"Bristol" + 0.007*"good" + 0.006*"needs" + 0.006*"health" + 0.005*"need" + 0.004*"plans" + 0.004*"ensure" + 0.004*"always"
-2024-08-05 08:35:11,928 - topic diff=0.818620, rho=1.000000
-2024-08-05 08:35:11,928 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1151, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:11.928455', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:12,937 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:12,937 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:12,937 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:12,938 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:12,938 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:12,938 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:12,938 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:12,938 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:12,938 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:12,939 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:12,939 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:12,939 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:14,741 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:14,744 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)
-2024-08-05 08:35:14,744 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-08-05T08:35:14.744736', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:14,745 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:14,745 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:14,746 - using serial LDA version on this node
-2024-08-05 08:35:14,746 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:14,746 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:14,750 - -8.240 per-word bound, 302.4 perplexity estimate based on a held-out corpus of 1 documents with 2404 words
-2024-08-05 08:35:14,750 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:14,752 - topic #0 (0.333): 0.015*"’" + 0.005*"number" + 0.005*"Buckinghamshire" + 0.005*"17" + 0.005*"protection" + 0.004*"2021" + 0.004*"plans" + 0.004*"many" + 0.004*"needs" + 0.004*"6"
-2024-08-05 08:35:14,752 - topic #1 (0.333): 0.011*"’" + 0.005*"plans" + 0.004*"practice" + 0.004*"17" + 0.003*"December" + 0.003*"number" + 0.003*"protection" + 0.003*"teams" + 0.003*"Buckinghamshire" + 0.003*"progress"
-2024-08-05 08:35:14,752 - topic #2 (0.333): 0.014*"’" + 0.006*"plans" + 0.005*"number" + 0.005*"Buckinghamshire" + 0.004*"6" + 0.004*"many" + 0.004*"17" + 0.004*"practice" + 0.004*"December" + 0.003*"small"
-2024-08-05 08:35:14,752 - topic diff=0.731419, rho=1.000000
-2024-08-05 08:35:14,753 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1263, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:14.753112', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:16,050 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:16,051 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:16,051 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:16,051 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:16,052 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:16,052 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:16,056 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:16,063 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:16,063 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:16,064 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:16,064 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:16,064 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:21,721 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:21,726 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)
-2024-08-05 08:35:21,726 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-08-05T08:35:21.726590', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:21,728 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:21,728 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:21,729 - using serial LDA version on this node
-2024-08-05 08:35:21,729 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:21,729 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:21,738 - -7.976 per-word bound, 251.7 perplexity estimate based on a held-out corpus of 1 documents with 2427 words
-2024-08-05 08:35:21,742 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:21,744 - topic #0 (0.333): 0.013*"’" + 0.006*"needs" + 0.006*"2021" + 0.006*"protection" + 0.006*"team" + 0.006*"need" + 0.005*"Bury" + 0.005*"impact" + 0.005*"risk" + 0.005*"practice"
-2024-08-05 08:35:21,744 - topic #1 (0.333): 0.010*"’" + 0.007*"protection" + 0.006*"2021" + 0.006*"needs" + 0.005*"team" + 0.005*"need" + 0.005*"practice" + 0.005*"impact" + 0.005*"quality" + 0.005*"risk"
-2024-08-05 08:35:21,744 - topic #2 (0.333): 0.011*"’" + 0.007*"needs" + 0.007*"practice" + 0.006*"2021" + 0.006*"protection" + 0.005*"team" + 0.004*"impact" + 0.004*"October" + 0.004*"quality" + 0.004*"always"
-2024-08-05 08:35:21,744 - topic diff=0.803612, rho=1.000000
-2024-08-05 08:35:21,745 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.02s', 'datetime': '2024-08-05T08:35:21.745054', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:23,607 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:23,624 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:23,624 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:23,632 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:23,633 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:23,633 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:23,633 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:23,634 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:23,634 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:23,634 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:23,634 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:23,635 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:26,218 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:26,220 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)
-2024-08-05 08:35:26,220 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-08-05T08:35:26.220881', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:26,221 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:26,222 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:26,222 - using serial LDA version on this node
-2024-08-05 08:35:26,222 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:26,222 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:26,226 - -8.028 per-word bound, 261.1 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
-2024-08-05 08:35:26,226 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:26,228 - topic #0 (0.333): 0.019*"’" + 0.012*"needs" + 0.009*"Calderdale" + 0.006*"ensure" + 0.006*"well" + 0.006*"experiences" + 0.005*"risk" + 0.005*"plans" + 0.005*"progress" + 0.005*"PAs"
-2024-08-05 08:35:26,228 - topic #1 (0.333): 0.025*"’" + 0.008*"Calderdale" + 0.007*"needs" + 0.007*"plans" + 0.006*"well" + 0.006*"progress" + 0.005*"ensure" + 0.005*"risk" + 0.005*"supported" + 0.004*"parents"
-2024-08-05 08:35:26,228 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"Calderdale" + 0.006*"progress" + 0.006*"well" + 0.005*"parents" + 0.004*"plans" + 0.004*"ensure" + 0.004*"experiences" + 0.004*"risk"
-2024-08-05 08:35:26,228 - topic diff=0.780981, rho=1.000000
-2024-08-05 08:35:26,228 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:26.228832', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:27,217 - Inspection date 2024-02-19 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:27,218 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:27,218 - Inspection date 2024-02-19 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:27,218 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:27,218 - Inspection date 2024-02-19 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:27,219 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:27,219 - Inspection date 2024-02-19 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:27,219 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:27,220 - Inspection date 2024-02-19 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:27,220 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:27,220 - Inspection date 2024-02-19 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:27,220 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:29,060 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:29,062 - built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)
-2024-08-05 08:35:29,062 - Dictionary lifecycle event {'msg': "built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)", 'datetime': '2024-08-05T08:35:29.062843', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:29,063 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:29,064 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:29,064 - using serial LDA version on this node
-2024-08-05 08:35:29,064 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:29,064 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:29,068 - -8.004 per-word bound, 256.8 perplexity estimate based on a held-out corpus of 1 documents with 2339 words
-2024-08-05 08:35:29,068 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:29,069 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"Cambridgeshire" + 0.006*"leaders" + 0.005*"2024" + 0.005*"effective" + 0.005*"However" + 0.005*"clear" + 0.005*"15" + 0.004*"good"
-2024-08-05 08:35:29,070 - topic #1 (0.333): 0.015*"’" + 0.007*"good" + 0.006*"Cambridgeshire" + 0.005*"leaders" + 0.005*"experiences" + 0.005*"well" + 0.005*"effective" + 0.004*"quality" + 0.004*"needs" + 0.004*"leadership"
-2024-08-05 08:35:29,070 - topic #2 (0.333): 0.020*"’" + 0.008*"needs" + 0.007*"leaders" + 0.006*"Cambridgeshire" + 0.005*"well" + 0.005*"practice" + 0.005*"4" + 0.005*"effective" + 0.005*"leadership" + 0.005*"good"
-2024-08-05 08:35:29,070 - topic diff=0.784694, rho=1.000000
-2024-08-05 08:35:29,070 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1082, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:29.070708', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:30,132 - Inspection date 2024-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:30,133 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:30,133 - Inspection date 2024-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:30,133 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:30,133 - Inspection date 2024-03-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:30,133 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:30,134 - Inspection date 2024-03-04 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:30,134 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:30,134 - Inspection date 2024-03-04 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:30,134 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:30,134 - Inspection date 2024-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:30,135 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:31,815 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:31,818 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
-2024-08-05 08:35:31,818 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-08-05T08:35:31.818283', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:31,819 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:31,819 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:31,819 - using serial LDA version on this node
-2024-08-05 08:35:31,820 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:31,820 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:31,823 - -7.965 per-word bound, 249.9 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
-2024-08-05 08:35:31,823 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:31,825 - topic #0 (0.333): 0.019*"’" + 0.011*"well" + 0.008*"needs" + 0.007*"progress" + 0.007*"need" + 0.006*"carers" + 0.006*"good" + 0.006*"plans" + 0.005*"effective" + 0.005*"education"
-2024-08-05 08:35:31,825 - topic #1 (0.333): 0.009*"’" + 0.008*"well" + 0.006*"good" + 0.005*"plans" + 0.005*"need" + 0.005*"needs" + 0.004*"carers" + 0.004*"Bedfordshire" + 0.004*"17" + 0.004*"education"
-2024-08-05 08:35:31,825 - topic #2 (0.333): 0.018*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"carers" + 0.006*"need" + 0.006*"plans" + 0.006*"Bedfordshire" + 0.006*"good" + 0.005*"Leaders" + 0.005*"Central"
-2024-08-05 08:35:31,825 - topic diff=0.791665, rho=1.000000
-2024-08-05 08:35:31,825 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1030, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:31.825731', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:32,836 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:32,836 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:32,837 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:32,837 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:32,837 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:32,837 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:32,837 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:32,838 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:32,838 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:32,838 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:32,838 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:32,838 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:34,371 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:34,373 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)
-2024-08-05 08:35:34,374 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-08-05T08:35:34.374158', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:34,375 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:34,375 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:34,375 - using serial LDA version on this node
-2024-08-05 08:35:34,375 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:34,375 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:34,379 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 2272 words
-2024-08-05 08:35:34,379 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:34,380 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"2024" + 0.007*"East" + 0.006*"quality" + 0.006*"practice" + 0.006*"well" + 0.006*"Cheshire" + 0.005*"leaders" + 0.005*"need"
-2024-08-05 08:35:34,381 - topic #1 (0.333): 0.008*"’" + 0.006*"plans" + 0.006*"needs" + 0.006*"quality" + 0.006*"2024" + 0.005*"well" + 0.005*"practice" + 0.004*"means" + 0.004*"leaders" + 0.004*"effective"
-2024-08-05 08:35:34,381 - topic #2 (0.333): 0.015*"’" + 0.009*"2024" + 0.008*"plans" + 0.008*"needs" + 0.007*"practice" + 0.007*"well" + 0.006*"Cheshire" + 0.006*"effective" + 0.006*"leaders" + 0.005*"East"
-2024-08-05 08:35:34,381 - topic diff=0.786808, rho=1.000000
-2024-08-05 08:35:34,381 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:34.381565', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:35,273 - Inspection date 2024-02-26 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:35,273 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:35,273 - Inspection date 2024-02-26 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:35,273 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:35,274 - Inspection date 2024-02-26 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:35,274 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:35,274 - Inspection date 2024-02-26 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:35,274 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:35,274 - Inspection date 2024-02-26 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:35,274 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:35,274 - Inspection date 2024-02-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:35,275 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:37,023 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:37,025 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)
-2024-08-05 08:35:37,026 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)", 'datetime': '2024-08-05T08:35:37.026051', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:37,027 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:37,027 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:37,027 - using serial LDA version on this node
-2024-08-05 08:35:37,027 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:37,027 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:37,031 - -7.999 per-word bound, 255.8 perplexity estimate based on a held-out corpus of 1 documents with 2186 words
-2024-08-05 08:35:37,031 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:37,032 - topic #0 (0.333): 0.014*"’" + 0.005*"well" + 0.004*"needs" + 0.004*"effective" + 0.004*"order" + 0.004*"leaders" + 0.004*"receive" + 0.004*"However" + 0.004*"learning" + 0.003*"always"
-2024-08-05 08:35:37,033 - topic #1 (0.333): 0.029*"’" + 0.008*"well" + 0.008*"needs" + 0.005*"practice" + 0.005*"impact" + 0.005*"effectively" + 0.005*"plans" + 0.004*"always" + 0.004*"effective" + 0.004*"progress"
-2024-08-05 08:35:37,033 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"receive" + 0.004*"practice" + 0.004*"order" + 0.004*"effectively" + 0.004*"plans" + 0.004*"always" + 0.004*"need"
-2024-08-05 08:35:37,033 - topic diff=0.783968, rho=1.000000
-2024-08-05 08:35:37,033 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:37.033650', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:38,141 - Inspection date 2019-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:38,142 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:38,142 - Inspection date 2019-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:38,142 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:38,143 - Inspection date 2019-03-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:38,143 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:38,143 - Inspection date 2019-03-18 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:38,143 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:38,144 - Inspection date 2019-03-18 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:38,144 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:38,144 - Inspection date 2019-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:38,145 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:39,974 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:39,976 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)
-2024-08-05 08:35:39,977 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-08-05T08:35:39.977132', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:39,978 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:39,978 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:39,978 - using serial LDA version on this node
-2024-08-05 08:35:39,979 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:39,979 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:39,983 - -8.051 per-word bound, 265.3 perplexity estimate based on a held-out corpus of 1 documents with 2639 words
-2024-08-05 08:35:39,983 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:39,984 - topic #0 (0.333): 0.025*"’" + 0.008*"plans" + 0.005*"needs" + 0.005*"2" + 0.005*"practice" + 0.005*"quality" + 0.005*"Council" + 0.005*"risk" + 0.005*"Bradford" + 0.005*"21"
-2024-08-05 08:35:39,984 - topic #1 (0.333): 0.017*"’" + 0.005*"Bradford" + 0.005*"plans" + 0.004*"needs" + 0.004*"2" + 0.004*"changes" + 0.004*"impact" + 0.004*"Borough" + 0.004*"December" + 0.004*"quality"
-2024-08-05 08:35:39,985 - topic #2 (0.333): 0.016*"’" + 0.006*"plans" + 0.005*"City" + 0.005*"need" + 0.005*"◼" + 0.004*"Bradford" + 0.004*"impact" + 0.004*"December" + 0.004*"senior" + 0.004*"risk"
-2024-08-05 08:35:39,985 - topic diff=0.821770, rho=1.000000
-2024-08-05 08:35:39,985 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1164, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:39.985344', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:40,950 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:40,951 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:40,951 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:40,951 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:40,951 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:40,951 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:40,951 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:40,951 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:40,952 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:40,952 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:40,952 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:40,952 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:42,663 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:42,665 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)
-2024-08-05 08:35:42,665 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-08-05T08:35:42.665468', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:42,666 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:42,666 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:42,666 - using serial LDA version on this node
-2024-08-05 08:35:42,667 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:42,667 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:42,670 - -7.835 per-word bound, 228.3 perplexity estimate based on a held-out corpus of 1 documents with 1767 words
-2024-08-05 08:35:42,670 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:42,671 - topic #0 (0.333): 0.015*"needs" + 0.013*"’" + 0.010*"well" + 0.008*"effective" + 0.007*"clear" + 0.006*"ensure" + 0.006*"progress" + 0.006*"good" + 0.005*"plans" + 0.005*"within"
-2024-08-05 08:35:42,671 - topic #1 (0.333): 0.012*"’" + 0.009*"needs" + 0.009*"well" + 0.008*"ensure" + 0.007*"effective" + 0.006*"progress" + 0.006*"clear" + 0.005*"plans" + 0.005*"good" + 0.005*"supported"
-2024-08-05 08:35:42,672 - topic #2 (0.333): 0.011*"ensure" + 0.011*"well" + 0.010*"’" + 0.009*"needs" + 0.005*"clear" + 0.005*"plans" + 0.005*"clearly" + 0.005*"good" + 0.005*"effective" + 0.005*"progress"
-2024-08-05 08:35:42,672 - topic diff=0.746091, rho=1.000000
-2024-08-05 08:35:42,672 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=876, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:42.672395', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:43,945 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:43,945 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:43,945 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:43,945 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:43,946 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:43,946 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:43,946 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:43,946 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:43,946 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:43,946 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:43,947 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:43,947 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:45,494 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:45,497 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)
-2024-08-05 08:35:45,497 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-08-05T08:35:45.497327', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:45,498 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:45,498 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:45,498 - using serial LDA version on this node
-2024-08-05 08:35:45,499 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:45,499 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:45,502 - -7.909 per-word bound, 240.3 perplexity estimate based on a held-out corpus of 1 documents with 2281 words
-2024-08-05 08:35:45,502 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:45,504 - topic #0 (0.333): 0.013*"’" + 0.008*"effective" + 0.007*"leaders" + 0.007*"well" + 0.007*"Wakefield" + 0.007*"November" + 0.006*"plans" + 0.006*"quality" + 0.006*"good" + 0.005*"practice"
-2024-08-05 08:35:45,504 - topic #1 (0.333): 0.018*"’" + 0.009*"Wakefield" + 0.008*"well" + 0.008*"quality" + 0.007*"leaders" + 0.006*"November" + 0.006*"effective" + 0.006*"plans" + 0.006*"good" + 0.006*"practice"
-2024-08-05 08:35:45,504 - topic #2 (0.333): 0.018*"’" + 0.008*"November" + 0.008*"good" + 0.008*"quality" + 0.007*"Wakefield" + 0.006*"well" + 0.006*"leaders" + 0.006*"progress" + 0.006*"effective" + 0.005*"needs"
-2024-08-05 08:35:45,504 - topic diff=0.802424, rho=1.000000
-2024-08-05 08:35:45,504 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1007, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:45.504798', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:46,430 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:46,430 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:46,430 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:46,431 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:46,431 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:46,431 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:46,431 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:46,431 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:46,432 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:46,432 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:46,432 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:46,432 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:48,106 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:48,110 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)
-2024-08-05 08:35:48,110 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-08-05T08:35:48.110452', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:48,111 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:48,112 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:48,112 - using serial LDA version on this node
-2024-08-05 08:35:48,113 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:48,113 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:48,119 - -7.865 per-word bound, 233.1 perplexity estimate based on a held-out corpus of 1 documents with 1855 words
-2024-08-05 08:35:48,119 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:48,121 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"March" + 0.005*"supported" + 0.005*"effective" + 0.005*"ensure" + 0.004*"need" + 0.004*"education" + 0.004*"plans" + 0.004*"However"
-2024-08-05 08:35:48,121 - topic #1 (0.333): 0.018*"’" + 0.008*"needs" + 0.008*"March" + 0.007*"effective" + 0.007*"quality" + 0.007*"York" + 0.006*"However" + 0.006*"good" + 0.006*"7" + 0.005*"well"
-2024-08-05 08:35:48,121 - topic #2 (0.333): 0.011*"’" + 0.008*"quality" + 0.006*"March" + 0.006*"needs" + 0.005*"training" + 0.005*"ensure" + 0.004*"practice" + 0.004*"well" + 0.004*"plans" + 0.004*"York"
-2024-08-05 08:35:48,122 - topic diff=0.784118, rho=1.000000
-2024-08-05 08:35:48,122 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=909, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:48.122389', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:49,153 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:49,153 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:49,153 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:49,153 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:49,154 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:49,154 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:49,154 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:49,154 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:49,154 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:49,154 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:49,154 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:49,155 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:50,620 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:50,623 - built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)
-2024-08-05 08:35:50,623 - Dictionary lifecycle event {'msg': "built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)", 'datetime': '2024-08-05T08:35:50.623221', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:50,624 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:50,624 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:50,624 - using serial LDA version on this node
-2024-08-05 08:35:50,624 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:50,624 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:50,628 - -7.948 per-word bound, 246.9 perplexity estimate based on a held-out corpus of 1 documents with 2157 words
-2024-08-05 08:35:50,628 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:50,629 - topic #0 (0.333): 0.015*"’" + 0.013*"well" + 0.010*"quality" + 0.010*"effective" + 0.008*"leaders" + 0.006*"timely" + 0.006*"plans" + 0.006*"arrangements" + 0.005*"good" + 0.005*"Senior"
-2024-08-05 08:35:50,629 - topic #1 (0.333): 0.013*"well" + 0.010*"’" + 0.006*"quality" + 0.006*"leaders" + 0.005*"timely" + 0.005*"highly" + 0.005*"plans" + 0.005*"effective" + 0.005*"needs" + 0.004*"good"
-2024-08-05 08:35:50,630 - topic #2 (0.333): 0.018*"well" + 0.011*"quality" + 0.010*"’" + 0.010*"effective" + 0.010*"leaders" + 0.007*"good" + 0.006*"arrangements" + 0.006*"plans" + 0.005*"ensure" + 0.005*"timely"
-2024-08-05 08:35:50,630 - topic diff=0.784652, rho=1.000000
-2024-08-05 08:35:50,630 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1014, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:50.630381', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:51,745 - Inspection date 2019-10-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:51,745 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:51,745 - Inspection date 2019-10-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:51,746 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:51,746 - Inspection date 2019-10-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:51,746 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:51,746 - Inspection date 2019-10-14 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:51,746 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:51,746 - Inspection date 2019-10-14 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:51,746 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:51,747 - Inspection date 2019-10-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:51,747 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:52,918 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:52,921 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)
-2024-08-05 08:35:52,922 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-08-05T08:35:52.922095', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:52,923 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:52,923 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:52,923 - using serial LDA version on this node
-2024-08-05 08:35:52,924 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:52,924 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:52,930 - -7.679 per-word bound, 204.9 perplexity estimate based on a held-out corpus of 1 documents with 1521 words
-2024-08-05 08:35:52,930 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:52,932 - topic #0 (0.333): 0.025*"’" + 0.017*"Isles" + 0.013*"Scilly" + 0.010*"practice" + 0.009*"information" + 0.009*"need" + 0.008*"protection" + 0.007*"needs" + 0.006*"risks" + 0.006*"quality"
-2024-08-05 08:35:52,932 - topic #1 (0.333): 0.021*"’" + 0.014*"Scilly" + 0.009*"need" + 0.009*"information" + 0.008*"Isles" + 0.007*"needs" + 0.007*"quality" + 0.007*"place" + 0.006*"practice" + 0.006*"protection"
-2024-08-05 08:35:52,933 - topic #2 (0.333): 0.012*"’" + 0.008*"practice" + 0.008*"information" + 0.007*"Isles" + 0.007*"Scilly" + 0.005*"need" + 0.005*"protection" + 0.005*"needs" + 0.005*"risks" + 0.005*"place"
-2024-08-05 08:35:52,933 - topic diff=0.767050, rho=1.000000
-2024-08-05 08:35:52,933 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=754, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:52.933645', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:53,948 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:53,949 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:53,949 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:53,949 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:53,949 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:53,949 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:53,949 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:53,949 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:53,950 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:53,950 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:53,950 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:53,950 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:55,634 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:55,636 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)
-2024-08-05 08:35:55,636 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-08-05T08:35:55.636760', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:55,637 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:55,637 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:55,638 - using serial LDA version on this node
-2024-08-05 08:35:55,638 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:55,638 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:55,641 - -7.845 per-word bound, 229.9 perplexity estimate based on a held-out corpus of 1 documents with 2074 words
-2024-08-05 08:35:55,641 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:55,643 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.008*"Coventry" + 0.006*"needs" + 0.005*"strong" + 0.005*"plans" + 0.005*"supported" + 0.005*"family" + 0.005*"need" + 0.004*"2022"
-2024-08-05 08:35:55,643 - topic #1 (0.333): 0.021*"’" + 0.009*"Coventry" + 0.009*"well" + 0.009*"needs" + 0.008*"supported" + 0.007*"plans" + 0.006*"family" + 0.006*"strong" + 0.006*"need" + 0.005*"PAs"
-2024-08-05 08:35:55,643 - topic #2 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"well" + 0.005*"Coventry" + 0.005*"family" + 0.005*"supported" + 0.004*"plans" + 0.004*"strong" + 0.004*"need" + 0.004*"1"
-2024-08-05 08:35:55,643 - topic diff=0.810433, rho=1.000000
-2024-08-05 08:35:55,643 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=938, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:55.643632', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:56,573 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:35:56,573 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:56,573 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:35:56,573 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:56,573 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:35:56,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:56,574 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:35:56,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:56,574 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:35:56,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:56,574 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:35:56,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:35:58,959 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:35:58,962 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)
-2024-08-05 08:35:58,962 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-08-05T08:35:58.962426', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:35:58,963 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:35:58,963 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:35:58,963 - using serial LDA version on this node
-2024-08-05 08:35:58,964 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:35:58,964 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:35:58,968 - -8.087 per-word bound, 271.9 perplexity estimate based on a held-out corpus of 1 documents with 2653 words
-2024-08-05 08:35:58,968 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:35:58,970 - topic #0 (0.333): 0.024*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"leaders" + 0.007*"October" + 0.007*"practice" + 0.007*"Darlington" + 0.006*"quality" + 0.005*"education" + 0.005*"effective"
-2024-08-05 08:35:58,970 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.006*"October" + 0.006*"leaders" + 0.005*"needs" + 0.005*"practice" + 0.005*"Darlington" + 0.004*"21" + 0.004*"supported" + 0.004*"education"
-2024-08-05 08:35:58,970 - topic #2 (0.333): 0.012*"’" + 0.005*"effective" + 0.005*"needs" + 0.005*"October" + 0.005*"well" + 0.005*"leaders" + 0.005*"practice" + 0.004*"supported" + 0.004*"Darlington" + 0.004*"family"
-2024-08-05 08:35:58,970 - topic diff=0.814711, rho=1.000000
-2024-08-05 08:35:58,970 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1195, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:35:58.970695', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:00,111 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:00,111 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:00,112 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:00,112 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:00,112 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:00,112 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:00,113 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:00,113 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:00,113 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:00,113 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:00,113 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:00,113 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:02,016 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:02,018 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)
-2024-08-05 08:36:02,019 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-08-05T08:36:02.019056', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:02,020 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:02,020 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:02,020 - using serial LDA version on this node
-2024-08-05 08:36:02,020 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:02,021 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:02,024 - -8.048 per-word bound, 264.7 perplexity estimate based on a held-out corpus of 1 documents with 2396 words
-2024-08-05 08:36:02,024 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:02,026 - topic #0 (0.333): 0.022*"’" + 0.008*"needs" + 0.008*"Derby" + 0.007*"leaders" + 0.007*"quality" + 0.006*"receive" + 0.006*"appropriate" + 0.006*"need" + 0.006*"progress" + 0.006*"plans"
-2024-08-05 08:36:02,026 - topic #1 (0.333): 0.017*"’" + 0.009*"needs" + 0.007*"receive" + 0.006*"Derby" + 0.006*"quality" + 0.006*"progress" + 0.005*"good" + 0.005*"well" + 0.005*"appropriate" + 0.005*"home"
-2024-08-05 08:36:02,026 - topic #2 (0.333): 0.024*"’" + 0.011*"needs" + 0.006*"Derby" + 0.006*"good" + 0.006*"quality" + 0.006*"plans" + 0.005*"need" + 0.005*"receive" + 0.005*"well" + 0.005*"progress"
-2024-08-05 08:36:02,026 - topic diff=0.773008, rho=1.000000
-2024-08-05 08:36:02,026 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1121, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:02.026947', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:02,964 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:02,965 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:02,965 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:02,965 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:02,965 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:02,965 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:02,966 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:02,966 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:02,966 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:02,966 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:02,966 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:02,966 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:04,296 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:04,299 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)
-2024-08-05 08:36:04,299 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-08-05T08:36:04.299439', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:04,300 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:04,300 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:04,300 - using serial LDA version on this node
-2024-08-05 08:36:04,301 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:04,301 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:04,304 - -8.038 per-word bound, 262.8 perplexity estimate based on a held-out corpus of 1 documents with 2035 words
-2024-08-05 08:36:04,304 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:04,307 - topic #0 (0.333): 0.018*"’" + 0.009*"well" + 0.006*"Derbyshire" + 0.006*"positive" + 0.005*"plans" + 0.005*"needs" + 0.005*"10" + 0.005*"education" + 0.005*"health" + 0.005*"progress"
-2024-08-05 08:36:04,307 - topic #1 (0.333): 0.011*"’" + 0.007*"well" + 0.007*"Derbyshire" + 0.005*"effective" + 0.004*"leaders" + 0.004*"needs" + 0.004*"number" + 0.004*"plans" + 0.004*"education" + 0.004*"October"
-2024-08-05 08:36:04,307 - topic #2 (0.333): 0.011*"’" + 0.007*"well" + 0.006*"Derbyshire" + 0.005*"plans" + 0.005*"number" + 0.005*"good" + 0.004*"leaders" + 0.004*"2023" + 0.004*"need" + 0.004*"needs"
-2024-08-05 08:36:04,307 - topic diff=0.738127, rho=1.000000
-2024-08-05 08:36:04,307 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:04.307762', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:05,256 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:05,257 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:05,257 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:05,257 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:05,257 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:05,257 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:05,258 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:05,258 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:05,258 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:05,258 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:05,258 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:05,258 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:06,810 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:06,812 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)
-2024-08-05 08:36:06,813 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-08-05T08:36:06.813038', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:06,814 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:06,814 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:06,814 - using serial LDA version on this node
-2024-08-05 08:36:06,814 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:06,815 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:06,818 - -8.143 per-word bound, 282.6 perplexity estimate based on a held-out corpus of 1 documents with 2313 words
-2024-08-05 08:36:06,819 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:06,820 - topic #0 (0.333): 0.007*"’" + 0.006*"well" + 0.005*"risk" + 0.005*"leaders" + 0.004*"health" + 0.004*"progress" + 0.003*"quality" + 0.003*"protection" + 0.003*"case" + 0.003*"time"
-2024-08-05 08:36:06,820 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"health" + 0.005*"leaders" + 0.005*"progress" + 0.005*"risk" + 0.005*"protection" + 0.004*"case" + 0.004*"Devon" + 0.004*"needs"
-2024-08-05 08:36:06,820 - topic #2 (0.333): 0.009*"’" + 0.006*"well" + 0.004*"health" + 0.004*"leaders" + 0.004*"progress" + 0.004*"risk" + 0.004*"time" + 0.004*"early" + 0.004*"Devon" + 0.004*"living"
-2024-08-05 08:36:06,820 - topic diff=0.733226, rho=1.000000
-2024-08-05 08:36:06,821 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:06.821115', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:07,901 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:07,901 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:07,901 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:07,902 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:07,902 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:07,902 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:07,902 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:07,902 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:07,902 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:07,903 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:07,903 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:07,903 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:09,507 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:09,512 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)
-2024-08-05 08:36:09,512 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-08-05T08:36:09.512603', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:09,514 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:09,514 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:09,514 - using serial LDA version on this node
-2024-08-05 08:36:09,515 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:09,515 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:09,521 - -8.117 per-word bound, 277.7 perplexity estimate based on a held-out corpus of 1 documents with 2429 words
-2024-08-05 08:36:09,521 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:09,523 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"Doncaster" + 0.006*"records" + 0.005*"arrangements" + 0.005*"many" + 0.005*"quality" + 0.005*"25" + 0.005*"progress" + 0.004*"information"
-2024-08-05 08:36:09,524 - topic #1 (0.333): 0.016*"’" + 0.006*"Doncaster" + 0.005*"progress" + 0.005*"plans" + 0.005*"well" + 0.005*"14" + 0.005*"records" + 0.004*"25" + 0.004*"leaders" + 0.004*"effective"
-2024-08-05 08:36:09,524 - topic #2 (0.333): 0.025*"’" + 0.006*"well" + 0.006*"leaders" + 0.005*"many" + 0.005*"quality" + 0.004*"progress" + 0.004*"oversight" + 0.004*"plans" + 0.004*"February" + 0.004*"protection"
-2024-08-05 08:36:09,524 - topic diff=0.769350, rho=1.000000
-2024-08-05 08:36:09,524 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:09.524638', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:11,507 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:11,507 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:11,507 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:11,508 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:11,508 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:11,508 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:11,508 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:11,508 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:11,509 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:11,509 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:11,509 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:11,509 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:12,882 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:12,884 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)
-2024-08-05 08:36:12,885 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-08-05T08:36:12.885058', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:12,886 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:12,886 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:12,886 - using serial LDA version on this node
-2024-08-05 08:36:12,886 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:12,886 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:12,890 - -8.102 per-word bound, 274.7 perplexity estimate based on a held-out corpus of 1 documents with 1942 words
-2024-08-05 08:36:12,890 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:12,891 - topic #0 (0.333): 0.013*"’" + 0.009*"Dorset" + 0.007*"well" + 0.006*"good" + 0.004*"needs" + 0.004*"arrangements" + 0.004*"supported" + 0.004*"2021" + 0.004*"leaders" + 0.004*"protection"
-2024-08-05 08:36:12,892 - topic #1 (0.333): 0.014*"’" + 0.007*"Dorset" + 0.006*"good" + 0.006*"needs" + 0.005*"well" + 0.005*"arrangements" + 0.004*"October" + 0.004*"2021" + 0.004*"impact" + 0.004*"leaders"
-2024-08-05 08:36:12,892 - topic #2 (0.333): 0.014*"’" + 0.007*"Dorset" + 0.006*"good" + 0.005*"well" + 0.005*"8" + 0.004*"need" + 0.004*"including" + 0.004*"impact" + 0.004*"protection" + 0.004*"change"
-2024-08-05 08:36:12,892 - topic diff=0.715051, rho=1.000000
-2024-08-05 08:36:12,892 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1067, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:12.892497', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:13,845 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:13,845 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:13,846 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:13,846 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:13,846 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:13,846 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:13,846 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:13,846 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:13,847 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:13,847 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:13,847 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:13,847 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:15,235 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:15,237 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)
-2024-08-05 08:36:15,237 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-08-05T08:36:15.237868', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:15,238 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:15,239 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:15,239 - using serial LDA version on this node
-2024-08-05 08:36:15,239 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:15,239 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:15,243 - -8.016 per-word bound, 258.8 perplexity estimate based on a held-out corpus of 1 documents with 2138 words
-2024-08-05 08:36:15,243 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:15,244 - topic #0 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"Dudley" + 0.005*"arrangements" + 0.005*"always" + 0.005*"oversight" + 0.005*"quality" + 0.005*"well" + 0.004*"plans" + 0.004*"However"
-2024-08-05 08:36:15,244 - topic #1 (0.333): 0.014*"needs" + 0.013*"’" + 0.010*"Dudley" + 0.006*"well" + 0.006*"plans" + 0.005*"arrangements" + 0.005*"always" + 0.005*"ensure" + 0.005*"quality" + 0.004*"enough"
-2024-08-05 08:36:15,245 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.006*"Dudley" + 0.005*"well" + 0.005*"oversight" + 0.005*"plans" + 0.004*"always" + 0.004*"However" + 0.004*"ensure" + 0.004*"arrangements"
-2024-08-05 08:36:15,245 - topic diff=0.757551, rho=1.000000
-2024-08-05 08:36:15,245 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1050, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:15.245321', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:16,214 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:16,214 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:16,215 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:16,215 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:16,215 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:16,215 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:16,215 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:16,215 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:16,215 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:16,215 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:16,216 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:16,216 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:19,125 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:19,128 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)
-2024-08-05 08:36:19,128 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-08-05T08:36:19.128345', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:19,129 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:19,129 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:19,129 - using serial LDA version on this node
-2024-08-05 08:36:19,130 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:19,130 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:19,134 - -7.968 per-word bound, 250.3 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
-2024-08-05 08:36:19,134 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:19,135 - topic #0 (0.333): 0.009*"’" + 0.005*"needs" + 0.005*"plans" + 0.004*"progress" + 0.004*"May" + 0.004*"well" + 0.004*"Durham" + 0.004*"parents" + 0.004*"ensure" + 0.003*"leaders"
-2024-08-05 08:36:19,135 - topic #1 (0.333): 0.016*"’" + 0.010*"needs" + 0.008*"May" + 0.007*"Durham" + 0.007*"well" + 0.006*"plans" + 0.006*"ensure" + 0.005*"practice" + 0.005*"leaders" + 0.005*"risks"
-2024-08-05 08:36:19,135 - topic #2 (0.333): 0.016*"’" + 0.014*"needs" + 0.008*"Durham" + 0.007*"well" + 0.007*"May" + 0.007*"plans" + 0.007*"ensure" + 0.006*"practice" + 0.005*"family" + 0.005*"2022"
-2024-08-05 08:36:19,135 - topic diff=0.799783, rho=1.000000
-2024-08-05 08:36:19,136 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:19.136124', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:20,220 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:20,220 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:20,221 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:20,221 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:20,221 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:20,221 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:20,221 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:20,221 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:20,222 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:20,222 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:20,222 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:20,222 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:21,831 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:21,833 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)
-2024-08-05 08:36:21,833 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-08-05T08:36:21.833815', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:21,834 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:21,834 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:21,835 - using serial LDA version on this node
-2024-08-05 08:36:21,835 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:21,835 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:21,838 - -7.924 per-word bound, 242.8 perplexity estimate based on a held-out corpus of 1 documents with 2014 words
-2024-08-05 08:36:21,839 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:21,840 - topic #0 (0.333): 0.014*"’" + 0.010*"needs" + 0.009*"well" + 0.009*"plans" + 0.007*"progress" + 0.006*"Riding" + 0.006*"East" + 0.005*"10" + 0.005*"place" + 0.005*"partners"
-2024-08-05 08:36:21,840 - topic #1 (0.333): 0.019*"’" + 0.008*"needs" + 0.008*"well" + 0.007*"plans" + 0.007*"progress" + 0.006*"East" + 0.005*"education" + 0.005*"Riding" + 0.005*"January" + 0.005*"good"
-2024-08-05 08:36:21,840 - topic #2 (0.333): 0.015*"’" + 0.009*"plans" + 0.009*"needs" + 0.006*"well" + 0.006*"Riding" + 0.006*"East" + 0.006*"progress" + 0.005*"2023" + 0.005*"information" + 0.004*"February"
-2024-08-05 08:36:21,840 - topic diff=0.775897, rho=1.000000
-2024-08-05 08:36:21,840 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:21.840927', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:22,715 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:22,716 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:22,716 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:22,716 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:22,716 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:22,716 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:22,717 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:22,717 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:22,717 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:22,717 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:22,717 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:22,717 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:24,580 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:24,584 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)
-2024-08-05 08:36:24,584 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-08-05T08:36:24.584863', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:24,586 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:24,586 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:24,587 - using serial LDA version on this node
-2024-08-05 08:36:24,587 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:24,587 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:24,594 - -8.075 per-word bound, 269.7 perplexity estimate based on a held-out corpus of 1 documents with 2220 words
-2024-08-05 08:36:24,594 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:24,596 - topic #0 (0.333): 0.018*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"including" + 0.007*"East" + 0.007*"Sussex" + 0.006*"progress" + 0.006*"impact" + 0.005*"plans" + 0.005*"provide"
-2024-08-05 08:36:24,596 - topic #1 (0.333): 0.019*"’" + 0.009*"plans" + 0.009*"well" + 0.008*"needs" + 0.007*"Sussex" + 0.006*"East" + 0.006*"progress" + 0.005*"effective" + 0.005*"education" + 0.005*"impact"
-2024-08-05 08:36:24,597 - topic #2 (0.333): 0.011*"’" + 0.008*"well" + 0.008*"plans" + 0.007*"needs" + 0.006*"progress" + 0.005*"East" + 0.005*"impact" + 0.005*"experiences" + 0.004*"time" + 0.004*"effective"
-2024-08-05 08:36:24,597 - topic diff=0.757942, rho=1.000000
-2024-08-05 08:36:24,597 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1111, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:24.597520', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:25,583 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:25,584 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:25,584 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:25,584 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:25,584 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:25,584 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:25,585 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:25,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:25,585 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:25,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:25,585 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:25,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:27,265 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:27,267 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)
-2024-08-05 08:36:27,267 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-08-05T08:36:27.267746', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:27,268 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:27,269 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:27,269 - using serial LDA version on this node
-2024-08-05 08:36:27,269 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:27,269 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:27,273 - -8.011 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2686 words
-2024-08-05 08:36:27,273 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:27,275 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"progress" + 0.005*"risk" + 0.005*"supported" + 0.005*"parents" + 0.005*"family" + 0.005*"understand" + 0.004*"Essex"
-2024-08-05 08:36:27,275 - topic #1 (0.333): 0.021*"’" + 0.009*"well" + 0.007*"progress" + 0.006*"needs" + 0.006*"plans" + 0.006*"family" + 0.005*"leaders" + 0.005*"new" + 0.005*"Essex" + 0.005*"‘"
-2024-08-05 08:36:27,275 - topic #2 (0.333): 0.013*"’" + 0.007*"plans" + 0.006*"progress" + 0.005*"needs" + 0.005*"experiences" + 0.005*"well" + 0.005*"parents" + 0.005*"helped" + 0.005*"Essex" + 0.004*"understand"
-2024-08-05 08:36:27,275 - topic diff=0.807635, rho=1.000000
-2024-08-05 08:36:27,275 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:27.275740', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:28,375 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:28,375 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:28,375 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:28,376 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:28,376 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:28,376 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:28,376 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:28,376 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:28,377 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:28,377 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:28,377 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:28,377 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:31,841 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:31,843 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)
-2024-08-05 08:36:31,843 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-08-05T08:36:31.843906', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:31,844 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:31,845 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:31,845 - using serial LDA version on this node
-2024-08-05 08:36:31,845 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:31,845 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:31,849 - -8.042 per-word bound, 263.5 perplexity estimate based on a held-out corpus of 1 documents with 2356 words
-2024-08-05 08:36:31,849 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:31,850 - topic #0 (0.333): 0.013*"’" + 0.008*"effective" + 0.007*"good" + 0.007*"quality" + 0.007*"practice" + 0.006*"needs" + 0.005*"well" + 0.005*"improve" + 0.005*"need" + 0.004*"progress"
-2024-08-05 08:36:31,851 - topic #1 (0.333): 0.014*"’" + 0.010*"effective" + 0.007*"practice" + 0.007*"good" + 0.006*"needs" + 0.006*"well" + 0.006*"timely" + 0.006*"quality" + 0.005*"early" + 0.005*"improve"
-2024-08-05 08:36:31,851 - topic #2 (0.333): 0.014*"’" + 0.007*"effective" + 0.006*"good" + 0.005*"plans" + 0.005*"practice" + 0.005*"timely" + 0.005*"quality" + 0.005*"needs" + 0.005*"well" + 0.004*"home"
-2024-08-05 08:36:31,851 - topic diff=0.768875, rho=1.000000
-2024-08-05 08:36:31,851 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:31.851566', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:33,178 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:33,178 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:33,179 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:33,179 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:33,179 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:33,179 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:33,179 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:33,179 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:33,180 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:33,180 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:33,180 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:33,180 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:34,732 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:34,737 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)
-2024-08-05 08:36:34,737 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-08-05T08:36:34.737507', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:34,739 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:34,739 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:34,739 - using serial LDA version on this node
-2024-08-05 08:36:34,740 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:34,740 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:34,744 - -8.064 per-word bound, 267.6 perplexity estimate based on a held-out corpus of 1 documents with 2579 words
-2024-08-05 08:36:34,744 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:34,746 - topic #0 (0.333): 0.018*"’" + 0.009*"plans" + 0.008*"needs" + 0.007*"2022" + 0.006*"February" + 0.005*"protection" + 0.005*"timely" + 0.005*"appropriate" + 0.005*"18" + 0.005*"well"
-2024-08-05 08:36:34,746 - topic #1 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"2022" + 0.006*"February" + 0.006*"well" + 0.005*"plans" + 0.004*"appropriate" + 0.004*"education" + 0.004*"Gloucestershire" + 0.004*"family"
-2024-08-05 08:36:34,746 - topic #2 (0.333): 0.020*"’" + 0.008*"February" + 0.008*"needs" + 0.006*"2022" + 0.006*"progress" + 0.006*"well" + 0.006*"Gloucestershire" + 0.005*"plans" + 0.005*"experienced" + 0.005*"good"
-2024-08-05 08:36:34,746 - topic diff=0.825526, rho=1.000000
-2024-08-05 08:36:34,746 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:34.746731', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:35,665 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:35,665 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:35,666 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:35,666 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:35,666 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:35,666 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:35,667 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:35,667 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:35,667 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:35,667 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:35,668 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:35,668 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:37,307 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:37,309 - built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)
-2024-08-05 08:36:37,309 - Dictionary lifecycle event {'msg': "built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)", 'datetime': '2024-08-05T08:36:37.309929', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:37,311 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:37,311 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:37,311 - using serial LDA version on this node
-2024-08-05 08:36:37,311 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:37,311 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:37,315 - -8.058 per-word bound, 266.4 perplexity estimate based on a held-out corpus of 1 documents with 2652 words
-2024-08-05 08:36:37,316 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:37,317 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"including" + 0.005*"quality" + 0.005*"recently" + 0.005*"protection" + 0.005*"Halton" + 0.004*"need" + 0.004*"many" + 0.004*"plans"
-2024-08-05 08:36:37,317 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.007*"Halton" + 0.007*"quality" + 0.006*"plans" + 0.005*"many" + 0.005*"need" + 0.005*"Leaders" + 0.005*"including" + 0.005*"13"
-2024-08-05 08:36:37,317 - topic #2 (0.333): 0.019*"’" + 0.007*"many" + 0.006*"Halton" + 0.006*"needs" + 0.005*"need" + 0.005*"quality" + 0.005*"including" + 0.005*"13" + 0.004*"protection" + 0.004*"Leaders"
-2024-08-05 08:36:37,317 - topic diff=0.800961, rho=1.000000
-2024-08-05 08:36:37,318 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1172, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:37.318138', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:38,330 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:38,330 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:38,330 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:38,330 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:38,331 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:38,331 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:38,331 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:38,331 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:38,331 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:38,331 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:38,332 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:38,332 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:40,028 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:40,031 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)
-2024-08-05 08:36:40,031 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)", 'datetime': '2024-08-05T08:36:40.031266', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:40,032 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:40,032 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:40,032 - using serial LDA version on this node
-2024-08-05 08:36:40,033 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:40,033 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:40,036 - -7.976 per-word bound, 251.7 perplexity estimate based on a held-out corpus of 1 documents with 2524 words
-2024-08-05 08:36:40,036 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:40,038 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"plans" + 0.007*"family" + 0.006*"progress" + 0.006*"carers" + 0.005*"needs" + 0.005*"new" + 0.005*"receive" + 0.005*"quality"
-2024-08-05 08:36:40,038 - topic #1 (0.333): 0.021*"’" + 0.008*"family" + 0.007*"progress" + 0.007*"new" + 0.006*"plans" + 0.006*"well" + 0.006*"Hampshire" + 0.005*"practice" + 0.005*"achieve" + 0.005*"understand"
-2024-08-05 08:36:40,038 - topic #2 (0.333): 0.011*"’" + 0.008*"new" + 0.007*"well" + 0.007*"quality" + 0.006*"family" + 0.006*"plans" + 0.005*"progress" + 0.005*"receive" + 0.004*"practice" + 0.004*"parents"
-2024-08-05 08:36:40,038 - topic diff=0.811314, rho=1.000000
-2024-08-05 08:36:40,038 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:40.038835', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:41,020 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:41,021 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:41,022 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:41,022 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:41,022 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:41,022 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:41,023 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:41,023 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:41,023 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:41,023 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:41,023 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:41,023 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:42,873 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:42,876 - built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)
-2024-08-05 08:36:42,876 - Dictionary lifecycle event {'msg': "built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)", 'datetime': '2024-08-05T08:36:42.876207', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:42,877 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:42,877 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:42,877 - using serial LDA version on this node
-2024-08-05 08:36:42,878 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:42,878 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:42,882 - -8.073 per-word bound, 269.3 perplexity estimate based on a held-out corpus of 1 documents with 2584 words
-2024-08-05 08:36:42,882 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:42,883 - topic #0 (0.333): 0.016*"’" + 0.008*"Hartlepool" + 0.008*"March" + 0.006*"needs" + 0.006*"leaders" + 0.006*"well" + 0.006*"effective" + 0.005*"supported" + 0.005*"strong" + 0.005*"good"
-2024-08-05 08:36:42,884 - topic #1 (0.333): 0.025*"’" + 0.008*"March" + 0.008*"needs" + 0.007*"Hartlepool" + 0.006*"well" + 0.005*"18" + 0.005*"leaders" + 0.005*"clear" + 0.005*"ensure" + 0.005*"plans"
-2024-08-05 08:36:42,884 - topic #2 (0.333): 0.017*"’" + 0.006*"Hartlepool" + 0.006*"March" + 0.006*"needs" + 0.005*"well" + 0.004*"plans" + 0.004*"leaders" + 0.004*"ensure" + 0.004*"clear" + 0.004*"strong"
-2024-08-05 08:36:42,884 - topic diff=0.796629, rho=1.000000
-2024-08-05 08:36:42,884 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1171, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:42.884560', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:44,033 - Inspection date 2024-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:44,033 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:44,034 - Inspection date 2024-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:44,034 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:44,034 - Inspection date 2024-03-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:44,034 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:44,034 - Inspection date 2024-03-18 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:44,034 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:44,034 - Inspection date 2024-03-18 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:44,035 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:44,035 - Inspection date 2024-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:44,035 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:46,010 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:46,013 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
-2024-08-05 08:36:46,013 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-08-05T08:36:46.013520', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:46,014 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:46,014 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:46,014 - using serial LDA version on this node
-2024-08-05 08:36:46,015 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:46,015 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:46,019 - -8.044 per-word bound, 263.9 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
-2024-08-05 08:36:46,019 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:46,020 - topic #0 (0.333): 0.014*"’" + 0.006*"impact" + 0.006*"practice" + 0.005*"many" + 0.005*"lack" + 0.005*"needs" + 0.005*"18" + 0.005*"oversight" + 0.005*"Herefordshire" + 0.005*"progress"
-2024-08-05 08:36:46,021 - topic #1 (0.333): 0.023*"’" + 0.006*"practice" + 0.005*"needs" + 0.005*"Herefordshire" + 0.004*"impact" + 0.004*"many" + 0.004*"agency" + 0.004*"plans" + 0.004*"2022" + 0.004*"lack"
-2024-08-05 08:36:46,021 - topic #2 (0.333): 0.014*"’" + 0.006*"Herefordshire" + 0.006*"lack" + 0.005*"practice" + 0.005*"plans" + 0.005*"progress" + 0.004*"carers" + 0.004*"July" + 0.004*"needs" + 0.004*"quality"
-2024-08-05 08:36:46,021 - topic diff=0.784809, rho=1.000000
-2024-08-05 08:36:46,021 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:46.021533', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:46,943 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:46,944 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:46,944 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:46,944 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:46,944 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:46,944 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:46,945 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:46,945 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:46,945 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:46,945 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:46,945 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:46,945 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:48,492 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:48,495 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)
-2024-08-05 08:36:48,495 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-08-05T08:36:48.495674', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:48,496 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:48,496 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:48,497 - using serial LDA version on this node
-2024-08-05 08:36:48,497 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:48,497 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:48,501 - -8.136 per-word bound, 281.3 perplexity estimate based on a held-out corpus of 1 documents with 2456 words
-2024-08-05 08:36:48,501 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:48,503 - topic #0 (0.333): 0.029*"’" + 0.007*"well" + 0.007*"Hertfordshire" + 0.006*"needs" + 0.006*"receive" + 0.005*"plans" + 0.005*"23" + 0.005*"need" + 0.004*"‘" + 0.004*"2023"
-2024-08-05 08:36:48,503 - topic #1 (0.333): 0.016*"’" + 0.006*"needs" + 0.004*"Hertfordshire" + 0.004*"receive" + 0.004*"positive" + 0.004*"well" + 0.003*"family" + 0.003*"27" + 0.003*"23" + 0.003*"‘"
-2024-08-05 08:36:48,503 - topic #2 (0.333): 0.019*"’" + 0.007*"well" + 0.007*"Hertfordshire" + 0.006*"needs" + 0.005*"leaders" + 0.004*"risk" + 0.004*"positive" + 0.004*"plans" + 0.004*"2023" + 0.004*"January"
-2024-08-05 08:36:48,503 - topic diff=0.808111, rho=1.000000
-2024-08-05 08:36:48,503 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:48.503633', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:50,264 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:50,264 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:50,265 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:50,265 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:50,265 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:50,265 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:50,265 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:50,265 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:50,265 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:50,265 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:50,265 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:50,266 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:51,883 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:51,885 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)
-2024-08-05 08:36:51,885 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-08-05T08:36:51.885595', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:51,886 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:51,886 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:51,886 - using serial LDA version on this node
-2024-08-05 08:36:51,887 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:51,887 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:51,891 - -7.958 per-word bound, 248.6 perplexity estimate based on a held-out corpus of 1 documents with 1934 words
-2024-08-05 08:36:51,891 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:51,894 - topic #0 (0.333): 0.017*"’" + 0.008*"leaders" + 0.005*"3" + 0.005*"plans" + 0.005*"needs" + 0.005*"Wight" + 0.005*"progress" + 0.005*"PAs" + 0.005*"improve" + 0.005*"experiences"
-2024-08-05 08:36:51,894 - topic #1 (0.333): 0.018*"’" + 0.008*"leaders" + 0.006*"Isle" + 0.005*"well" + 0.005*"needs" + 0.005*"3" + 0.005*"Wight" + 0.005*"protection" + 0.005*"supported" + 0.005*"progress"
-2024-08-05 08:36:51,894 - topic #2 (0.333): 0.017*"’" + 0.009*"leaders" + 0.007*"well" + 0.006*"time" + 0.006*"needs" + 0.006*"good" + 0.005*"Senior" + 0.005*"plans" + 0.005*"October" + 0.005*"supported"
-2024-08-05 08:36:51,894 - topic diff=0.768122, rho=1.000000
-2024-08-05 08:36:51,894 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:51.894665', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:52,805 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:52,805 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:52,805 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:52,805 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:52,806 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:52,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:52,806 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:52,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:52,806 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:52,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:52,807 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:52,807 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:55,361 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:55,364 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)
-2024-08-05 08:36:55,364 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-08-05T08:36:55.364763', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:55,365 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:55,366 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:55,366 - using serial LDA version on this node
-2024-08-05 08:36:55,366 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:55,366 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:55,371 - -8.174 per-word bound, 288.8 perplexity estimate based on a held-out corpus of 1 documents with 2888 words
-2024-08-05 08:36:55,371 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:55,372 - topic #0 (0.333): 0.021*"’" + 0.009*"Kent" + 0.008*"needs" + 0.007*"well" + 0.006*"Council" + 0.006*"supported" + 0.005*"County" + 0.004*"progress" + 0.004*"2022" + 0.004*"ensure"
-2024-08-05 08:36:55,372 - topic #1 (0.333): 0.015*"’" + 0.009*"Kent" + 0.006*"Council" + 0.006*"County" + 0.006*"needs" + 0.005*"supported" + 0.005*"progress" + 0.004*"well" + 0.004*"leaders" + 0.004*"provide"
-2024-08-05 08:36:55,373 - topic #2 (0.333): 0.016*"’" + 0.011*"Kent" + 0.007*"needs" + 0.006*"well" + 0.006*"practice" + 0.005*"supported" + 0.005*"County" + 0.005*"Council" + 0.005*"progress" + 0.004*"leaders"
-2024-08-05 08:36:55,373 - topic diff=0.804326, rho=1.000000
-2024-08-05 08:36:55,373 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1298, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:55.373465', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:56,302 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:56,302 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:56,302 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:56,303 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:56,303 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:56,303 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:56,303 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:56,303 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:56,303 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:56,303 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:56,304 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:56,304 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:57,710 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:36:57,712 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)
-2024-08-05 08:36:57,713 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-08-05T08:36:57.713057', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:57,713 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:36:57,714 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:36:57,714 - using serial LDA version on this node
-2024-08-05 08:36:57,714 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:36:57,714 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:36:57,718 - -7.943 per-word bound, 246.2 perplexity estimate based on a held-out corpus of 1 documents with 1970 words
-2024-08-05 08:36:57,718 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:36:57,719 - topic #0 (0.333): 0.011*"’" + 0.008*"planning" + 0.006*"protection" + 0.006*"management" + 0.006*"need" + 0.005*"well" + 0.005*"number" + 0.005*"risks" + 0.005*"Hull" + 0.005*"teams"
-2024-08-05 08:36:57,719 - topic #1 (0.333): 0.016*"’" + 0.007*"number" + 0.007*"planning" + 0.006*"well" + 0.006*"protection" + 0.005*"agency" + 0.005*"progress" + 0.005*"impact" + 0.005*"needs" + 0.005*"Hull"
-2024-08-05 08:36:57,719 - topic #2 (0.333): 0.019*"’" + 0.008*"practice" + 0.008*"number" + 0.006*"Hull" + 0.006*"need" + 0.006*"well" + 0.006*"management" + 0.005*"oversight" + 0.005*"protection" + 0.005*"risks"
-2024-08-05 08:36:57,720 - topic diff=0.752681, rho=1.000000
-2024-08-05 08:36:57,720 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:36:57.720221', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:36:58,690 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:36:58,690 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:58,690 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:36:58,690 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:58,691 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:36:58,691 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:58,691 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:36:58,691 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:58,691 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:36:58,691 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:36:58,692 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:36:58,692 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:00,768 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:00,770 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)
-2024-08-05 08:37:00,771 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)", 'datetime': '2024-08-05T08:37:00.771070', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:00,772 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:00,772 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:00,772 - using serial LDA version on this node
-2024-08-05 08:37:00,773 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:00,773 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:00,777 - -8.058 per-word bound, 266.5 perplexity estimate based on a held-out corpus of 1 documents with 2489 words
-2024-08-05 08:37:00,777 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:00,779 - topic #0 (0.333): 0.012*"’" + 0.007*"practice" + 0.007*"quality" + 0.006*"Senior" + 0.006*"good" + 0.005*"training" + 0.005*"protection" + 0.005*"well" + 0.005*"permanence" + 0.005*"plans"
-2024-08-05 08:37:00,779 - topic #1 (0.333): 0.013*"’" + 0.007*"quality" + 0.007*"good" + 0.006*"needs" + 0.005*"practice" + 0.005*"senior" + 0.005*"plans" + 0.005*"well" + 0.004*"protection" + 0.004*"permanence"
-2024-08-05 08:37:00,779 - topic #2 (0.333): 0.010*"’" + 0.006*"practice" + 0.006*"permanence" + 0.005*"quality" + 0.005*"plans" + 0.005*"well" + 0.005*"training" + 0.005*"good" + 0.005*"Senior" + 0.005*"protection"
-2024-08-05 08:37:00,779 - topic diff=0.789291, rho=1.000000
-2024-08-05 08:37:00,779 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:00.779814', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:01,831 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:01,831 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:01,831 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:01,831 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:01,832 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:01,832 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:01,832 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:01,832 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:01,832 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:01,832 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:01,833 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:01,833 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:03,164 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:03,167 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)
-2024-08-05 08:37:03,167 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-08-05T08:37:03.167365', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:03,168 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:03,168 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:03,168 - using serial LDA version on this node
-2024-08-05 08:37:03,168 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:03,169 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:03,172 - -7.832 per-word bound, 227.9 perplexity estimate based on a held-out corpus of 1 documents with 1837 words
-2024-08-05 08:37:03,172 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:03,173 - topic #0 (0.333): 0.014*"’" + 0.007*"progress" + 0.007*"Knowsley" + 0.006*"plans" + 0.006*"quality" + 0.006*"2021" + 0.005*"need" + 0.005*"leaders" + 0.005*"22" + 0.005*"experiences"
-2024-08-05 08:37:03,173 - topic #1 (0.333): 0.017*"’" + 0.010*"progress" + 0.007*"quality" + 0.007*"needs" + 0.007*"plans" + 0.006*"2021" + 0.006*"need" + 0.005*"Knowsley" + 0.005*"experiences" + 0.005*"good"
-2024-08-05 08:37:03,173 - topic #2 (0.333): 0.012*"’" + 0.010*"needs" + 0.008*"plans" + 0.007*"progress" + 0.006*"quality" + 0.006*"Knowsley" + 0.005*"2021" + 0.005*"good" + 0.005*"education" + 0.005*"experiences"
-2024-08-05 08:37:03,173 - topic diff=0.745038, rho=1.000000
-2024-08-05 08:37:03,174 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=886, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:03.174056', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:04,079 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:04,079 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:04,080 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:04,080 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:04,080 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:04,080 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:04,080 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:04,080 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:04,081 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:04,081 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:04,081 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:04,081 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:05,636 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:05,639 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)
-2024-08-05 08:37:05,639 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-08-05T08:37:05.639617', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:05,640 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:05,640 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:05,641 - using serial LDA version on this node
-2024-08-05 08:37:05,641 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:05,641 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:05,645 - -7.972 per-word bound, 251.0 perplexity estimate based on a held-out corpus of 1 documents with 2263 words
-2024-08-05 08:37:05,645 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:05,646 - topic #0 (0.333): 0.014*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"Lancashire" + 0.006*"need" + 0.005*"positive" + 0.005*"progress" + 0.005*"plans" + 0.005*"practice" + 0.005*"health"
-2024-08-05 08:37:05,646 - topic #1 (0.333): 0.014*"’" + 0.009*"well" + 0.006*"supported" + 0.006*"needs" + 0.006*"need" + 0.006*"Lancashire" + 0.005*"9" + 0.005*"practice" + 0.005*"positive" + 0.005*"plans"
-2024-08-05 08:37:05,646 - topic #2 (0.333): 0.020*"’" + 0.009*"need" + 0.008*"well" + 0.007*"needs" + 0.006*"Lancashire" + 0.006*"plans" + 0.005*"number" + 0.005*"health" + 0.005*"practice" + 0.005*"parents"
-2024-08-05 08:37:05,647 - topic diff=0.777375, rho=1.000000
-2024-08-05 08:37:05,647 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:05.647188', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:06,643 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:06,643 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:06,643 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:06,643 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:06,644 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:06,644 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:06,644 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:06,644 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:06,644 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:06,644 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:06,644 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:06,644 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:08,278 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:08,280 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)
-2024-08-05 08:37:08,280 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-08-05T08:37:08.280938', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:08,281 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:08,282 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:08,282 - using serial LDA version on this node
-2024-08-05 08:37:08,282 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:08,282 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:08,286 - -8.010 per-word bound, 257.8 perplexity estimate based on a held-out corpus of 1 documents with 2261 words
-2024-08-05 08:37:08,286 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:08,287 - topic #0 (0.333): 0.015*"’" + 0.008*"needs" + 0.006*"Leeds" + 0.006*"risk" + 0.005*"plans" + 0.005*"well" + 0.005*"ensure" + 0.005*"4" + 0.004*"practice" + 0.004*"supported"
-2024-08-05 08:37:08,287 - topic #1 (0.333): 0.016*"’" + 0.009*"Leeds" + 0.007*"well" + 0.007*"needs" + 0.005*"practice" + 0.004*"protection" + 0.004*"21" + 0.004*"benefit" + 0.004*"risk" + 0.004*"supported"
-2024-08-05 08:37:08,288 - topic #2 (0.333): 0.017*"’" + 0.007*"Leeds" + 0.006*"risk" + 0.005*"needs" + 0.005*"well" + 0.005*"practice" + 0.004*"protection" + 0.004*"relationships" + 0.004*"4" + 0.004*"March"
-2024-08-05 08:37:08,288 - topic diff=0.774110, rho=1.000000
-2024-08-05 08:37:08,288 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1071, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:08.288393', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:09,283 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:09,283 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:09,283 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:09,283 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:09,283 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:09,283 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:09,284 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:09,284 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:09,284 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:09,284 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:09,284 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:09,284 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:11,245 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:11,247 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)
-2024-08-05 08:37:11,248 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-08-05T08:37:11.248077', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:11,248 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:11,249 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:11,249 - using serial LDA version on this node
-2024-08-05 08:37:11,249 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:11,249 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:11,253 - -7.870 per-word bound, 233.9 perplexity estimate based on a held-out corpus of 1 documents with 1950 words
-2024-08-05 08:37:11,253 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:11,254 - topic #0 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"2021" + 0.006*"Leicester" + 0.006*"needs" + 0.005*"good" + 0.004*"including" + 0.004*"number" + 0.004*"October" + 0.004*"improve"
-2024-08-05 08:37:11,254 - topic #1 (0.333): 0.024*"’" + 0.009*"2021" + 0.009*"well" + 0.008*"Leicester" + 0.007*"needs" + 0.006*"good" + 0.006*"number" + 0.006*"20" + 0.006*"1" + 0.006*"ensure"
-2024-08-05 08:37:11,254 - topic #2 (0.333): 0.016*"’" + 0.010*"well" + 0.008*"2021" + 0.008*"Leicester" + 0.007*"ensure" + 0.007*"needs" + 0.006*"good" + 0.005*"Council" + 0.004*"improve" + 0.004*"number"
-2024-08-05 08:37:11,254 - topic diff=0.794091, rho=1.000000
-2024-08-05 08:37:11,255 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=932, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:11.255089', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:12,417 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:12,417 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:12,417 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:12,417 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:12,417 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:12,417 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:12,418 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:12,418 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:12,418 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:12,418 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:12,418 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:12,418 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:14,718 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:14,721 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)
-2024-08-05 08:37:14,721 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)", 'datetime': '2024-08-05T08:37:14.721767', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:14,722 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:14,723 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:14,723 - using serial LDA version on this node
-2024-08-05 08:37:14,723 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:14,723 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:14,727 - -8.107 per-word bound, 275.7 perplexity estimate based on a held-out corpus of 1 documents with 2745 words
-2024-08-05 08:37:14,727 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:14,729 - topic #0 (0.333): 0.016*"’" + 0.009*"well" + 0.006*"Leicestershire" + 0.006*"plans" + 0.005*"needs" + 0.005*"experiences" + 0.005*"need" + 0.005*"family" + 0.004*"understand" + 0.004*"3"
-2024-08-05 08:37:14,729 - topic #1 (0.333): 0.022*"’" + 0.008*"well" + 0.006*"Leicestershire" + 0.006*"family" + 0.006*"risk" + 0.006*"understand" + 0.005*"need" + 0.005*"progress" + 0.005*"needs" + 0.005*"experiences"
-2024-08-05 08:37:14,729 - topic #2 (0.333): 0.015*"’" + 0.009*"well" + 0.007*"Leicestershire" + 0.006*"needs" + 0.006*"progress" + 0.006*"experiences" + 0.006*"family" + 0.005*"need" + 0.005*"PAs" + 0.005*"plans"
-2024-08-05 08:37:14,729 - topic diff=0.813383, rho=1.000000
-2024-08-05 08:37:14,730 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:14.730100', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:15,758 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:15,759 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:15,759 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:15,760 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:15,760 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:15,760 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:15,761 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:15,761 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:15,761 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:15,761 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:15,761 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:15,761 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:17,825 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:17,828 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)
-2024-08-05 08:37:17,829 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-08-05T08:37:17.829113', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:17,830 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:17,830 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:17,830 - using serial LDA version on this node
-2024-08-05 08:37:17,831 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:17,831 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:17,835 - -8.189 per-word bound, 291.9 perplexity estimate based on a held-out corpus of 1 documents with 2927 words
-2024-08-05 08:37:17,835 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:17,837 - topic #0 (0.333): 0.031*"’" + 0.008*"Lincolnshire" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.005*"family" + 0.005*"24" + 0.004*"progress" + 0.004*"need" + 0.004*"28"
-2024-08-05 08:37:17,837 - topic #1 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"Lincolnshire" + 0.004*"progress" + 0.004*"well" + 0.004*"number" + 0.004*"working" + 0.004*"plans" + 0.004*"family" + 0.003*"2023"
-2024-08-05 08:37:17,837 - topic #2 (0.333): 0.012*"’" + 0.008*"Lincolnshire" + 0.006*"needs" + 0.005*"well" + 0.005*"progress" + 0.004*"supported" + 0.004*"April" + 0.004*"family" + 0.004*"education" + 0.004*"24"
-2024-08-05 08:37:17,837 - topic diff=0.794156, rho=1.000000
-2024-08-05 08:37:17,837 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1323, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:17.837877', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:18,808 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:18,809 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:18,809 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:18,809 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:18,810 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:18,810 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:18,810 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:18,810 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:18,810 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:18,811 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:18,811 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:18,811 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:21,070 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:21,073 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
-2024-08-05 08:37:21,073 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-08-05T08:37:21.073485', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:21,074 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:21,074 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:21,075 - using serial LDA version on this node
-2024-08-05 08:37:21,075 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:21,075 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:21,079 - -7.993 per-word bound, 254.8 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
-2024-08-05 08:37:21,079 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:21,080 - topic #0 (0.333): 0.021*"’" + 0.007*"needs" + 0.006*"Liverpool" + 0.006*"need" + 0.006*"quality" + 0.005*"always" + 0.005*"protection" + 0.005*"timely" + 0.005*"practice" + 0.004*"senior"
-2024-08-05 08:37:21,081 - topic #1 (0.333): 0.023*"’" + 0.008*"practice" + 0.008*"needs" + 0.008*"always" + 0.007*"need" + 0.006*"Liverpool" + 0.005*"quality" + 0.005*"PAs" + 0.005*"2023" + 0.005*"13"
-2024-08-05 08:37:21,081 - topic #2 (0.333): 0.009*"’" + 0.006*"practice" + 0.005*"quality" + 0.004*"always" + 0.004*"needs" + 0.004*"13" + 0.004*"need" + 0.004*"Liverpool" + 0.004*"protection" + 0.004*"24"
-2024-08-05 08:37:21,081 - topic diff=0.853351, rho=1.000000
-2024-08-05 08:37:21,081 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1134, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:21.081558', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:22,101 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:22,101 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:22,102 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:22,102 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:22,102 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:22,102 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:22,102 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:22,102 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:22,103 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:22,103 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:22,103 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:22,103 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:24,310 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:24,314 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)
-2024-08-05 08:37:24,315 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-08-05T08:37:24.315220', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:24,317 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:24,317 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:24,317 - using serial LDA version on this node
-2024-08-05 08:37:24,318 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:24,318 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:24,325 - -8.087 per-word bound, 272.0 perplexity estimate based on a held-out corpus of 1 documents with 2610 words
-2024-08-05 08:37:24,325 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:24,327 - topic #0 (0.333): 0.027*"’" + 0.007*"needs" + 0.007*"plans" + 0.006*"good" + 0.005*"well" + 0.005*"information" + 0.005*"practice" + 0.004*"carers" + 0.004*"21" + 0.004*"Dagenham"
-2024-08-05 08:37:24,328 - topic #1 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"progress" + 0.005*"carers" + 0.005*"practice" + 0.005*"plans" + 0.004*"ensure" + 0.004*"Barking" + 0.004*"planning" + 0.004*"Dagenham"
-2024-08-05 08:37:24,328 - topic #2 (0.333): 0.022*"’" + 0.009*"needs" + 0.006*"good" + 0.006*"well" + 0.005*"London" + 0.005*"carers" + 0.005*"plans" + 0.005*"10" + 0.005*"information" + 0.005*"practice"
-2024-08-05 08:37:24,328 - topic diff=0.799015, rho=1.000000
-2024-08-05 08:37:24,328 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1193, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:24.328974', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:25,338 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:25,338 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:25,339 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:25,339 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:25,339 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:25,339 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:25,339 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:25,339 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:25,340 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:25,340 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:25,340 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:25,340 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:27,504 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:27,507 - built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)
-2024-08-05 08:37:27,507 - Dictionary lifecycle event {'msg': "built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)", 'datetime': '2024-08-05T08:37:27.507441', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:27,508 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:27,508 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:27,508 - using serial LDA version on this node
-2024-08-05 08:37:27,509 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:27,509 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:27,513 - -8.055 per-word bound, 266.0 perplexity estimate based on a held-out corpus of 1 documents with 2445 words
-2024-08-05 08:37:27,513 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:27,514 - topic #0 (0.333): 0.029*"’" + 0.010*"needs" + 0.008*"Barnet" + 0.007*"well" + 0.007*"plans" + 0.005*"understand" + 0.005*"experiences" + 0.004*"14" + 0.004*"10" + 0.004*"inform"
-2024-08-05 08:37:27,515 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"Barnet" + 0.006*"well" + 0.005*"risk" + 0.005*"2024" + 0.004*"information" + 0.004*"10" + 0.004*"effective"
-2024-08-05 08:37:27,515 - topic #2 (0.333): 0.015*"’" + 0.009*"well" + 0.007*"needs" + 0.007*"Barnet" + 0.007*"plans" + 0.006*"experiences" + 0.004*"June" + 0.004*"need" + 0.004*"risk" + 0.004*"10"
-2024-08-05 08:37:27,515 - topic diff=0.789493, rho=1.000000
-2024-08-05 08:37:27,515 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1132, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:27.515575', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:28,501 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:28,501 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:28,501 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:28,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:28,502 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:28,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:28,502 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:28,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:28,502 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:28,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:28,503 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:28,503 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:30,739 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:30,741 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)
-2024-08-05 08:37:30,741 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-08-05T08:37:30.741964', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:30,743 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:30,743 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:30,743 - using serial LDA version on this node
-2024-08-05 08:37:30,743 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:30,743 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:30,747 - -8.103 per-word bound, 274.9 perplexity estimate based on a held-out corpus of 1 documents with 2563 words
-2024-08-05 08:37:30,747 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:30,749 - topic #0 (0.333): 0.022*"’" + 0.007*"well" + 0.006*"need" + 0.006*"needs" + 0.006*"effective" + 0.005*"plans" + 0.005*"including" + 0.005*"Bexley" + 0.005*"practice" + 0.004*"10"
-2024-08-05 08:37:30,749 - topic #1 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"Bexley" + 0.005*"need" + 0.005*"plans" + 0.005*"oversight" + 0.004*"make" + 0.004*"effective" + 0.004*"clear"
-2024-08-05 08:37:30,749 - topic #2 (0.333): 0.018*"’" + 0.006*"effective" + 0.006*"needs" + 0.005*"Bexley" + 0.005*"plans" + 0.005*"well" + 0.005*"10" + 0.005*"need" + 0.004*"level" + 0.004*"6"
-2024-08-05 08:37:30,749 - topic diff=0.779359, rho=1.000000
-2024-08-05 08:37:30,749 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1190, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:30.749928', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:31,697 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:31,697 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:31,697 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:31,697 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:31,697 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:31,697 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:31,698 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:31,698 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:31,698 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:31,698 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:31,698 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:31,698 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:33,620 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:33,623 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)
-2024-08-05 08:37:33,623 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-08-05T08:37:33.623231', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:33,624 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:33,624 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:33,624 - using serial LDA version on this node
-2024-08-05 08:37:33,625 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:33,625 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:33,628 - -7.933 per-word bound, 244.4 perplexity estimate based on a held-out corpus of 1 documents with 2371 words
-2024-08-05 08:37:33,628 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:33,630 - topic #0 (0.333): 0.023*"’" + 0.008*"well" + 0.007*"leaders" + 0.007*"plans" + 0.006*"progress" + 0.006*"good" + 0.006*"small" + 0.006*"senior" + 0.005*"practice" + 0.005*"number"
-2024-08-05 08:37:33,630 - topic #1 (0.333): 0.010*"’" + 0.007*"well" + 0.006*"plans" + 0.006*"Brent" + 0.005*"progress" + 0.005*"leaders" + 0.005*"good" + 0.004*"timely" + 0.004*"quality" + 0.004*"practice"
-2024-08-05 08:37:33,630 - topic #2 (0.333): 0.015*"’" + 0.010*"well" + 0.008*"leaders" + 0.006*"progress" + 0.006*"number" + 0.006*"plans" + 0.006*"quality" + 0.005*"good" + 0.005*"Brent" + 0.005*"family"
-2024-08-05 08:37:33,630 - topic diff=0.829095, rho=1.000000
-2024-08-05 08:37:33,630 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:33.630937', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:34,619 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:34,620 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:34,620 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:34,620 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:34,620 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:34,620 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:34,620 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:34,621 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:34,621 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:34,621 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:34,621 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:34,621 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:36,843 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:36,846 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)
-2024-08-05 08:37:36,846 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-08-05T08:37:36.846440', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:36,847 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:36,847 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:36,847 - using serial LDA version on this node
-2024-08-05 08:37:36,848 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:36,848 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:36,852 - -8.186 per-word bound, 291.1 perplexity estimate based on a held-out corpus of 1 documents with 2640 words
-2024-08-05 08:37:36,852 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:36,854 - topic #0 (0.333): 0.023*"’" + 0.007*"needs" + 0.007*"Bromley" + 0.006*"well" + 0.005*"plans" + 0.004*"relationships" + 0.004*"education" + 0.004*"practice" + 0.004*"13" + 0.004*"17"
-2024-08-05 08:37:36,854 - topic #1 (0.333): 0.014*"’" + 0.011*"Bromley" + 0.007*"leaders" + 0.006*"well" + 0.005*"needs" + 0.005*"practice" + 0.005*"plans" + 0.004*"experiences" + 0.004*"education" + 0.004*"strong"
-2024-08-05 08:37:36,854 - topic #2 (0.333): 0.022*"’" + 0.009*"Bromley" + 0.008*"needs" + 0.008*"well" + 0.006*"plans" + 0.005*"leaders" + 0.005*"practice" + 0.005*"health" + 0.004*"education" + 0.004*"progress"
-2024-08-05 08:37:36,854 - topic diff=0.768157, rho=1.000000
-2024-08-05 08:37:36,854 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1266, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:36.854673', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:37,752 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:37,752 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:37,753 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:37,753 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:37,753 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:37,753 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:37,753 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:37,753 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:37,753 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:37,754 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:37,754 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:37,754 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:39,893 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:39,895 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)
-2024-08-05 08:37:39,895 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-08-05T08:37:39.895280', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:39,896 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:39,896 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:39,896 - using serial LDA version on this node
-2024-08-05 08:37:39,896 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:39,897 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:39,900 - -8.060 per-word bound, 266.8 perplexity estimate based on a held-out corpus of 1 documents with 1735 words
-2024-08-05 08:37:39,900 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:39,901 - topic #0 (0.333): 0.010*"’" + 0.007*"leaders" + 0.007*"Camden" + 0.006*"practice" + 0.005*"response" + 0.005*"well" + 0.004*"meetings" + 0.004*"2022" + 0.004*"protection" + 0.004*"needs"
-2024-08-05 08:37:39,902 - topic #1 (0.333): 0.010*"’" + 0.007*"Camden" + 0.007*"practice" + 0.007*"leaders" + 0.005*"well" + 0.005*"protection" + 0.004*"needs" + 0.004*"April" + 0.004*"29" + 0.004*"appropriate"
-2024-08-05 08:37:39,902 - topic #2 (0.333): 0.011*"’" + 0.007*"Camden" + 0.006*"needs" + 0.006*"well" + 0.005*"leaders" + 0.005*"protection" + 0.005*"practice" + 0.005*"appropriate" + 0.004*"25" + 0.004*"response"
-2024-08-05 08:37:39,902 - topic diff=0.696284, rho=1.000000
-2024-08-05 08:37:39,902 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=993, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:39.902492', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:40,827 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:40,828 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:40,828 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:40,828 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:40,828 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:40,828 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:40,829 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:40,829 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:40,829 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:40,829 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:40,829 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:40,829 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:42,569 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:42,573 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)
-2024-08-05 08:37:42,573 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-08-05T08:37:42.573554', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:42,574 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:42,574 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:42,575 - using serial LDA version on this node
-2024-08-05 08:37:42,575 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:42,575 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:42,579 - -7.988 per-word bound, 253.8 perplexity estimate based on a held-out corpus of 1 documents with 2209 words
-2024-08-05 08:37:42,579 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:42,581 - topic #0 (0.333): 0.012*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"Croydon" + 0.006*"ensure" + 0.006*"health" + 0.006*"However" + 0.005*"quality" + 0.005*"need" + 0.005*"good"
-2024-08-05 08:37:42,581 - topic #1 (0.333): 0.013*"’" + 0.006*"needs" + 0.005*"Croydon" + 0.005*"quality" + 0.005*"good" + 0.005*"well" + 0.005*"Senior" + 0.005*"health" + 0.005*"need" + 0.004*"effective"
-2024-08-05 08:37:42,581 - topic #2 (0.333): 0.011*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Senior" + 0.006*"need" + 0.005*"plans" + 0.005*"education" + 0.005*"arrangements" + 0.005*"Croydon" + 0.005*"quality"
-2024-08-05 08:37:42,581 - topic diff=0.770404, rho=1.000000
-2024-08-05 08:37:42,581 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:42.581763', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:43,653 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:43,654 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:43,654 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:43,654 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:43,654 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:43,654 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:43,655 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:43,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:43,655 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:43,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:43,655 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:43,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:45,670 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:45,674 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)
-2024-08-05 08:37:45,677 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)", 'datetime': '2024-08-05T08:37:45.677180', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:45,678 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:45,679 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:45,679 - using serial LDA version on this node
-2024-08-05 08:37:45,679 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:45,679 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:45,685 - -8.055 per-word bound, 266.0 perplexity estimate based on a held-out corpus of 1 documents with 2365 words
-2024-08-05 08:37:45,685 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:45,687 - topic #0 (0.333): 0.021*"’" + 0.010*"Ealing" + 0.008*"well" + 0.006*"needs" + 0.006*"plans" + 0.006*"London" + 0.006*"progress" + 0.006*"need" + 0.005*"3" + 0.005*"effective"
-2024-08-05 08:37:45,687 - topic #1 (0.333): 0.013*"’" + 0.006*"progress" + 0.006*"Ealing" + 0.005*"well" + 0.005*"needs" + 0.004*"need" + 0.004*"effective" + 0.003*"including" + 0.003*"3" + 0.003*"improve"
-2024-08-05 08:37:45,687 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"Ealing" + 0.006*"progress" + 0.006*"plans" + 0.006*"needs" + 0.006*"experiences" + 0.005*"effective" + 0.005*"22" + 0.005*"need"
-2024-08-05 08:37:45,687 - topic diff=0.811676, rho=1.000000
-2024-08-05 08:37:45,687 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:45.687887', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:46,685 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:46,685 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:46,686 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:46,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:46,686 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:46,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:46,686 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:46,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:46,687 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:46,687 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:46,687 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:46,687 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:48,540 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:48,543 - built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)
-2024-08-05 08:37:48,544 - Dictionary lifecycle event {'msg': "built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)", 'datetime': '2024-08-05T08:37:48.544181', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:48,545 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:48,546 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:48,546 - using serial LDA version on this node
-2024-08-05 08:37:48,546 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:48,546 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:48,552 - -7.939 per-word bound, 245.3 perplexity estimate based on a held-out corpus of 1 documents with 2104 words
-2024-08-05 08:37:48,553 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:48,555 - topic #0 (0.333): 0.016*"’" + 0.011*"needs" + 0.009*"practice" + 0.008*"good" + 0.008*"ensure" + 0.008*"clear" + 0.008*"effective" + 0.007*"timely" + 0.007*"quality" + 0.006*"Enfield"
-2024-08-05 08:37:48,555 - topic #1 (0.333): 0.007*"’" + 0.006*"needs" + 0.006*"practice" + 0.005*"ensure" + 0.005*"Enfield" + 0.005*"good" + 0.004*"effective" + 0.004*"progress" + 0.004*"clear" + 0.004*"timely"
-2024-08-05 08:37:48,555 - topic #2 (0.333): 0.014*"’" + 0.008*"ensure" + 0.007*"good" + 0.006*"practice" + 0.006*"Enfield" + 0.006*"needs" + 0.006*"quality" + 0.006*"effective" + 0.006*"leaders" + 0.005*"need"
-2024-08-05 08:37:48,555 - topic diff=0.807316, rho=1.000000
-2024-08-05 08:37:48,556 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=999, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:48.556193', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:49,654 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:49,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:49,656 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:49,656 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:49,657 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:49,657 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:49,657 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:49,658 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:49,658 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:49,658 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:49,662 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:49,662 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:51,220 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:51,222 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)
-2024-08-05 08:37:51,222 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)", 'datetime': '2024-08-05T08:37:51.222975', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:51,223 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:51,224 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:51,224 - using serial LDA version on this node
-2024-08-05 08:37:51,224 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:51,224 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:51,228 - -7.989 per-word bound, 254.0 perplexity estimate based on a held-out corpus of 1 documents with 2078 words
-2024-08-05 08:37:51,228 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:51,229 - topic #0 (0.333): 0.017*"’" + 0.010*"Greenwich" + 0.009*"needs" + 0.008*"well" + 0.006*"plans" + 0.005*"3" + 0.005*"7" + 0.005*"2024" + 0.005*"provide" + 0.005*"progress"
-2024-08-05 08:37:51,230 - topic #1 (0.333): 0.016*"’" + 0.011*"Greenwich" + 0.006*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"provide" + 0.004*"Royal" + 0.004*"Borough" + 0.004*"7" + 0.004*"June"
-2024-08-05 08:37:51,230 - topic #2 (0.333): 0.019*"’" + 0.011*"Greenwich" + 0.006*"needs" + 0.006*"plans" + 0.006*"well" + 0.005*"progress" + 0.005*"June" + 0.004*"7" + 0.004*"quality" + 0.004*"3"
-2024-08-05 08:37:51,230 - topic diff=0.757945, rho=1.000000
-2024-08-05 08:37:51,230 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:51.230592', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:52,128 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:52,128 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:52,128 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:52,128 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:52,128 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:52,129 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:52,129 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:52,129 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:52,129 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:52,129 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:52,129 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:52,129 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:54,327 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:54,329 - built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)
-2024-08-05 08:37:54,330 - Dictionary lifecycle event {'msg': "built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)", 'datetime': '2024-08-05T08:37:54.329986', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:54,331 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:54,331 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:54,331 - using serial LDA version on this node
-2024-08-05 08:37:54,331 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:54,331 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:54,335 - -8.003 per-word bound, 256.5 perplexity estimate based on a held-out corpus of 1 documents with 2603 words
-2024-08-05 08:37:54,335 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:54,337 - topic #0 (0.333): 0.014*"’" + 0.010*"practice" + 0.007*"effective" + 0.007*"number" + 0.006*"planning" + 0.006*"needs" + 0.006*"plans" + 0.006*"within" + 0.006*"small" + 0.005*"need"
-2024-08-05 08:37:54,337 - topic #1 (0.333): 0.012*"’" + 0.010*"practice" + 0.006*"plans" + 0.006*"quality" + 0.006*"needs" + 0.006*"planning" + 0.006*"within" + 0.005*"including" + 0.005*"effective" + 0.005*"making"
-2024-08-05 08:37:54,337 - topic #2 (0.333): 0.013*"’" + 0.009*"practice" + 0.008*"number" + 0.006*"planning" + 0.005*"However" + 0.005*"effective" + 0.005*"including" + 0.005*"small" + 0.005*"within" + 0.005*"oversight"
-2024-08-05 08:37:54,337 - topic diff=0.837694, rho=1.000000
-2024-08-05 08:37:54,337 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1122, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:54.337839', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:55,642 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:55,642 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:55,643 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:55,643 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:55,643 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:55,643 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:55,643 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:55,643 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:55,644 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:55,644 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:55,644 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:55,644 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:57,545 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:37:57,548 - built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
-2024-08-05 08:37:57,549 - Dictionary lifecycle event {'msg': "built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-08-05T08:37:57.549078', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:57,550 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:37:57,550 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:37:57,550 - using serial LDA version on this node
-2024-08-05 08:37:57,551 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:37:57,551 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:37:57,555 - -8.203 per-word bound, 294.8 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
-2024-08-05 08:37:57,555 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:37:57,557 - topic #0 (0.333): 0.012*"’" + 0.007*"well" + 0.005*"receive" + 0.005*"needs" + 0.005*"plans" + 0.004*"2024" + 0.004*"understand" + 0.004*"leaders" + 0.004*"Fulham" + 0.004*"effective"
-2024-08-05 08:37:57,557 - topic #1 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"receive" + 0.005*"protection" + 0.005*"Hammersmith" + 0.005*"plans" + 0.005*"Leaders" + 0.005*"supported" + 0.005*"Fulham"
-2024-08-05 08:37:57,557 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.005*"receive" + 0.004*"effective" + 0.004*"11" + 0.004*"needs" + 0.004*"Fulham" + 0.004*"Hammersmith" + 0.004*"place" + 0.004*"leaders"
-2024-08-05 08:37:57,557 - topic diff=0.802116, rho=1.000000
-2024-08-05 08:37:57,557 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1330, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:37:57.557863', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:37:58,409 - Inspection date 2024-03-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:37:58,409 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:58,409 - Inspection date 2024-03-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:37:58,409 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:58,410 - Inspection date 2024-03-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:37:58,410 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:58,410 - Inspection date 2024-03-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:37:58,410 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:58,410 - Inspection date 2024-03-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:37:58,410 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:37:58,410 - Inspection date 2024-03-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:37:58,411 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:00,826 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:00,831 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)
-2024-08-05 08:38:00,838 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-08-05T08:38:00.838952', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:00,841 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:00,841 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:00,842 - using serial LDA version on this node
-2024-08-05 08:38:00,844 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:00,844 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:00,863 - -8.165 per-word bound, 287.0 perplexity estimate based on a held-out corpus of 1 documents with 2620 words
-2024-08-05 08:38:00,867 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:00,869 - topic #0 (0.333): 0.013*"’" + 0.007*"Haringey" + 0.007*"needs" + 0.007*"well" + 0.006*"need" + 0.006*"good" + 0.005*"impact" + 0.004*"plans" + 0.004*"13" + 0.004*"risk"
-2024-08-05 08:38:00,871 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.009*"Haringey" + 0.008*"plans" + 0.005*"24" + 0.005*"well" + 0.005*"good" + 0.005*"progress" + 0.005*"risk" + 0.004*"education"
-2024-08-05 08:38:00,871 - topic #2 (0.333): 0.013*"’" + 0.009*"Haringey" + 0.007*"plans" + 0.007*"needs" + 0.006*"well" + 0.005*"progress" + 0.005*"supported" + 0.005*"good" + 0.004*"need" + 0.004*"education"
-2024-08-05 08:38:00,871 - topic diff=0.770137, rho=1.000000
-2024-08-05 08:38:00,872 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1252, num_topics=3, decay=0.5, chunksize=2000> in 0.03s', 'datetime': '2024-08-05T08:38:00.872003', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:01,797 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:01,798 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:01,798 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:01,798 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:01,798 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:01,798 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:01,799 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:01,799 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:01,799 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:01,799 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:01,799 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:01,799 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:03,718 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:03,720 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)
-2024-08-05 08:38:03,720 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-08-05T08:38:03.720406', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:03,721 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:03,721 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:03,721 - using serial LDA version on this node
-2024-08-05 08:38:03,722 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:03,722 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:03,725 - -7.970 per-word bound, 250.8 perplexity estimate based on a held-out corpus of 1 documents with 1732 words
-2024-08-05 08:38:03,725 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:03,726 - topic #0 (0.333): 0.013*"’" + 0.011*"good" + 0.009*"needs" + 0.008*"well" + 0.006*"impact" + 0.006*"early" + 0.005*"practice" + 0.005*"need" + 0.005*"experiences" + 0.004*"plans"
-2024-08-05 08:38:03,726 - topic #1 (0.333): 0.011*"’" + 0.010*"good" + 0.007*"well" + 0.006*"needs" + 0.006*"protection" + 0.005*"impact" + 0.005*"plans" + 0.005*"need" + 0.004*"practice" + 0.004*"Harrow"
-2024-08-05 08:38:03,727 - topic #2 (0.333): 0.011*"’" + 0.011*"good" + 0.010*"well" + 0.009*"needs" + 0.007*"plans" + 0.005*"protection" + 0.005*"experiences" + 0.005*"need" + 0.005*"early" + 0.005*"practice"
-2024-08-05 08:38:03,727 - topic diff=0.684806, rho=1.000000
-2024-08-05 08:38:03,727 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=942, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:03.727395', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:05,510 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:05,510 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:05,510 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:05,511 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:05,511 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:05,511 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:05,511 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:05,511 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:05,511 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:05,511 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:05,512 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:05,512 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:07,015 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:07,017 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)
-2024-08-05 08:38:07,017 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-08-05T08:38:07.017817', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:07,018 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:07,019 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:07,019 - using serial LDA version on this node
-2024-08-05 08:38:07,019 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:07,019 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:07,023 - -8.009 per-word bound, 257.5 perplexity estimate based on a held-out corpus of 1 documents with 2243 words
-2024-08-05 08:38:07,023 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:07,024 - topic #0 (0.333): 0.016*"’" + 0.012*"Havering" + 0.008*"plans" + 0.006*"quality" + 0.004*"oversight" + 0.004*"information" + 0.004*"2023" + 0.004*"11" + 0.004*"effective" + 0.004*"many"
-2024-08-05 08:38:07,025 - topic #1 (0.333): 0.018*"’" + 0.011*"Havering" + 0.009*"quality" + 0.006*"oversight" + 0.006*"plans" + 0.005*"effective" + 0.005*"22" + 0.005*"needs" + 0.004*"practice" + 0.004*"protection"
-2024-08-05 08:38:07,025 - topic #2 (0.333): 0.019*"’" + 0.010*"Havering" + 0.009*"quality" + 0.008*"plans" + 0.006*"effective" + 0.005*"needs" + 0.005*"oversight" + 0.005*"11" + 0.004*"December" + 0.004*"practice"
-2024-08-05 08:38:07,025 - topic diff=0.770422, rho=1.000000
-2024-08-05 08:38:07,025 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:07.025498', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:07,995 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:07,995 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:07,996 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:07,996 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:07,996 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:07,996 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:07,996 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:07,996 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:07,997 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:07,997 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:07,997 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:07,997 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:09,885 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:09,887 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)
-2024-08-05 08:38:09,888 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-08-05T08:38:09.888083', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:09,889 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:09,889 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:09,889 - using serial LDA version on this node
-2024-08-05 08:38:09,890 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:09,890 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:09,893 - -8.076 per-word bound, 269.8 perplexity estimate based on a held-out corpus of 1 documents with 2511 words
-2024-08-05 08:38:09,894 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:09,895 - topic #0 (0.333): 0.019*"’" + 0.011*"needs" + 0.007*"well" + 0.007*"plans" + 0.006*"Hillingdon" + 0.004*"need" + 0.004*"6" + 0.004*"2" + 0.004*"timely" + 0.004*"team"
-2024-08-05 08:38:09,895 - topic #1 (0.333): 0.019*"’" + 0.010*"needs" + 0.010*"Hillingdon" + 0.009*"plans" + 0.008*"well" + 0.005*"6" + 0.004*"team" + 0.004*"leaders" + 0.004*"October" + 0.004*"health"
-2024-08-05 08:38:09,895 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"Hillingdon" + 0.007*"plans" + 0.006*"needs" + 0.006*"need" + 0.006*"team" + 0.004*"2" + 0.004*"practice" + 0.004*"family"
-2024-08-05 08:38:09,896 - topic diff=0.790867, rho=1.000000
-2024-08-05 08:38:09,896 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:09.896155', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:11,105 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:11,106 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:11,106 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:11,107 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:11,107 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:11,107 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:11,107 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:11,109 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:11,109 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:11,109 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:11,110 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:11,111 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:12,838 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:12,840 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)
-2024-08-05 08:38:12,840 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-08-05T08:38:12.840628', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:12,841 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:12,841 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:12,842 - using serial LDA version on this node
-2024-08-05 08:38:12,842 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:12,842 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:12,846 - -8.004 per-word bound, 256.7 perplexity estimate based on a held-out corpus of 1 documents with 2271 words
-2024-08-05 08:38:12,846 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:12,847 - topic #0 (0.333): 0.019*"’" + 0.010*"well" + 0.010*"needs" + 0.007*"timely" + 0.007*"Hounslow" + 0.006*"plans" + 0.005*"effective" + 0.005*"training" + 0.005*"strong" + 0.004*"16"
-2024-08-05 08:38:12,847 - topic #1 (0.333): 0.016*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"effective" + 0.006*"Hounslow" + 0.005*"timely" + 0.005*"plans" + 0.005*"16" + 0.004*"education" + 0.004*"oversight"
-2024-08-05 08:38:12,847 - topic #2 (0.333): 0.023*"’" + 0.012*"needs" + 0.010*"well" + 0.009*"effective" + 0.007*"Hounslow" + 0.006*"timely" + 0.005*"plans" + 0.005*"experiences" + 0.005*"progress" + 0.005*"oversight"
-2024-08-05 08:38:12,848 - topic diff=0.781410, rho=1.000000
-2024-08-05 08:38:12,848 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1070, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:12.848146', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:13,899 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:13,899 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:13,899 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:13,899 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:13,900 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:13,900 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:13,900 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:13,900 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:13,900 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:13,900 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:13,900 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:13,901 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:15,487 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:15,489 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)
-2024-08-05 08:38:15,489 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-08-05T08:38:15.489947', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:15,490 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:15,491 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:15,491 - using serial LDA version on this node
-2024-08-05 08:38:15,491 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:15,491 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:15,495 - -7.925 per-word bound, 243.1 perplexity estimate based on a held-out corpus of 1 documents with 1982 words
-2024-08-05 08:38:15,495 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:15,496 - topic #0 (0.333): 0.016*"needs" + 0.014*"’" + 0.013*"well" + 0.007*"plans" + 0.006*"quality" + 0.006*"effective" + 0.006*"highly" + 0.006*"leaders" + 0.005*"good" + 0.005*"risk"
-2024-08-05 08:38:15,496 - topic #1 (0.333): 0.013*"’" + 0.008*"well" + 0.008*"good" + 0.007*"needs" + 0.007*"plans" + 0.007*"highly" + 0.005*"Islington" + 0.005*"quality" + 0.005*"risk" + 0.005*"leaders"
-2024-08-05 08:38:15,496 - topic #2 (0.333): 0.009*"’" + 0.008*"well" + 0.006*"needs" + 0.006*"plans" + 0.005*"good" + 0.005*"practice" + 0.005*"Islington" + 0.005*"quality" + 0.004*"leaders" + 0.004*"highly"
-2024-08-05 08:38:15,497 - topic diff=0.757060, rho=1.000000
-2024-08-05 08:38:15,497 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:15.497144', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:17,386 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:17,386 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:17,386 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:17,387 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:17,387 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:17,387 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:17,387 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:17,387 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:17,387 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:17,388 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:17,388 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:17,388 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:18,734 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:18,736 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)
-2024-08-05 08:38:18,736 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-08-05T08:38:18.736688', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:18,737 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:18,737 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:18,737 - using serial LDA version on this node
-2024-08-05 08:38:18,738 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:18,738 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:18,741 - -7.904 per-word bound, 239.5 perplexity estimate based on a held-out corpus of 1 documents with 2090 words
-2024-08-05 08:38:18,741 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:18,743 - topic #0 (0.333): 0.011*"’" + 0.010*"needs" + 0.007*"plans" + 0.006*"progress" + 0.006*"good" + 0.005*"well" + 0.005*"2022" + 0.005*"Lambeth" + 0.005*"carers" + 0.005*"impact"
-2024-08-05 08:38:18,743 - topic #1 (0.333): 0.017*"’" + 0.010*"well" + 0.009*"needs" + 0.008*"plans" + 0.008*"Lambeth" + 0.006*"good" + 0.006*"need" + 0.005*"leaders" + 0.005*"impact" + 0.005*"4"
-2024-08-05 08:38:18,743 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"good" + 0.006*"plans" + 0.006*"impact" + 0.006*"progress" + 0.006*"need" + 0.005*"Lambeth" + 0.005*"number"
-2024-08-05 08:38:18,743 - topic diff=0.802722, rho=1.000000
-2024-08-05 08:38:18,743 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:18.743824', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:19,685 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:19,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:19,686 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:19,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:19,687 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:19,687 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:19,687 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:19,687 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:19,688 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:19,688 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:19,688 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:19,688 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:21,483 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:21,488 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)
-2024-08-05 08:38:21,488 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-08-05T08:38:21.488329', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:21,490 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:21,490 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:21,490 - using serial LDA version on this node
-2024-08-05 08:38:21,491 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:21,491 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:21,498 - -8.051 per-word bound, 265.3 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
-2024-08-05 08:38:21,498 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:21,501 - topic #0 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"effective" + 0.005*"plans" + 0.005*"Lewisham" + 0.005*"progress" + 0.004*"4" + 0.004*"arrangements" + 0.004*"December"
-2024-08-05 08:38:21,501 - topic #1 (0.333): 0.022*"’" + 0.008*"needs" + 0.008*"well" + 0.008*"plans" + 0.007*"effective" + 0.007*"Lewisham" + 0.006*"good" + 0.005*"2023" + 0.005*"4" + 0.005*"leaders"
-2024-08-05 08:38:21,501 - topic #2 (0.333): 0.013*"’" + 0.009*"well" + 0.006*"plans" + 0.006*"needs" + 0.005*"arrangements" + 0.005*"Lewisham" + 0.005*"progress" + 0.005*"effective" + 0.005*"need" + 0.004*"15"
-2024-08-05 08:38:21,501 - topic diff=0.780814, rho=1.000000
-2024-08-05 08:38:21,502 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:21.502140', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:22,461 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:22,462 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:22,462 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:22,462 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:22,462 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:22,463 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:22,463 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:22,463 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:22,463 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:22,463 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:22,463 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:22,463 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:23,957 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:23,959 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)
-2024-08-05 08:38:23,959 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-08-05T08:38:23.959726', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:23,960 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:23,960 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:23,961 - using serial LDA version on this node
-2024-08-05 08:38:23,961 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:23,961 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:23,965 - -7.990 per-word bound, 254.3 perplexity estimate based on a held-out corpus of 1 documents with 2032 words
-2024-08-05 08:38:23,965 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:23,966 - topic #0 (0.333): 0.020*"’" + 0.007*"well" + 0.007*"Merton" + 0.006*"needs" + 0.005*"plans" + 0.005*"progress" + 0.004*"2022" + 0.004*"family" + 0.004*"across" + 0.004*"good"
-2024-08-05 08:38:23,966 - topic #1 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"Merton" + 0.006*"needs" + 0.005*"plans" + 0.005*"family" + 0.005*"good" + 0.005*"28" + 0.004*"education" + 0.004*"early"
-2024-08-05 08:38:23,967 - topic #2 (0.333): 0.010*"’" + 0.009*"well" + 0.006*"Merton" + 0.005*"needs" + 0.004*"helping" + 0.004*"ensure" + 0.004*"information" + 0.004*"progress" + 0.004*"4" + 0.004*"access"
-2024-08-05 08:38:23,967 - topic diff=0.756035, rho=1.000000
-2024-08-05 08:38:23,967 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1015, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:23.967334', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:24,838 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:24,838 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:24,838 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:24,838 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:24,838 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:24,839 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:24,839 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:24,839 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:24,839 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:24,839 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:24,839 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:24,840 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:26,792 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:26,795 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)
-2024-08-05 08:38:26,795 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-08-05T08:38:26.795373', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:26,796 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:26,796 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:26,796 - using serial LDA version on this node
-2024-08-05 08:38:26,797 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:26,797 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:26,801 - -8.060 per-word bound, 266.9 perplexity estimate based on a held-out corpus of 1 documents with 2540 words
-2024-08-05 08:38:26,801 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:26,802 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"need" + 0.006*"practice" + 0.006*"plans" + 0.006*"progress" + 0.005*"Newham" + 0.005*"effective" + 0.004*"team" + 0.004*"good"
-2024-08-05 08:38:26,802 - topic #1 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"plans" + 0.006*"effective" + 0.006*"progress" + 0.005*"Newham" + 0.005*"practice" + 0.005*"need" + 0.005*"good" + 0.004*"Leaders"
-2024-08-05 08:38:26,803 - topic #2 (0.333): 0.024*"’" + 0.009*"needs" + 0.009*"Newham" + 0.006*"progress" + 0.006*"effective" + 0.006*"practice" + 0.006*"need" + 0.006*"plans" + 0.006*"good" + 0.005*"ensure"
-2024-08-05 08:38:26,803 - topic diff=0.781792, rho=1.000000
-2024-08-05 08:38:26,803 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1153, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:26.803351', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:27,820 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:27,820 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:27,821 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:27,821 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:27,821 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:27,821 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:27,821 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:27,821 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:27,822 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:27,822 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:27,822 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:27,822 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:29,590 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:29,594 - built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)
-2024-08-05 08:38:29,594 - Dictionary lifecycle event {'msg': "built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-08-05T08:38:29.594570', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:29,595 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:29,595 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:29,596 - using serial LDA version on this node
-2024-08-05 08:38:29,596 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:29,596 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:29,600 - -8.170 per-word bound, 287.9 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
-2024-08-05 08:38:29,601 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:29,602 - topic #0 (0.333): 0.013*"’" + 0.006*"Redbridge" + 0.005*"carers" + 0.005*"needs" + 0.005*"practice" + 0.005*"early" + 0.004*"supported" + 0.004*"effective" + 0.004*"leaders" + 0.004*"10"
-2024-08-05 08:38:29,602 - topic #1 (0.333): 0.015*"’" + 0.007*"Redbridge" + 0.005*"needs" + 0.005*"leaders" + 0.005*"practice" + 0.005*"well" + 0.004*"supported" + 0.004*"family" + 0.004*"14" + 0.004*"effective"
-2024-08-05 08:38:29,603 - topic #2 (0.333): 0.015*"’" + 0.008*"Redbridge" + 0.005*"supported" + 0.005*"family" + 0.005*"carers" + 0.005*"needs" + 0.004*"practice" + 0.004*"leaders" + 0.004*"risk" + 0.004*"parents"
-2024-08-05 08:38:29,603 - topic diff=0.751096, rho=1.000000
-2024-08-05 08:38:29,603 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1204, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:29.603268', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:30,512 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:30,512 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:30,513 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:30,513 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:30,513 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:30,513 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:30,513 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:30,513 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:30,514 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:30,514 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:30,514 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:30,514 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:32,026 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:32,028 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)
-2024-08-05 08:38:32,028 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-08-05T08:38:32.028662', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:32,029 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:32,029 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:32,029 - using serial LDA version on this node
-2024-08-05 08:38:32,030 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:32,030 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:32,033 - -7.983 per-word bound, 253.0 perplexity estimate based on a held-out corpus of 1 documents with 1818 words
-2024-08-05 08:38:32,033 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:32,035 - topic #0 (0.333): 0.013*"’" + 0.012*"well" + 0.006*"Richmond" + 0.006*"supported" + 0.005*"needs" + 0.005*"need" + 0.005*"team" + 0.004*"good" + 0.004*"upon" + 0.004*"ensure"
-2024-08-05 08:38:32,035 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.009*"Richmond" + 0.009*"needs" + 0.006*"good" + 0.006*"supported" + 0.006*"need" + 0.005*"team" + 0.005*"4" + 0.005*"strong"
-2024-08-05 08:38:32,035 - topic #2 (0.333): 0.017*"’" + 0.010*"well" + 0.008*"Richmond" + 0.007*"needs" + 0.006*"team" + 0.005*"supported" + 0.005*"need" + 0.005*"additional" + 0.005*"good" + 0.004*"ensure"
-2024-08-05 08:38:32,035 - topic diff=0.732211, rho=1.000000
-2024-08-05 08:38:32,035 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:32.035651', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:32,905 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:32,906 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:32,906 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:32,906 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:32,906 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:32,907 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:32,907 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:32,907 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:32,907 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:32,907 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:32,907 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:32,907 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:34,244 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:34,246 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)
-2024-08-05 08:38:34,246 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-08-05T08:38:34.246963', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:34,247 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:34,247 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:34,248 - using serial LDA version on this node
-2024-08-05 08:38:34,248 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:34,248 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:34,251 - -7.921 per-word bound, 242.3 perplexity estimate based on a held-out corpus of 1 documents with 1878 words
-2024-08-05 08:38:34,252 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:34,253 - topic #0 (0.333): 0.021*"’" + 0.009*"Southwark" + 0.009*"needs" + 0.008*"well" + 0.008*"good" + 0.007*"progress" + 0.007*"effective" + 0.005*"leaders" + 0.005*"need" + 0.005*"Leaders"
-2024-08-05 08:38:34,253 - topic #1 (0.333): 0.016*"’" + 0.009*"Southwark" + 0.008*"good" + 0.007*"well" + 0.007*"needs" + 0.006*"need" + 0.006*"plans" + 0.006*"strong" + 0.005*"progress" + 0.005*"Leaders"
-2024-08-05 08:38:34,253 - topic #2 (0.333): 0.017*"’" + 0.009*"Southwark" + 0.007*"good" + 0.006*"well" + 0.006*"plans" + 0.006*"needs" + 0.005*"receive" + 0.005*"need" + 0.004*"Leaders" + 0.004*"strong"
-2024-08-05 08:38:34,253 - topic diff=0.739336, rho=1.000000
-2024-08-05 08:38:34,253 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=945, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:34.253968', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:35,112 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:35,113 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:35,113 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:35,113 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:35,113 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:35,113 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:35,113 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:35,114 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:35,114 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:35,114 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:35,114 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:35,114 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:36,661 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:36,663 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)
-2024-08-05 08:38:36,663 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-08-05T08:38:36.663869', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:36,664 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:36,664 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:36,665 - using serial LDA version on this node
-2024-08-05 08:38:36,665 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:36,665 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:36,668 - -7.989 per-word bound, 254.1 perplexity estimate based on a held-out corpus of 1 documents with 1847 words
-2024-08-05 08:38:36,669 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:36,670 - topic #0 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"Sutton" + 0.005*"progress" + 0.005*"effective" + 0.004*"good" + 0.004*"6" + 0.004*"leaders" + 0.004*"receive"
-2024-08-05 08:38:36,670 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.005*"good" + 0.005*"needs" + 0.004*"Sutton" + 0.004*"protection" + 0.004*"progress" + 0.004*"receive" + 0.004*"home" + 0.004*"leaders"
-2024-08-05 08:38:36,670 - topic #2 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"Sutton" + 0.006*"needs" + 0.006*"progress" + 0.006*"receive" + 0.005*"effective" + 0.005*"good" + 0.005*"6" + 0.005*"10"
-2024-08-05 08:38:36,670 - topic diff=0.730034, rho=1.000000
-2024-08-05 08:38:36,670 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:36.670962', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:38,402 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:38,402 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:38,403 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:38,403 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:38,403 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:38,403 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:38,403 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:38,404 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:38,404 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:38,404 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:38,404 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:38,404 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:39,934 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:39,938 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)
-2024-08-05 08:38:39,938 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-08-05T08:38:39.938728', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:39,939 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:39,940 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:39,940 - using serial LDA version on this node
-2024-08-05 08:38:39,940 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:39,940 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:39,945 - -8.128 per-word bound, 279.7 perplexity estimate based on a held-out corpus of 1 documents with 2465 words
-2024-08-05 08:38:39,945 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:39,946 - topic #0 (0.333): 0.017*"’" + 0.007*"good" + 0.006*"well" + 0.005*"plans" + 0.005*"need" + 0.005*"‘" + 0.005*"progress" + 0.005*"effective" + 0.004*"risk" + 0.004*"needs"
-2024-08-05 08:38:39,946 - topic #1 (0.333): 0.012*"’" + 0.006*"good" + 0.006*"effective" + 0.005*"practice" + 0.005*"plans" + 0.005*"early" + 0.005*"‘" + 0.005*"need" + 0.004*"well" + 0.004*"needs"
-2024-08-05 08:38:39,947 - topic #2 (0.333): 0.015*"’" + 0.007*"plans" + 0.007*"effective" + 0.006*"‘" + 0.006*"good" + 0.006*"practice" + 0.006*"well" + 0.006*"progress" + 0.005*"need" + 0.005*"early"
-2024-08-05 08:38:39,947 - topic diff=0.774096, rho=1.000000
-2024-08-05 08:38:39,947 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1194, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:39.947354', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:40,972 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:40,972 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:40,973 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:40,973 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:40,973 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:40,973 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:40,973 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:40,973 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:40,974 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:40,974 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:40,974 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:40,974 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:42,425 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:42,427 - built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
-2024-08-05 08:38:42,427 - Dictionary lifecycle event {'msg': "built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-08-05T08:38:42.427848', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:42,428 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:42,429 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:42,429 - using serial LDA version on this node
-2024-08-05 08:38:42,429 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:42,429 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:42,433 - -7.979 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
-2024-08-05 08:38:42,433 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:42,434 - topic #0 (0.333): 0.014*"’" + 0.012*"well" + 0.010*"needs" + 0.009*"effective" + 0.008*"good" + 0.005*"risk" + 0.005*"plans" + 0.005*"timely" + 0.005*"progress" + 0.004*"health"
-2024-08-05 08:38:42,434 - topic #1 (0.333): 0.009*"’" + 0.008*"needs" + 0.007*"need" + 0.007*"well" + 0.005*"effective" + 0.005*"plans" + 0.004*"good" + 0.004*"timely" + 0.004*"information" + 0.004*"protection"
-2024-08-05 08:38:42,435 - topic #2 (0.333): 0.017*"’" + 0.015*"well" + 0.010*"good" + 0.008*"needs" + 0.007*"effective" + 0.007*"need" + 0.006*"plans" + 0.005*"clear" + 0.005*"timely" + 0.004*"receive"
-2024-08-05 08:38:42,435 - topic diff=0.794555, rho=1.000000
-2024-08-05 08:38:42,435 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1036, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:42.435355', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:43,329 - Inspection date 2019-01-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:43,329 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:43,329 - Inspection date 2019-01-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:43,329 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:43,329 - Inspection date 2019-01-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:43,330 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:43,330 - Inspection date 2019-01-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:43,330 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:43,330 - Inspection date 2019-01-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:43,330 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:43,330 - Inspection date 2019-01-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:43,330 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:44,737 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:44,739 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)
-2024-08-05 08:38:44,739 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-08-05T08:38:44.739951', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:44,740 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:44,740 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:44,741 - using serial LDA version on this node
-2024-08-05 08:38:44,741 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:44,741 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:44,744 - -7.848 per-word bound, 230.5 perplexity estimate based on a held-out corpus of 1 documents with 1772 words
-2024-08-05 08:38:44,744 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:44,746 - topic #0 (0.333): 0.009*"’" + 0.007*"well" + 0.005*"Senior" + 0.005*"progress" + 0.005*"However" + 0.005*"needs" + 0.005*"ensure" + 0.005*"18" + 0.005*"effective" + 0.004*"quality"
-2024-08-05 08:38:44,746 - topic #1 (0.333): 0.013*"’" + 0.006*"needs" + 0.006*"practice" + 0.006*"well" + 0.006*"protection" + 0.005*"progress" + 0.005*"receive" + 0.005*"7" + 0.005*"effective" + 0.005*"improve"
-2024-08-05 08:38:44,746 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"Wandsworth" + 0.006*"protection" + 0.005*"progress" + 0.005*"supported" + 0.005*"quality" + 0.005*"Senior" + 0.005*"team" + 0.005*"7"
-2024-08-05 08:38:44,746 - topic diff=0.750695, rho=1.000000
-2024-08-05 08:38:44,746 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=884, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:44.746847', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:45,650 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:45,650 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:45,651 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:45,651 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:45,651 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:45,651 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:45,651 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:45,651 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:45,652 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:45,652 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:45,652 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:45,652 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:47,542 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:47,545 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)
-2024-08-05 08:38:47,545 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-08-05T08:38:47.545599', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:47,546 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:47,546 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:47,547 - using serial LDA version on this node
-2024-08-05 08:38:47,547 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:47,547 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:47,551 - -8.154 per-word bound, 284.8 perplexity estimate based on a held-out corpus of 1 documents with 2101 words
-2024-08-05 08:38:47,551 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:47,552 - topic #0 (0.333): 0.013*"’" + 0.006*"needs" + 0.005*"well" + 0.004*"highly" + 0.004*"practice" + 0.003*"family" + 0.003*"skilled" + 0.003*"high" + 0.003*"direct" + 0.003*"many"
-2024-08-05 08:38:47,553 - topic #1 (0.333): 0.015*"’" + 0.007*"practice" + 0.006*"highly" + 0.006*"needs" + 0.004*"well" + 0.004*"many" + 0.004*"plans" + 0.004*"across" + 0.004*"high" + 0.003*"family"
-2024-08-05 08:38:47,553 - topic #2 (0.333): 0.011*"’" + 0.008*"practice" + 0.006*"highly" + 0.006*"needs" + 0.005*"well" + 0.005*"across" + 0.004*"many" + 0.004*"shared" + 0.004*"experiences" + 0.004*"family"
-2024-08-05 08:38:47,553 - topic diff=0.691115, rho=1.000000
-2024-08-05 08:38:47,553 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1136, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:47.553522', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:48,702 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:48,702 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:48,703 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:48,703 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:48,703 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:48,703 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:48,703 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:48,703 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:48,704 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:48,704 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:48,704 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:48,704 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:50,542 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:50,545 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)
-2024-08-05 08:38:50,545 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-08-05T08:38:50.545327', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:50,546 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:50,546 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:50,546 - using serial LDA version on this node
-2024-08-05 08:38:50,547 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:50,547 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:50,551 - -8.111 per-word bound, 276.4 perplexity estimate based on a held-out corpus of 1 documents with 2593 words
-2024-08-05 08:38:50,551 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:50,552 - topic #0 (0.333): 0.016*"’" + 0.008*"need" + 0.007*"plans" + 0.006*"needs" + 0.006*"impact" + 0.006*"Luton" + 0.005*"well" + 0.005*"effective" + 0.005*"good" + 0.005*"ensure"
-2024-08-05 08:38:50,553 - topic #1 (0.333): 0.016*"’" + 0.006*"plans" + 0.006*"needs" + 0.005*"need" + 0.005*"good" + 0.005*"progress" + 0.005*"effective" + 0.005*"Luton" + 0.004*"ensure" + 0.004*"including"
-2024-08-05 08:38:50,553 - topic #2 (0.333): 0.020*"’" + 0.006*"Luton" + 0.006*"needs" + 0.006*"effective" + 0.006*"progress" + 0.005*"need" + 0.005*"receive" + 0.005*"quality" + 0.005*"good" + 0.005*"Leaders"
-2024-08-05 08:38:50,553 - topic diff=0.789542, rho=1.000000
-2024-08-05 08:38:50,553 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1199, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:50.553656', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:51,684 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:51,684 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:51,685 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:51,685 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:51,685 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:51,685 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:51,686 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:51,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:51,686 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:51,686 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:51,687 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:51,687 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:53,230 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:53,232 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)
-2024-08-05 08:38:53,232 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-08-05T08:38:53.232915', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:53,233 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:53,233 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:53,234 - using serial LDA version on this node
-2024-08-05 08:38:53,234 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:53,234 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:53,237 - -7.775 per-word bound, 219.0 perplexity estimate based on a held-out corpus of 1 documents with 1938 words
-2024-08-05 08:38:53,237 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:53,238 - topic #0 (0.333): 0.020*"’" + 0.012*"Manchester" + 0.009*"needs" + 0.007*"well" + 0.006*"supported" + 0.006*"education" + 0.005*"plans" + 0.005*"protection" + 0.005*"effective" + 0.005*"quality"
-2024-08-05 08:38:53,239 - topic #1 (0.333): 0.022*"’" + 0.009*"needs" + 0.009*"Manchester" + 0.007*"always" + 0.006*"supported" + 0.006*"disabled" + 0.005*"well" + 0.005*"plans" + 0.005*"progress" + 0.005*"education"
-2024-08-05 08:38:53,239 - topic #2 (0.333): 0.021*"’" + 0.010*"Manchester" + 0.009*"needs" + 0.008*"well" + 0.008*"always" + 0.007*"supported" + 0.006*"effective" + 0.005*"protection" + 0.005*"plans" + 0.005*"family"
-2024-08-05 08:38:53,239 - topic diff=0.811500, rho=1.000000
-2024-08-05 08:38:53,239 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=871, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:53.239614', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:54,216 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:54,216 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:54,216 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:54,216 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:54,216 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:54,216 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:54,217 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:54,217 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:54,217 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:54,217 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:54,217 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:54,217 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:55,864 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:55,866 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)
-2024-08-05 08:38:55,867 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-08-05T08:38:55.866994', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:55,867 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:55,868 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:55,868 - using serial LDA version on this node
-2024-08-05 08:38:55,868 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:55,868 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:55,872 - -7.892 per-word bound, 237.5 perplexity estimate based on a held-out corpus of 1 documents with 1857 words
-2024-08-05 08:38:55,872 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:55,873 - topic #0 (0.333): 0.015*"’" + 0.009*"Medway" + 0.008*"well" + 0.008*"quality" + 0.008*"practice" + 0.007*"leaders" + 0.005*"experiences" + 0.005*"impact" + 0.005*"needs" + 0.005*"progress"
-2024-08-05 08:38:55,873 - topic #1 (0.333): 0.019*"’" + 0.009*"Medway" + 0.008*"well" + 0.008*"practice" + 0.007*"needs" + 0.007*"quality" + 0.006*"oversight" + 0.006*"leaders" + 0.005*"28" + 0.005*"impact"
-2024-08-05 08:38:55,873 - topic #2 (0.333): 0.013*"’" + 0.008*"Medway" + 0.008*"quality" + 0.008*"practice" + 0.006*"experiences" + 0.006*"well" + 0.006*"oversight" + 0.006*"leaders" + 0.006*"impact" + 0.006*"needs"
-2024-08-05 08:38:55,873 - topic diff=0.759982, rho=1.000000
-2024-08-05 08:38:55,874 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=922, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:55.874061', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:56,792 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:56,792 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:56,792 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:56,792 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:56,793 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:56,793 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:56,793 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:56,793 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:56,793 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:56,793 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:56,794 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:56,794 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:58,829 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:38:58,831 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)
-2024-08-05 08:38:58,831 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-08-05T08:38:58.831838', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:58,832 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:38:58,833 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:38:58,833 - using serial LDA version on this node
-2024-08-05 08:38:58,833 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:38:58,833 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:38:58,837 - -8.001 per-word bound, 256.2 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
-2024-08-05 08:38:58,837 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:38:58,839 - topic #0 (0.333): 0.011*"’" + 0.007*"plans" + 0.007*"Middlesbrough" + 0.006*"effective" + 0.006*"needs" + 0.005*"progress" + 0.005*"practice" + 0.005*"well" + 0.005*"24" + 0.005*"13"
-2024-08-05 08:38:58,839 - topic #1 (0.333): 0.016*"’" + 0.008*"effective" + 0.007*"well" + 0.007*"plans" + 0.007*"Middlesbrough" + 0.005*"progress" + 0.005*"place" + 0.005*"practice" + 0.005*"needs" + 0.005*"need"
-2024-08-05 08:38:58,839 - topic #2 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"effective" + 0.006*"plans" + 0.006*"well" + 0.006*"Middlesbrough" + 0.006*"practice" + 0.005*"means" + 0.005*"good" + 0.004*"13"
-2024-08-05 08:38:58,839 - topic diff=0.777815, rho=1.000000
-2024-08-05 08:38:58,840 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1068, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:38:58.840097', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:38:59,743 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:38:59,743 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:59,744 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:38:59,744 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:59,744 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:38:59,744 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:59,744 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:38:59,744 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:59,745 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:38:59,745 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:38:59,745 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:38:59,745 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:01,596 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:01,598 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)
-2024-08-05 08:39:01,599 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-08-05T08:39:01.599012', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:01,600 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:01,600 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:01,600 - using serial LDA version on this node
-2024-08-05 08:39:01,600 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:01,600 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:01,604 - -8.034 per-word bound, 262.1 perplexity estimate based on a held-out corpus of 1 documents with 2328 words
-2024-08-05 08:39:01,604 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:01,606 - topic #0 (0.333): 0.015*"’" + 0.007*"Milton" + 0.006*"Keynes" + 0.005*"25" + 0.005*"well" + 0.005*"need" + 0.004*"good" + 0.004*"October" + 0.004*"practice" + 0.004*"impact"
-2024-08-05 08:39:01,606 - topic #1 (0.333): 0.016*"’" + 0.007*"Keynes" + 0.006*"well" + 0.006*"need" + 0.005*"Milton" + 0.005*"25" + 0.005*"5" + 0.005*"plans" + 0.005*"practice" + 0.005*"needs"
-2024-08-05 08:39:01,606 - topic #2 (0.333): 0.013*"’" + 0.006*"Milton" + 0.005*"2021" + 0.005*"leaders" + 0.005*"Keynes" + 0.005*"practice" + 0.005*"well" + 0.005*"need" + 0.004*"plans" + 0.004*"good"
-2024-08-05 08:39:01,606 - topic diff=0.779141, rho=1.000000
-2024-08-05 08:39:01,606 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1101, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:01.606644', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:02,774 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:02,775 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:02,775 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:02,775 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:02,775 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:02,775 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:02,776 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:02,776 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:02,776 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:02,776 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:02,776 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:02,776 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:04,217 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:04,221 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)
-2024-08-05 08:39:04,222 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-08-05T08:39:04.222167', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:04,223 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:04,223 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:04,224 - using serial LDA version on this node
-2024-08-05 08:39:04,224 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:04,224 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:04,230 - -7.881 per-word bound, 235.8 perplexity estimate based on a held-out corpus of 1 documents with 2076 words
-2024-08-05 08:39:04,230 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:04,232 - topic #0 (0.333): 0.017*"’" + 0.013*"plans" + 0.011*"needs" + 0.008*"good" + 0.007*"protection" + 0.007*"well" + 0.007*"Newcastle" + 0.006*"progress" + 0.006*"ensure" + 0.006*"need"
-2024-08-05 08:39:04,232 - topic #1 (0.333): 0.017*"’" + 0.007*"Newcastle" + 0.006*"plans" + 0.006*"protection" + 0.006*"planning" + 0.006*"good" + 0.006*"well" + 0.005*"making" + 0.005*"10" + 0.005*"need"
-2024-08-05 08:39:04,232 - topic #2 (0.333): 0.014*"’" + 0.010*"plans" + 0.007*"Newcastle" + 0.006*"progress" + 0.006*"needs" + 0.006*"protection" + 0.006*"good" + 0.006*"well" + 0.005*"making" + 0.005*"2021"
-2024-08-05 08:39:04,232 - topic diff=0.790392, rho=1.000000
-2024-08-05 08:39:04,233 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=956, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:04.232980', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:05,241 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:05,241 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:05,241 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:05,241 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:05,242 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:05,242 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:05,242 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:05,242 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:05,242 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:05,242 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:05,242 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:05,242 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:07,202 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:07,204 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)
-2024-08-05 08:39:07,205 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-08-05T08:39:07.205103', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:07,206 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:07,206 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:07,206 - using serial LDA version on this node
-2024-08-05 08:39:07,207 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:07,207 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:07,211 - -8.124 per-word bound, 278.9 perplexity estimate based on a held-out corpus of 1 documents with 2655 words
-2024-08-05 08:39:07,211 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:07,212 - topic #0 (0.333): 0.015*"’" + 0.007*"Norfolk" + 0.006*"well" + 0.006*"carers" + 0.005*"supported" + 0.005*"including" + 0.005*"needs" + 0.004*"practice" + 0.004*"plans" + 0.004*"information"
-2024-08-05 08:39:07,212 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"Norfolk" + 0.005*"supported" + 0.005*"practice" + 0.005*"leaders" + 0.005*"effective" + 0.004*"plans" + 0.004*"carers"
-2024-08-05 08:39:07,213 - topic #2 (0.333): 0.018*"’" + 0.010*"well" + 0.009*"Norfolk" + 0.007*"carers" + 0.006*"practice" + 0.006*"needs" + 0.005*"supported" + 0.005*"range" + 0.005*"plans" + 0.005*"18"
-2024-08-05 08:39:07,213 - topic diff=0.782231, rho=1.000000
-2024-08-05 08:39:07,213 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1221, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:07.213335', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:08,142 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:08,142 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:08,142 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:08,143 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:08,143 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:08,143 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:08,143 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:08,143 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:08,144 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:08,144 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:08,144 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:08,145 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:09,896 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:09,898 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)
-2024-08-05 08:39:09,898 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-08-05T08:39:09.898743', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:09,899 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:09,899 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:09,899 - using serial LDA version on this node
-2024-08-05 08:39:09,900 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:09,900 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:09,904 - -7.889 per-word bound, 237.0 perplexity estimate based on a held-out corpus of 1 documents with 2045 words
-2024-08-05 08:39:09,904 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:09,905 - topic #0 (0.333): 0.011*"’" + 0.008*"practice" + 0.007*"risk" + 0.006*"leaders" + 0.006*"need" + 0.006*"needs" + 0.005*"planning" + 0.005*"North" + 0.005*"senior" + 0.005*"Lincolnshire"
-2024-08-05 08:39:09,905 - topic #1 (0.333): 0.012*"’" + 0.007*"practice" + 0.007*"risk" + 0.007*"leaders" + 0.007*"planning" + 0.006*"needs" + 0.005*"many" + 0.005*"quality" + 0.005*"North" + 0.005*"need"
-2024-08-05 08:39:09,906 - topic #2 (0.333): 0.018*"’" + 0.008*"practice" + 0.006*"planning" + 0.006*"risk" + 0.006*"leaders" + 0.006*"needs" + 0.005*"many" + 0.005*"October" + 0.005*"oversight" + 0.005*"2021"
-2024-08-05 08:39:09,906 - topic diff=0.769334, rho=1.000000
-2024-08-05 08:39:09,906 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=958, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:09.906252', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:10,818 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:10,819 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:10,819 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:10,819 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:10,819 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:10,819 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:10,820 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:10,820 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:10,820 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:10,820 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:10,820 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:10,821 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:12,647 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:12,651 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)
-2024-08-05 08:39:12,651 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-08-05T08:39:12.651755', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:12,653 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:12,653 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:12,654 - using serial LDA version on this node
-2024-08-05 08:39:12,654 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:12,654 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:12,660 - -8.062 per-word bound, 267.2 perplexity estimate based on a held-out corpus of 1 documents with 2174 words
-2024-08-05 08:39:12,661 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:12,663 - topic #0 (0.333): 0.014*"’" + 0.008*"‘" + 0.006*"family" + 0.005*"leaders" + 0.005*"North" + 0.005*"approach" + 0.005*"10" + 0.005*"team" + 0.005*"protection" + 0.005*"Lincolnshire"
-2024-08-05 08:39:12,663 - topic #1 (0.333): 0.026*"’" + 0.007*"‘" + 0.007*"Lincolnshire" + 0.006*"family" + 0.006*"North" + 0.006*"well" + 0.006*"approach" + 0.005*"need" + 0.005*"2022" + 0.005*"14"
-2024-08-05 08:39:12,663 - topic #2 (0.333): 0.016*"’" + 0.006*"‘" + 0.005*"leaders" + 0.005*"family" + 0.005*"well" + 0.004*"team" + 0.004*"North" + 0.004*"council" + 0.004*"need" + 0.004*"10"
-2024-08-05 08:39:12,663 - topic diff=0.768471, rho=1.000000
-2024-08-05 08:39:12,664 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:12.663992', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:13,639 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:13,640 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:13,640 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:13,640 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:13,640 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:13,640 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:13,640 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:13,641 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:13,641 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:13,641 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:13,641 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:13,641 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:15,113 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:15,115 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)
-2024-08-05 08:39:15,115 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-08-05T08:39:15.115635', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:15,116 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:15,116 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:15,117 - using serial LDA version on this node
-2024-08-05 08:39:15,117 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:15,117 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:15,121 - -8.031 per-word bound, 261.5 perplexity estimate based on a held-out corpus of 1 documents with 2204 words
-2024-08-05 08:39:15,121 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:15,122 - topic #0 (0.333): 0.012*"’" + 0.009*"Northamptonshire" + 0.008*"North" + 0.006*"well" + 0.005*"need" + 0.005*"impact" + 0.005*"quality" + 0.004*"plans" + 0.004*"Leaders" + 0.004*"NCT"
-2024-08-05 08:39:15,122 - topic #1 (0.333): 0.021*"’" + 0.007*"Northamptonshire" + 0.007*"North" + 0.006*"quality" + 0.006*"well" + 0.006*"needs" + 0.005*"practice" + 0.005*"NCT" + 0.005*"14" + 0.005*"3"
-2024-08-05 08:39:15,122 - topic #2 (0.333): 0.016*"’" + 0.008*"Northamptonshire" + 0.006*"well" + 0.005*"quality" + 0.005*"Leaders" + 0.005*"practice" + 0.005*"North" + 0.005*"e" + 0.005*"impact" + 0.004*"experiences"
-2024-08-05 08:39:15,122 - topic diff=0.752481, rho=1.000000
-2024-08-05 08:39:15,123 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:15.123050', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:16,065 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:16,065 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:16,066 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:16,066 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:16,066 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:16,066 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:16,066 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:16,066 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:16,066 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:16,066 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:16,067 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:16,067 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:17,650 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:17,652 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)
-2024-08-05 08:39:17,653 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-08-05T08:39:17.653143', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:17,654 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:17,654 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:17,654 - using serial LDA version on this node
-2024-08-05 08:39:17,655 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:17,655 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:17,659 - -8.068 per-word bound, 268.3 perplexity estimate based on a held-out corpus of 1 documents with 2902 words
-2024-08-05 08:39:17,659 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:17,660 - topic #0 (0.333): 0.012*"’" + 0.005*"always" + 0.005*"practice" + 0.004*"Somerset" + 0.004*"number" + 0.004*"needs" + 0.004*"progress" + 0.004*"quality" + 0.004*"experienced" + 0.004*"March"
-2024-08-05 08:39:17,660 - topic #1 (0.333): 0.022*"’" + 0.009*"needs" + 0.008*"quality" + 0.007*"Somerset" + 0.006*"North" + 0.006*"always" + 0.005*"need" + 0.005*"practice" + 0.005*"well" + 0.005*"number"
-2024-08-05 08:39:17,661 - topic #2 (0.333): 0.014*"’" + 0.009*"quality" + 0.007*"North" + 0.006*"number" + 0.006*"always" + 0.006*"risk" + 0.006*"practice" + 0.006*"needs" + 0.006*"experienced" + 0.006*"need"
-2024-08-05 08:39:17,661 - topic diff=0.845252, rho=1.000000
-2024-08-05 08:39:17,661 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1219, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:17.661355', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:19,436 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:19,437 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:19,437 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:19,437 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:19,437 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:19,437 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:19,437 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:19,437 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:19,438 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:19,438 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:19,438 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:19,438 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:21,227 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:21,232 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)
-2024-08-05 08:39:21,232 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-08-05T08:39:21.232403', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:21,233 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:21,233 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:21,234 - using serial LDA version on this node
-2024-08-05 08:39:21,234 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:21,234 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:21,238 - -8.226 per-word bound, 299.4 perplexity estimate based on a held-out corpus of 1 documents with 2518 words
-2024-08-05 08:39:21,239 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:21,240 - topic #0 (0.333): 0.015*"’" + 0.005*"well" + 0.005*"make" + 0.005*"leaders" + 0.004*"need" + 0.004*"needs" + 0.004*"protection" + 0.004*"early" + 0.003*"quality" + 0.003*"plans"
-2024-08-05 08:39:21,240 - topic #1 (0.333): 0.019*"’" + 0.008*"well" + 0.006*"need" + 0.006*"leaders" + 0.005*"impact" + 0.005*"make" + 0.005*"quality" + 0.004*"needs" + 0.004*"early" + 0.004*"progress"
-2024-08-05 08:39:21,241 - topic #2 (0.333): 0.011*"’" + 0.005*"well" + 0.005*"leaders" + 0.005*"quality" + 0.004*"need" + 0.004*"needs" + 0.003*"make" + 0.003*"foster" + 0.003*"understand" + 0.003*"experiences"
-2024-08-05 08:39:21,241 - topic diff=0.746695, rho=1.000000
-2024-08-05 08:39:21,241 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1273, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:21.241393', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:22,292 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:22,292 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:22,293 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:22,293 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:22,293 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:22,293 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:22,293 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:22,293 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:22,294 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:22,294 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:22,294 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:22,294 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:24,068 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:24,071 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)
-2024-08-05 08:39:24,071 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-08-05T08:39:24.071646', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:24,072 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:24,072 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:24,073 - using serial LDA version on this node
-2024-08-05 08:39:24,073 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:24,073 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:24,077 - -8.144 per-word bound, 282.9 perplexity estimate based on a held-out corpus of 1 documents with 2759 words
-2024-08-05 08:39:24,077 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:24,079 - topic #0 (0.333): 0.017*"’" + 0.006*"Yorkshire" + 0.006*"well" + 0.005*"North" + 0.005*"needs" + 0.005*"family" + 0.004*"practice" + 0.004*"3" + 0.004*"supported" + 0.004*"‘"
-2024-08-05 08:39:24,079 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"practice" + 0.006*"Yorkshire" + 0.005*"needs" + 0.005*"North" + 0.005*"‘" + 0.005*"family" + 0.004*"need" + 0.004*"July"
-2024-08-05 08:39:24,079 - topic #2 (0.333): 0.025*"’" + 0.010*"well" + 0.007*"North" + 0.007*"practice" + 0.006*"family" + 0.006*"Yorkshire" + 0.006*"needs" + 0.005*"‘" + 0.005*"3" + 0.005*"7"
-2024-08-05 08:39:24,079 - topic diff=0.815357, rho=1.000000
-2024-08-05 08:39:24,080 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1259, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:24.080053', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:25,126 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:25,126 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:25,127 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:25,127 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:25,127 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:25,127 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:25,127 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:25,128 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:25,128 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:25,128 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:25,128 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:25,128 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:26,967 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:26,972 - built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)
-2024-08-05 08:39:26,973 - Dictionary lifecycle event {'msg': "built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)", 'datetime': '2024-08-05T08:39:26.973039', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:26,975 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:26,975 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:26,975 - using serial LDA version on this node
-2024-08-05 08:39:26,976 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:26,976 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:26,983 - -8.073 per-word bound, 269.4 perplexity estimate based on a held-out corpus of 1 documents with 2884 words
-2024-08-05 08:39:26,984 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:26,986 - topic #0 (0.333): 0.014*"’" + 0.009*"family" + 0.008*"strong" + 0.007*"experiences" + 0.007*"leaders" + 0.007*"needs" + 0.006*"well" + 0.006*"Northumberland" + 0.006*"effective" + 0.005*"progress"
-2024-08-05 08:39:26,986 - topic #1 (0.333): 0.026*"’" + 0.007*"leaders" + 0.007*"family" + 0.006*"needs" + 0.006*"experiences" + 0.006*"practice" + 0.005*"strong" + 0.005*"provide" + 0.005*"well" + 0.005*"Northumberland"
-2024-08-05 08:39:26,987 - topic #2 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"family" + 0.005*"well" + 0.005*"experiences" + 0.005*"within" + 0.005*"Northumberland" + 0.004*"leaders" + 0.004*"strong" + 0.004*"receive"
-2024-08-05 08:39:26,987 - topic diff=0.841073, rho=1.000000
-2024-08-05 08:39:26,987 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1218, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:26.987424', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:28,076 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:28,076 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:28,077 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:28,077 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:28,077 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:28,077 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:28,077 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:28,077 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:28,078 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:28,078 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:28,078 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:28,078 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:29,899 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:29,902 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
-2024-08-05 08:39:29,902 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-08-05T08:39:29.902468', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:29,903 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:29,903 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:29,903 - using serial LDA version on this node
-2024-08-05 08:39:29,904 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:29,904 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:29,908 - -8.026 per-word bound, 260.7 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
-2024-08-05 08:39:29,908 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:29,909 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.005*"Nottingham" + 0.005*"impact" + 0.005*"consistently" + 0.004*"plans" + 0.004*"good" + 0.004*"need" + 0.004*"protection" + 0.004*"2022"
-2024-08-05 08:39:29,909 - topic #1 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"effective" + 0.006*"Nottingham" + 0.005*"11" + 0.005*"plans" + 0.005*"practice" + 0.005*"However" + 0.005*"protection" + 0.005*"City"
-2024-08-05 08:39:29,909 - topic #2 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"plans" + 0.006*"effective" + 0.005*"Nottingham" + 0.005*"oversight" + 0.005*"risk" + 0.005*"City" + 0.005*"2022" + 0.005*"impact"
-2024-08-05 08:39:29,910 - topic diff=0.765560, rho=1.000000
-2024-08-05 08:39:29,910 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:29.910154', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:30,841 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:30,841 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:30,842 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:30,842 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:30,842 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:30,842 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:30,842 - Inspection date None / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:30,842 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:30,843 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:30,843 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:30,843 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:30,843 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:32,256 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:32,258 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)
-2024-08-05 08:39:32,258 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)", 'datetime': '2024-08-05T08:39:32.258931', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:32,259 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:32,260 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:32,260 - using serial LDA version on this node
-2024-08-05 08:39:32,260 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:32,260 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:32,264 - -8.008 per-word bound, 257.4 perplexity estimate based on a held-out corpus of 1 documents with 2129 words
-2024-08-05 08:39:32,264 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:32,265 - topic #0 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"Nottinghamshire" + 0.006*"Leaders" + 0.005*"effective" + 0.005*"leaders" + 0.005*"practice" + 0.005*"2024" + 0.005*"20"
-2024-08-05 08:39:32,266 - topic #1 (0.333): 0.015*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"Nottinghamshire" + 0.007*"plans" + 0.005*"effective" + 0.005*"ensure" + 0.004*"risks" + 0.004*"20" + 0.004*"2024"
-2024-08-05 08:39:32,266 - topic #2 (0.333): 0.021*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"plans" + 0.005*"Nottinghamshire" + 0.005*"leaders" + 0.005*"benefit" + 0.004*"24" + 0.004*"May" + 0.004*"Leaders"
-2024-08-05 08:39:32,266 - topic diff=0.759292, rho=1.000000
-2024-08-05 08:39:32,266 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:32.266507', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:33,247 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:33,247 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:33,248 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:33,248 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:33,248 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:33,248 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:33,248 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:33,248 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:33,249 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:33,249 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:33,249 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:33,249 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:34,811 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:34,814 - built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)
-2024-08-05 08:39:34,814 - Dictionary lifecycle event {'msg': "built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)", 'datetime': '2024-08-05T08:39:34.814193', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:34,815 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:34,815 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:34,815 - using serial LDA version on this node
-2024-08-05 08:39:34,816 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:34,816 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:34,820 - -8.078 per-word bound, 270.2 perplexity estimate based on a held-out corpus of 1 documents with 2441 words
-2024-08-05 08:39:34,820 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:34,821 - topic #0 (0.333): 0.009*"’" + 0.008*"plans" + 0.007*"practice" + 0.006*"well" + 0.005*"leaders" + 0.005*"PAs" + 0.005*"needs" + 0.005*"Oldham" + 0.005*"risk" + 0.005*"need"
-2024-08-05 08:39:34,821 - topic #1 (0.333): 0.018*"’" + 0.009*"well" + 0.009*"plans" + 0.007*"needs" + 0.006*"PAs" + 0.006*"Oldham" + 0.006*"leaders" + 0.005*"practice" + 0.005*"effective" + 0.005*"progress"
-2024-08-05 08:39:34,822 - topic #2 (0.333): 0.009*"’" + 0.008*"well" + 0.007*"Oldham" + 0.007*"plans" + 0.006*"needs" + 0.005*"progress" + 0.005*"PAs" + 0.005*"leaders" + 0.004*"May" + 0.004*"practice"
-2024-08-05 08:39:34,822 - topic diff=0.787625, rho=1.000000
-2024-08-05 08:39:34,822 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1152, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:34.822394', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:35,807 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:35,808 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:35,808 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:35,808 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:35,808 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:35,808 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:35,808 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:35,809 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:35,809 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:35,809 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:35,809 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:35,809 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:37,406 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:37,409 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)
-2024-08-05 08:39:37,409 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-08-05T08:39:37.409198', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:37,410 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:37,410 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:37,410 - using serial LDA version on this node
-2024-08-05 08:39:37,410 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:37,411 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:37,414 - -7.989 per-word bound, 254.1 perplexity estimate based on a held-out corpus of 1 documents with 2294 words
-2024-08-05 08:39:37,414 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:37,416 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.006*"Oxfordshire" + 0.006*"receive" + 0.006*"well" + 0.005*"risk" + 0.005*"good" + 0.004*"supported" + 0.004*"practice" + 0.004*"2024"
-2024-08-05 08:39:37,416 - topic #1 (0.333): 0.025*"’" + 0.011*"needs" + 0.008*"Oxfordshire" + 0.008*"well" + 0.007*"risk" + 0.006*"supported" + 0.006*"good" + 0.006*"quality" + 0.005*"12" + 0.005*"progress"
-2024-08-05 08:39:37,416 - topic #2 (0.333): 0.010*"’" + 0.008*"needs" + 0.005*"Oxfordshire" + 0.005*"well" + 0.005*"receive" + 0.004*"supported" + 0.004*"good" + 0.004*"progress" + 0.004*"12" + 0.004*"risk"
-2024-08-05 08:39:37,416 - topic diff=0.801713, rho=1.000000
-2024-08-05 08:39:37,416 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1066, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:37.416683', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:38,379 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:38,380 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:38,380 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:38,380 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:38,380 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:38,380 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:38,381 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:38,381 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:38,381 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:38,381 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:38,381 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:38,381 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:39,824 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:39,826 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)
-2024-08-05 08:39:39,827 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-08-05T08:39:39.827088', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:39,827 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:39,828 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:39,828 - using serial LDA version on this node
-2024-08-05 08:39:39,828 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:39,828 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:39,831 - -7.880 per-word bound, 235.5 perplexity estimate based on a held-out corpus of 1 documents with 1737 words
-2024-08-05 08:39:39,831 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:39,833 - topic #0 (0.333): 0.013*"’" + 0.011*"needs" + 0.007*"8" + 0.006*"2023" + 0.006*"Peterborough" + 0.006*"well" + 0.006*"need" + 0.006*"progress" + 0.005*"supported" + 0.005*"plans"
-2024-08-05 08:39:39,833 - topic #1 (0.333): 0.014*"needs" + 0.012*"’" + 0.008*"Peterborough" + 0.007*"need" + 0.007*"plans" + 0.006*"2023" + 0.006*"supported" + 0.006*"well" + 0.005*"27" + 0.004*"progress"
-2024-08-05 08:39:39,833 - topic #2 (0.333): 0.018*"’" + 0.015*"needs" + 0.008*"need" + 0.007*"progress" + 0.006*"well" + 0.006*"Peterborough" + 0.006*"2023" + 0.006*"good" + 0.005*"receive" + 0.005*"December"
-2024-08-05 08:39:39,833 - topic diff=0.726451, rho=1.000000
-2024-08-05 08:39:39,833 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=893, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:39.833677', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:40,779 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:40,779 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:40,780 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:40,780 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:40,780 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:40,780 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:40,780 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:40,781 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:40,781 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:40,781 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:40,781 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:40,781 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:42,609 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:42,613 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
-2024-08-05 08:39:42,613 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-08-05T08:39:42.613753', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:42,615 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:42,615 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:42,615 - using serial LDA version on this node
-2024-08-05 08:39:42,615 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:42,616 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:42,620 - -8.088 per-word bound, 272.1 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
-2024-08-05 08:39:42,620 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:42,621 - topic #0 (0.333): 0.012*"’" + 0.009*"needs" + 0.007*"well" + 0.006*"Plymouth" + 0.005*"practice" + 0.005*"plans" + 0.004*"understand" + 0.004*"education" + 0.004*"appropriate" + 0.004*"2"
-2024-08-05 08:39:42,622 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.007*"well" + 0.005*"Plymouth" + 0.005*"practice" + 0.005*"February" + 0.005*"Council" + 0.004*"City" + 0.004*"quality" + 0.004*"timely"
-2024-08-05 08:39:42,622 - topic #2 (0.333): 0.014*"’" + 0.008*"Plymouth" + 0.008*"needs" + 0.007*"well" + 0.005*"2" + 0.005*"practice" + 0.005*"22" + 0.005*"appropriate" + 0.005*"plans" + 0.005*"2024"
-2024-08-05 08:39:42,622 - topic diff=0.841926, rho=1.000000
-2024-08-05 08:39:42,622 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1232, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:42.622478', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:43,584 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:43,584 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:43,584 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:43,584 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:43,585 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:43,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:43,585 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:43,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:43,585 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:43,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:43,585 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:43,585 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:45,466 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:45,468 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)
-2024-08-05 08:39:45,469 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-08-05T08:39:45.469048', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:45,470 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:45,470 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:45,470 - using serial LDA version on this node
-2024-08-05 08:39:45,471 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:45,471 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:45,475 - -8.102 per-word bound, 274.8 perplexity estimate based on a held-out corpus of 1 documents with 2738 words
-2024-08-05 08:39:45,475 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:45,476 - topic #0 (0.333): 0.017*"’" + 0.010*"care-experienced" + 0.009*"well" + 0.008*"Portsmouth" + 0.008*"needs" + 0.007*"plans" + 0.006*"family" + 0.005*"health" + 0.005*"leaders" + 0.005*"risk"
-2024-08-05 08:39:45,476 - topic #1 (0.333): 0.017*"’" + 0.007*"care-experienced" + 0.006*"well" + 0.005*"Portsmouth" + 0.005*"needs" + 0.005*"practice" + 0.005*"health" + 0.005*"family" + 0.004*"progress" + 0.004*"need"
-2024-08-05 08:39:45,477 - topic #2 (0.333): 0.017*"’" + 0.006*"needs" + 0.005*"Portsmouth" + 0.005*"care-experienced" + 0.005*"health" + 0.005*"well" + 0.004*"supported" + 0.004*"progress" + 0.004*"plans" + 0.004*"family"
-2024-08-05 08:39:45,477 - topic diff=0.809125, rho=1.000000
-2024-08-05 08:39:45,477 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:45.477441', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:46,422 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:46,422 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:46,423 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:46,423 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:46,423 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:46,423 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:46,423 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:46,424 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:46,424 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:46,424 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:46,424 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:46,424 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:48,100 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:48,102 - built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)
-2024-08-05 08:39:48,103 - Dictionary lifecycle event {'msg': "built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)", 'datetime': '2024-08-05T08:39:48.103130', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:48,104 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:48,104 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:48,104 - using serial LDA version on this node
-2024-08-05 08:39:48,105 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:48,105 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:48,109 - -8.158 per-word bound, 285.6 perplexity estimate based on a held-out corpus of 1 documents with 2562 words
-2024-08-05 08:39:48,109 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:48,110 - topic #0 (0.333): 0.010*"’" + 0.006*"needs" + 0.006*"PAs" + 0.005*"progress" + 0.005*"arrangements" + 0.004*"clear" + 0.004*"plans" + 0.004*"22" + 0.004*"Reading" + 0.004*"well"
-2024-08-05 08:39:48,110 - topic #1 (0.333): 0.016*"’" + 0.007*"needs" + 0.005*"Reading" + 0.005*"PAs" + 0.005*"well" + 0.005*"progress" + 0.004*"plans" + 0.004*"practice" + 0.004*"clear" + 0.004*"timely"
-2024-08-05 08:39:48,111 - topic #2 (0.333): 0.015*"’" + 0.006*"needs" + 0.005*"well" + 0.005*"plans" + 0.005*"PAs" + 0.005*"3" + 0.005*"progress" + 0.004*"Reading" + 0.004*"risk" + 0.004*"May"
-2024-08-05 08:39:48,111 - topic diff=0.759390, rho=1.000000
-2024-08-05 08:39:48,111 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1231, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:48.111375', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:49,046 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:49,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:49,047 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:49,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:49,047 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:49,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:49,047 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:49,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:49,048 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:49,048 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:49,048 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:49,048 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:50,922 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:50,925 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)
-2024-08-05 08:39:50,925 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-08-05T08:39:50.925648', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:50,926 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:50,926 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:50,927 - using serial LDA version on this node
-2024-08-05 08:39:50,927 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:50,927 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:50,931 - -8.007 per-word bound, 257.2 perplexity estimate based on a held-out corpus of 1 documents with 2515 words
-2024-08-05 08:39:50,931 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:50,932 - topic #0 (0.333): 0.018*"’" + 0.006*"needs" + 0.006*"leaders" + 0.006*"However" + 0.006*"2022" + 0.005*"consistently" + 0.005*"plans" + 0.005*"carers" + 0.005*"20" + 0.005*"Cleveland"
-2024-08-05 08:39:50,932 - topic #1 (0.333): 0.014*"’" + 0.005*"plans" + 0.005*"practice" + 0.004*"However" + 0.004*"leaders" + 0.004*"needs" + 0.004*"2022" + 0.004*"risk" + 0.004*"20" + 0.004*"response"
-2024-08-05 08:39:50,933 - topic #2 (0.333): 0.019*"’" + 0.007*"leaders" + 0.007*"consistently" + 0.006*"plans" + 0.006*"However" + 0.006*"needs" + 0.006*"risk" + 0.005*"Redcar" + 0.005*"20" + 0.005*"practice"
-2024-08-05 08:39:50,933 - topic diff=0.807510, rho=1.000000
-2024-08-05 08:39:50,933 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:50.933332', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:51,880 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:51,880 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:51,880 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:51,880 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:51,880 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:51,881 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:51,881 - Inspection date None / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:51,881 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:51,881 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:51,881 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:51,881 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:51,881 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:53,489 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:53,491 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)
-2024-08-05 08:39:53,492 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-08-05T08:39:53.492126', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:53,493 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:53,493 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:53,493 - using serial LDA version on this node
-2024-08-05 08:39:53,494 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:53,494 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:53,497 - -8.022 per-word bound, 259.9 perplexity estimate based on a held-out corpus of 1 documents with 2656 words
-2024-08-05 08:39:53,498 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:53,499 - topic #0 (0.333): 0.020*"’" + 0.010*"needs" + 0.009*"experienced" + 0.007*"practice" + 0.007*"response" + 0.006*"consistently" + 0.006*"good" + 0.006*"plans" + 0.005*"quality" + 0.005*"need"
-2024-08-05 08:39:53,499 - topic #1 (0.333): 0.020*"’" + 0.009*"experienced" + 0.007*"practice" + 0.007*"plans" + 0.006*"needs" + 0.006*"consistently" + 0.006*"response" + 0.005*"progress" + 0.005*"Rochdale" + 0.005*"quality"
-2024-08-05 08:39:53,499 - topic #2 (0.333): 0.021*"’" + 0.010*"experienced" + 0.009*"practice" + 0.006*"needs" + 0.005*"plans" + 0.005*"response" + 0.005*"PAs" + 0.005*"quality" + 0.005*"good" + 0.005*"well"
-2024-08-05 08:39:53,499 - topic diff=0.814871, rho=1.000000
-2024-08-05 08:39:53,499 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1150, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:53.499961', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:54,706 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:54,707 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:54,707 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:54,707 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:54,707 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:54,708 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:54,708 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:54,708 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:54,708 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:54,709 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:54,709 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:54,709 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:56,422 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:56,425 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)
-2024-08-05 08:39:56,425 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-08-05T08:39:56.425566', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:56,426 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:56,426 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:56,427 - using serial LDA version on this node
-2024-08-05 08:39:56,427 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:56,427 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:56,431 - -8.058 per-word bound, 266.5 perplexity estimate based on a held-out corpus of 1 documents with 2366 words
-2024-08-05 08:39:56,431 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:56,432 - topic #0 (0.333): 0.013*"’" + 0.009*"Rotherham" + 0.005*"needs" + 0.005*"However" + 0.005*"Council" + 0.005*"good" + 0.005*"ensure" + 0.005*"protection" + 0.005*"well" + 0.005*"plans"
-2024-08-05 08:39:56,433 - topic #1 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"Rotherham" + 0.005*"well" + 0.005*"good" + 0.004*"ensure" + 0.004*"However" + 0.004*"Borough" + 0.004*"1" + 0.004*"July"
-2024-08-05 08:39:56,433 - topic #2 (0.333): 0.018*"’" + 0.010*"Rotherham" + 0.007*"needs" + 0.005*"well" + 0.005*"ensure" + 0.005*"Council" + 0.005*"good" + 0.005*"plans" + 0.004*"clear" + 0.004*"However"
-2024-08-05 08:39:56,433 - topic diff=0.776004, rho=1.000000
-2024-08-05 08:39:56,433 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1127, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:56.433555', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:57,351 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:39:57,352 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:57,352 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:39:57,352 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:57,352 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:39:57,352 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:57,353 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:39:57,353 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:57,353 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:39:57,353 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:57,353 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:39:57,353 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:39:59,169 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:39:59,171 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)
-2024-08-05 08:39:59,171 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-08-05T08:39:59.171941', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:39:59,173 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:39:59,173 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:39:59,173 - using serial LDA version on this node
-2024-08-05 08:39:59,173 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:39:59,173 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:39:59,177 - -8.050 per-word bound, 265.0 perplexity estimate based on a held-out corpus of 1 documents with 2380 words
-2024-08-05 08:39:59,177 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:39:59,179 - topic #0 (0.333): 0.016*"well" + 0.012*"’" + 0.010*"practice" + 0.008*"strong" + 0.007*"highly" + 0.006*"effective" + 0.006*"needs" + 0.005*"high" + 0.004*"professionals" + 0.004*"progress"
-2024-08-05 08:39:59,179 - topic #1 (0.333): 0.013*"well" + 0.013*"practice" + 0.011*"’" + 0.008*"highly" + 0.007*"strong" + 0.006*"leaders" + 0.005*"needs" + 0.004*"effective" + 0.004*"professionals" + 0.004*"effectively"
-2024-08-05 08:39:59,179 - topic #2 (0.333): 0.012*"’" + 0.009*"well" + 0.008*"practice" + 0.005*"needs" + 0.005*"highly" + 0.005*"effective" + 0.004*"high" + 0.004*"leaders" + 0.004*"range" + 0.004*"improve"
-2024-08-05 08:39:59,179 - topic diff=0.777901, rho=1.000000
-2024-08-05 08:39:59,179 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:39:59.179872', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:00,218 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:00,218 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:00,219 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:00,219 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:00,219 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:00,219 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:00,219 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:00,219 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:00,220 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:00,220 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:00,220 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:00,220 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:01,851 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:01,853 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)
-2024-08-05 08:40:01,853 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-08-05T08:40:01.853965', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:01,854 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:01,855 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:01,855 - using serial LDA version on this node
-2024-08-05 08:40:01,855 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:01,855 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:01,859 - -8.064 per-word bound, 267.7 perplexity estimate based on a held-out corpus of 1 documents with 2257 words
-2024-08-05 08:40:01,859 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:01,860 - topic #0 (0.333): 0.016*"’" + 0.008*"plans" + 0.008*"well" + 0.007*"needs" + 0.005*"practice" + 0.005*"good" + 0.005*"parents" + 0.005*"effective" + 0.005*"clear" + 0.004*"need"
-2024-08-05 08:40:01,861 - topic #1 (0.333): 0.014*"’" + 0.010*"well" + 0.009*"plans" + 0.008*"needs" + 0.006*"good" + 0.005*"effective" + 0.005*"need" + 0.005*"clear" + 0.004*"progress" + 0.004*"range"
-2024-08-05 08:40:01,861 - topic #2 (0.333): 0.009*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"plans" + 0.004*"Kingston" + 0.004*"regularly" + 0.004*"risk" + 0.003*"good" + 0.003*"practice" + 0.003*"parents"
-2024-08-05 08:40:01,861 - topic diff=0.755804, rho=1.000000
-2024-08-05 08:40:01,861 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1107, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:01.861532', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:03,045 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:03,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:03,046 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:03,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:03,046 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:03,046 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:03,046 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:03,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:03,047 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:03,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:03,047 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:03,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:04,539 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:04,543 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)
-2024-08-05 08:40:04,543 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-08-05T08:40:04.543813', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:04,545 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:04,545 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:04,545 - using serial LDA version on this node
-2024-08-05 08:40:04,546 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:04,546 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:04,553 - -8.116 per-word bound, 277.4 perplexity estimate based on a held-out corpus of 1 documents with 2088 words
-2024-08-05 08:40:04,553 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:04,555 - topic #0 (0.333): 0.010*"’" + 0.004*"use" + 0.004*"effective" + 0.004*"needs" + 0.004*"quality" + 0.004*"information" + 0.003*"well" + 0.003*"benefit" + 0.003*"plans" + 0.003*"actions"
-2024-08-05 08:40:04,555 - topic #1 (0.333): 0.012*"’" + 0.005*"quality" + 0.005*"well" + 0.005*"information" + 0.005*"needs" + 0.004*"use" + 0.004*"effective" + 0.004*"plans" + 0.004*"health" + 0.004*"early"
-2024-08-05 08:40:04,555 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"plans" + 0.006*"needs" + 0.005*"quality" + 0.004*"benefit" + 0.004*"health" + 0.004*"always" + 0.004*"need" + 0.004*"case"
-2024-08-05 08:40:04,555 - topic diff=0.714826, rho=1.000000
-2024-08-05 08:40:04,556 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:04.556104', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:06,138 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:06,138 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:06,139 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:06,139 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:06,139 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:06,139 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:06,139 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:06,139 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:06,140 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:06,140 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:06,140 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:06,140 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:07,576 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:07,578 - built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)
-2024-08-05 08:40:07,578 - Dictionary lifecycle event {'msg': "built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)", 'datetime': '2024-08-05T08:40:07.578448', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:07,579 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:07,579 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:07,579 - using serial LDA version on this node
-2024-08-05 08:40:07,580 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:07,580 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:07,583 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2211 words
-2024-08-05 08:40:07,584 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:07,585 - topic #0 (0.333): 0.012*"’" + 0.007*"Rutland" + 0.006*"effective" + 0.006*"needs" + 0.005*"family" + 0.005*"impact" + 0.005*"positive" + 0.005*"need" + 0.005*"well" + 0.005*"good"
-2024-08-05 08:40:07,585 - topic #1 (0.333): 0.018*"’" + 0.009*"needs" + 0.008*"Rutland" + 0.007*"effective" + 0.006*"positive" + 0.006*"impact" + 0.005*"plans" + 0.005*"experiences" + 0.005*"PAs" + 0.005*"ensure"
-2024-08-05 08:40:07,585 - topic #2 (0.333): 0.023*"’" + 0.010*"Rutland" + 0.007*"impact" + 0.007*"needs" + 0.006*"plans" + 0.006*"effective" + 0.006*"need" + 0.006*"positive" + 0.005*"understand" + 0.005*"practice"
-2024-08-05 08:40:07,585 - topic diff=0.770902, rho=1.000000
-2024-08-05 08:40:07,586 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1089, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:07.585994', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:08,624 - Inspection date 2024-04-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:08,624 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:08,624 - Inspection date 2024-04-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:08,624 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:08,625 - Inspection date 2024-04-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:08,625 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:08,625 - Inspection date 2024-04-15 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:08,625 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:08,625 - Inspection date 2024-04-15 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:08,625 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:08,625 - Inspection date 2024-04-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:08,625 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:10,282 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:10,284 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)
-2024-08-05 08:40:10,285 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-08-05T08:40:10.285033', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:10,286 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:10,286 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:10,286 - using serial LDA version on this node
-2024-08-05 08:40:10,286 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:10,286 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:10,290 - -8.011 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2253 words
-2024-08-05 08:40:10,290 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:10,292 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"plans" + 0.006*"effective" + 0.006*"Salford" + 0.005*"needs" + 0.005*"practice" + 0.005*"planning" + 0.005*"6" + 0.004*"10"
-2024-08-05 08:40:10,292 - topic #1 (0.333): 0.010*"’" + 0.007*"well" + 0.007*"plans" + 0.007*"effective" + 0.006*"needs" + 0.005*"10" + 0.005*"practice" + 0.005*"planning" + 0.005*"leaders" + 0.005*"progress"
-2024-08-05 08:40:10,292 - topic #2 (0.333): 0.016*"’" + 0.010*"needs" + 0.009*"plans" + 0.007*"Salford" + 0.006*"effective" + 0.006*"well" + 0.005*"planning" + 0.005*"leaders" + 0.005*"practice" + 0.005*"appropriate"
-2024-08-05 08:40:10,292 - topic diff=0.790981, rho=1.000000
-2024-08-05 08:40:10,292 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:10.292933', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:11,501 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:11,501 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:11,502 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:11,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:11,502 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:11,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:11,502 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:11,502 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:11,503 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:11,503 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:11,503 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:11,503 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:13,809 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:13,813 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)
-2024-08-05 08:40:13,813 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-08-05T08:40:13.813863', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:13,815 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:13,815 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:13,815 - using serial LDA version on this node
-2024-08-05 08:40:13,816 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:13,816 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:13,823 - -7.946 per-word bound, 246.5 perplexity estimate based on a held-out corpus of 1 documents with 2066 words
-2024-08-05 08:40:13,823 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:13,825 - topic #0 (0.333): 0.015*"’" + 0.008*"Sandwell" + 0.008*"plans" + 0.008*"needs" + 0.006*"quality" + 0.006*"well" + 0.005*"education" + 0.005*"Trust" + 0.005*"9" + 0.005*"many"
-2024-08-05 08:40:13,825 - topic #1 (0.333): 0.010*"’" + 0.006*"plans" + 0.006*"well" + 0.006*"Sandwell" + 0.006*"needs" + 0.005*"quality" + 0.004*"changes" + 0.004*"20" + 0.004*"progress" + 0.004*"9"
-2024-08-05 08:40:13,825 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"Sandwell" + 0.007*"well" + 0.006*"plans" + 0.005*"Trust" + 0.005*"quality" + 0.005*"number" + 0.005*"progress" + 0.004*"9"
-2024-08-05 08:40:13,826 - topic diff=0.767843, rho=1.000000
-2024-08-05 08:40:13,826 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=995, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:13.826214', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:15,561 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:15,561 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:15,561 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:15,562 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:15,562 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:15,562 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:15,562 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:15,562 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:15,563 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:15,563 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:15,563 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:15,563 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:18,136 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:18,140 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)
-2024-08-05 08:40:18,141 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-08-05T08:40:18.141100', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:18,142 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:18,143 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:18,143 - using serial LDA version on this node
-2024-08-05 08:40:18,143 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:18,144 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:18,150 - -7.925 per-word bound, 243.0 perplexity estimate based on a held-out corpus of 1 documents with 2300 words
-2024-08-05 08:40:18,150 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:18,152 - topic #0 (0.333): 0.020*"’" + 0.010*"needs" + 0.006*"protection" + 0.006*"practice" + 0.005*"oversight" + 0.005*"many" + 0.005*"March" + 0.005*"management" + 0.005*"including" + 0.005*"always"
-2024-08-05 08:40:18,152 - topic #1 (0.333): 0.014*"’" + 0.010*"needs" + 0.006*"oversight" + 0.005*"practice" + 0.005*"including" + 0.005*"lack" + 0.005*"management" + 0.005*"4" + 0.005*"always" + 0.004*"◼"
-2024-08-05 08:40:18,152 - topic #2 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"practice" + 0.005*"oversight" + 0.005*"◼" + 0.005*"many" + 0.005*"lack" + 0.004*"delays" + 0.004*"timely" + 0.004*"February"
-2024-08-05 08:40:18,152 - topic diff=0.789556, rho=1.000000
-2024-08-05 08:40:18,153 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:18.153171', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:19,889 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:19,890 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:19,890 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:19,890 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:19,891 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:19,891 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:19,891 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:19,891 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:19,891 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:19,892 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:19,892 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:19,892 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:21,974 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:21,977 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)
-2024-08-05 08:40:21,977 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-08-05T08:40:21.977387', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:21,978 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:21,978 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:21,978 - using serial LDA version on this node
-2024-08-05 08:40:21,979 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:21,979 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:21,983 - -8.073 per-word bound, 269.3 perplexity estimate based on a held-out corpus of 1 documents with 2327 words
-2024-08-05 08:40:21,983 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:21,984 - topic #0 (0.333): 0.021*"’" + 0.012*"Sheffield" + 0.008*"needs" + 0.007*"well" + 0.006*"leaders" + 0.006*"health" + 0.005*"plans" + 0.005*"practice" + 0.005*"quality" + 0.004*"receive"
-2024-08-05 08:40:21,984 - topic #1 (0.333): 0.021*"’" + 0.011*"Sheffield" + 0.008*"needs" + 0.006*"practice" + 0.005*"well" + 0.005*"leaders" + 0.005*"good" + 0.005*"adviser" + 0.005*"health" + 0.004*"quality"
-2024-08-05 08:40:21,984 - topic #2 (0.333): 0.020*"’" + 0.010*"Sheffield" + 0.009*"needs" + 0.008*"well" + 0.006*"practice" + 0.005*"leaders" + 0.005*"11" + 0.005*"health" + 0.004*"effective" + 0.004*"ensure"
-2024-08-05 08:40:21,985 - topic diff=0.768209, rho=1.000000
-2024-08-05 08:40:21,985 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:21.985239', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:23,022 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:23,023 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:23,023 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:23,023 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:23,023 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:23,023 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:23,024 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:23,024 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:23,024 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:23,024 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:23,024 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:23,024 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:24,360 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:24,362 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)
-2024-08-05 08:40:24,362 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-08-05T08:40:24.362436', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:24,363 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:24,363 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:24,363 - using serial LDA version on this node
-2024-08-05 08:40:24,363 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:24,364 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:24,367 - -7.957 per-word bound, 248.5 perplexity estimate based on a held-out corpus of 1 documents with 1749 words
-2024-08-05 08:40:24,367 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:24,368 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"Shropshire" + 0.005*"training" + 0.005*"2022" + 0.005*"leaders" + 0.005*"plans" + 0.005*"progress" + 0.005*"11"
-2024-08-05 08:40:24,368 - topic #1 (0.333): 0.019*"’" + 0.011*"needs" + 0.008*"well" + 0.007*"Shropshire" + 0.007*"progress" + 0.006*"2022" + 0.006*"plans" + 0.005*"making" + 0.005*"7" + 0.005*"practice"
-2024-08-05 08:40:24,369 - topic #2 (0.333): 0.016*"’" + 0.007*"Shropshire" + 0.006*"needs" + 0.005*"progress" + 0.005*"plans" + 0.005*"well" + 0.004*"making" + 0.004*"11" + 0.004*"training" + 0.004*"2022"
-2024-08-05 08:40:24,369 - topic diff=0.724473, rho=1.000000
-2024-08-05 08:40:24,369 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=939, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:24.369238', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:25,251 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:25,251 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:25,252 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:25,252 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:25,252 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:25,252 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:25,252 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:25,252 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:25,252 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:25,253 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:25,253 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:25,253 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:27,207 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:27,209 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)
-2024-08-05 08:40:27,210 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-08-05T08:40:27.210034', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:27,211 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:27,211 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:27,211 - using serial LDA version on this node
-2024-08-05 08:40:27,211 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:27,211 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:27,215 - -8.044 per-word bound, 263.9 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
-2024-08-05 08:40:27,215 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:27,217 - topic #0 (0.333): 0.014*"’" + 0.009*"Slough" + 0.007*"needs" + 0.007*"quality" + 0.006*"plans" + 0.005*"3" + 0.005*"supported" + 0.005*"practice" + 0.005*"need" + 0.005*"impact"
-2024-08-05 08:40:27,217 - topic #1 (0.333): 0.017*"’" + 0.007*"Slough" + 0.007*"needs" + 0.006*"plans" + 0.006*"practice" + 0.005*"3" + 0.005*"January" + 0.005*"quality" + 0.004*"2023" + 0.004*"progress"
-2024-08-05 08:40:27,217 - topic #2 (0.333): 0.016*"’" + 0.007*"Slough" + 0.006*"plans" + 0.006*"quality" + 0.006*"practice" + 0.006*"leaders" + 0.005*"impact" + 0.005*"senior" + 0.005*"needs" + 0.005*"However"
-2024-08-05 08:40:27,217 - topic diff=0.781371, rho=1.000000
-2024-08-05 08:40:27,217 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1113, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:27.217924', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:28,199 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:28,199 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:28,199 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:28,199 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:28,199 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:28,200 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:28,200 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:28,200 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:28,200 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:28,200 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:28,200 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:28,201 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:29,922 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:29,925 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)
-2024-08-05 08:40:29,925 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-08-05T08:40:29.925166', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:29,926 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:29,926 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:29,926 - using serial LDA version on this node
-2024-08-05 08:40:29,926 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:29,927 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:29,930 - -7.924 per-word bound, 242.9 perplexity estimate based on a held-out corpus of 1 documents with 2163 words
-2024-08-05 08:40:29,930 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:29,931 - topic #0 (0.333): 0.015*"’" + 0.012*"lack" + 0.008*"2022" + 0.006*"risk" + 0.006*"Solihull" + 0.006*"quality" + 0.005*"means" + 0.005*"significant" + 0.005*"progress" + 0.005*"effective"
-2024-08-05 08:40:29,932 - topic #1 (0.333): 0.012*"’" + 0.010*"lack" + 0.008*"2022" + 0.007*"need" + 0.006*"risk" + 0.006*"Solihull" + 0.006*"practice" + 0.005*"significant" + 0.005*"quality" + 0.005*"effective"
-2024-08-05 08:40:29,932 - topic #2 (0.333): 0.018*"’" + 0.010*"lack" + 0.008*"2022" + 0.007*"need" + 0.007*"practice" + 0.006*"Solihull" + 0.006*"experiences" + 0.006*"quality" + 0.005*"effective" + 0.005*"timely"
-2024-08-05 08:40:29,932 - topic diff=0.793054, rho=1.000000
-2024-08-05 08:40:29,932 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=996, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:29.932496', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:30,885 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:30,886 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:30,886 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:30,886 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:30,886 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:30,886 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:30,887 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:30,887 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:30,887 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:30,887 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:30,887 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:30,887 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:33,544 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:33,546 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)
-2024-08-05 08:40:33,546 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-08-05T08:40:33.546968', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:33,547 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:33,548 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:33,548 - using serial LDA version on this node
-2024-08-05 08:40:33,548 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:33,548 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:33,552 - -7.923 per-word bound, 242.6 perplexity estimate based on a held-out corpus of 1 documents with 2181 words
-2024-08-05 08:40:33,552 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:33,553 - topic #0 (0.333): 0.016*"’" + 0.011*"well" + 0.010*"needs" + 0.006*"Somerset" + 0.006*"plans" + 0.006*"good" + 0.005*"including" + 0.005*"practice" + 0.005*"regularly" + 0.005*"supported"
-2024-08-05 08:40:33,553 - topic #1 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"Somerset" + 0.006*"leaders" + 0.006*"plans" + 0.006*"good" + 0.006*"number" + 0.006*"progress" + 0.005*"need"
-2024-08-05 08:40:33,554 - topic #2 (0.333): 0.017*"’" + 0.006*"needs" + 0.006*"well" + 0.006*"plans" + 0.005*"supported" + 0.005*"good" + 0.005*"need" + 0.005*"Somerset" + 0.005*"practice" + 0.004*"including"
-2024-08-05 08:40:33,554 - topic diff=0.806176, rho=1.000000
-2024-08-05 08:40:33,554 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:33.554459', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:34,433 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:34,433 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:34,433 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:34,433 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:34,434 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:34,434 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:34,434 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:34,434 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:34,434 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:34,434 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:34,435 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:34,435 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:36,144 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:36,147 - built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)
-2024-08-05 08:40:36,147 - Dictionary lifecycle event {'msg': "built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)", 'datetime': '2024-08-05T08:40:36.147674', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:36,148 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:36,148 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:36,149 - using serial LDA version on this node
-2024-08-05 08:40:36,149 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:36,149 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:36,153 - -8.055 per-word bound, 266.0 perplexity estimate based on a held-out corpus of 1 documents with 2751 words
-2024-08-05 08:40:36,153 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:36,155 - topic #0 (0.333): 0.012*"’" + 0.010*"needs" + 0.008*"leaders" + 0.006*"2024" + 0.006*"effective" + 0.006*"strong" + 0.005*"South" + 0.005*"plans" + 0.005*"June" + 0.005*"quality"
-2024-08-05 08:40:36,155 - topic #1 (0.333): 0.019*"’" + 0.010*"needs" + 0.007*"2024" + 0.007*"June" + 0.006*"well" + 0.006*"understand" + 0.005*"leaders" + 0.005*"ensure" + 0.005*"Gloucestershire" + 0.005*"quality"
-2024-08-05 08:40:36,155 - topic #2 (0.333): 0.022*"’" + 0.011*"needs" + 0.007*"June" + 0.007*"leaders" + 0.006*"2024" + 0.006*"ensure" + 0.005*"well" + 0.005*"effective" + 0.005*"progress" + 0.004*"strong"
-2024-08-05 08:40:36,155 - topic diff=0.831914, rho=1.000000
-2024-08-05 08:40:36,155 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1188, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:36.155844', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:37,423 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:37,424 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:37,424 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:37,424 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:37,424 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:37,425 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:37,425 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:37,425 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:37,425 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:37,425 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:37,426 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:37,426 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:39,015 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:39,018 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions)
-2024-08-05 08:40:39,019 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-08-05T08:40:39.019054', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:39,020 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:39,020 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:39,021 - using serial LDA version on this node
-2024-08-05 08:40:39,021 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:39,022 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:39,028 - -7.886 per-word bound, 236.6 perplexity estimate based on a held-out corpus of 1 documents with 2189 words
-2024-08-05 08:40:39,028 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:39,030 - topic #0 (0.333): 0.020*"’" + 0.008*"needs" + 0.008*"South" + 0.007*"Tyneside" + 0.006*"oversight" + 0.006*"14" + 0.005*"effective" + 0.005*"carers" + 0.005*"However" + 0.005*"December"
-2024-08-05 08:40:39,030 - topic #1 (0.333): 0.026*"’" + 0.008*"Tyneside" + 0.008*"needs" + 0.008*"South" + 0.006*"management" + 0.005*"2023" + 0.005*"effective" + 0.005*"9" + 0.004*"2022" + 0.004*"5"
-2024-08-05 08:40:39,031 - topic #2 (0.333): 0.025*"’" + 0.010*"needs" + 0.006*"South" + 0.006*"Tyneside" + 0.006*"15" + 0.006*"carers" + 0.006*"However" + 0.005*"oversight" + 0.005*"practice" + 0.005*"management"
-2024-08-05 08:40:39,031 - topic diff=0.797333, rho=1.000000
-2024-08-05 08:40:39,031 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=981, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:39.031529', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:40,008 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:40,008 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:40,008 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:40,008 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:40,008 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:40,008 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:40,009 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:40,009 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:40,009 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:40,009 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:40,009 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:40,009 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:41,615 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:41,618 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)
-2024-08-05 08:40:41,618 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-08-05T08:40:41.618575', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:41,619 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:41,619 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:41,620 - using serial LDA version on this node
-2024-08-05 08:40:41,620 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:41,620 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:41,624 - -8.149 per-word bound, 283.9 perplexity estimate based on a held-out corpus of 1 documents with 2318 words
-2024-08-05 08:40:41,624 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:41,625 - topic #0 (0.333): 0.017*"’" + 0.007*"plans" + 0.006*"Southampton" + 0.005*"including" + 0.005*"June" + 0.005*"needs" + 0.004*"improve" + 0.004*"experiences" + 0.004*"make" + 0.004*"5"
-2024-08-05 08:40:41,626 - topic #1 (0.333): 0.017*"’" + 0.005*"progress" + 0.005*"well" + 0.005*"5" + 0.004*"Southampton" + 0.004*"improve" + 0.004*"plans" + 0.004*"including" + 0.004*"needs" + 0.004*"timely"
-2024-08-05 08:40:41,626 - topic #2 (0.333): 0.015*"’" + 0.006*"Southampton" + 0.006*"plans" + 0.005*"progress" + 0.005*"improve" + 0.005*"16" + 0.004*"needs" + 0.004*"5" + 0.004*"good" + 0.004*"including"
-2024-08-05 08:40:41,626 - topic diff=0.742406, rho=1.000000
-2024-08-05 08:40:41,626 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1178, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:41.626603', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:42,475 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:42,476 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:42,476 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:42,476 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:42,476 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:42,476 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:42,476 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:42,477 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:42,477 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:42,477 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:42,477 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:42,477 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:44,175 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:44,178 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)
-2024-08-05 08:40:44,179 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-08-05T08:40:44.179067', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:44,180 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:44,180 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:44,181 - using serial LDA version on this node
-2024-08-05 08:40:44,181 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:44,181 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:44,188 - -7.945 per-word bound, 246.4 perplexity estimate based on a held-out corpus of 1 documents with 2086 words
-2024-08-05 08:40:44,188 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:44,190 - topic #0 (0.333): 0.013*"’" + 0.007*"planning" + 0.007*"leaders" + 0.007*"quality" + 0.007*"practice" + 0.006*"protection" + 0.005*"carers" + 0.005*"well" + 0.005*"number" + 0.005*"within"
-2024-08-05 08:40:44,190 - topic #1 (0.333): 0.016*"’" + 0.009*"planning" + 0.008*"practice" + 0.007*"quality" + 0.007*"number" + 0.006*"need" + 0.006*"risk" + 0.005*"leaders" + 0.005*"within" + 0.005*"plans"
-2024-08-05 08:40:44,191 - topic #2 (0.333): 0.010*"’" + 0.007*"planning" + 0.006*"practice" + 0.005*"leaders" + 0.005*"always" + 0.005*"quality" + 0.005*"effective" + 0.005*"protection" + 0.005*"Southend" + 0.005*"needs"
-2024-08-05 08:40:44,191 - topic diff=0.765839, rho=1.000000
-2024-08-05 08:40:44,191 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:44.191488', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:45,904 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:45,904 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:45,904 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:45,904 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:45,905 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:45,905 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:45,905 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:45,905 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:45,905 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:45,905 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:45,905 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:45,906 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:48,277 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:48,280 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)
-2024-08-05 08:40:48,280 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-08-05T08:40:48.280338', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:48,281 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:48,281 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:48,281 - using serial LDA version on this node
-2024-08-05 08:40:48,282 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:48,282 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:48,285 - -8.052 per-word bound, 265.5 perplexity estimate based on a held-out corpus of 1 documents with 2218 words
-2024-08-05 08:40:48,285 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:48,287 - topic #0 (0.333): 0.016*"’" + 0.006*"Helens" + 0.006*"well" + 0.006*"St" + 0.005*"10" + 0.005*"risk" + 0.005*"needs" + 0.005*"receive" + 0.004*"progress" + 0.004*"need"
-2024-08-05 08:40:48,287 - topic #1 (0.333): 0.014*"’" + 0.010*"Helens" + 0.007*"needs" + 0.007*"St" + 0.006*"progress" + 0.005*"well" + 0.005*"21" + 0.005*"need" + 0.005*"receive" + 0.005*"good"
-2024-08-05 08:40:48,287 - topic #2 (0.333): 0.017*"’" + 0.009*"St" + 0.008*"needs" + 0.007*"well" + 0.007*"Helens" + 0.006*"progress" + 0.006*"good" + 0.006*"10" + 0.006*"need" + 0.006*"risk"
-2024-08-05 08:40:48,287 - topic diff=0.778758, rho=1.000000
-2024-08-05 08:40:48,287 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:48.287932', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:49,254 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:49,254 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:49,255 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:49,255 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:49,255 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:49,255 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:49,256 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:49,256 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:49,256 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:49,256 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:49,257 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:49,257 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:50,964 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:50,967 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)
-2024-08-05 08:40:50,967 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-08-05T08:40:50.967323', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:50,968 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:50,968 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:50,968 - using serial LDA version on this node
-2024-08-05 08:40:50,969 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:50,969 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:50,972 - -8.000 per-word bound, 256.0 perplexity estimate based on a held-out corpus of 1 documents with 2334 words
-2024-08-05 08:40:50,973 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:50,974 - topic #0 (0.333): 0.020*"’" + 0.011*"needs" + 0.007*"practice" + 0.006*"health" + 0.006*"Staffordshire" + 0.006*"quality" + 0.006*"progress" + 0.005*"ensure" + 0.005*"oversight" + 0.005*"plans"
-2024-08-05 08:40:50,974 - topic #1 (0.333): 0.018*"’" + 0.012*"needs" + 0.006*"oversight" + 0.006*"progress" + 0.005*"quality" + 0.005*"Staffordshire" + 0.005*"ensure" + 0.005*"health" + 0.004*"risk" + 0.004*"practice"
-2024-08-05 08:40:50,974 - topic #2 (0.333): 0.013*"’" + 0.011*"needs" + 0.006*"quality" + 0.006*"oversight" + 0.006*"ensure" + 0.006*"plans" + 0.006*"progress" + 0.005*"6" + 0.005*"10" + 0.005*"practice"
-2024-08-05 08:40:50,974 - topic diff=0.801994, rho=1.000000
-2024-08-05 08:40:50,975 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:50.975006', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:51,859 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:51,860 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:51,860 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:51,860 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:51,860 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:51,860 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:51,861 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:51,861 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:51,861 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:51,861 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:51,861 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:51,861 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:53,520 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:53,522 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
-2024-08-05 08:40:53,522 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-08-05T08:40:53.522849', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:53,523 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:53,524 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:53,524 - using serial LDA version on this node
-2024-08-05 08:40:53,524 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:53,524 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:53,528 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
-2024-08-05 08:40:53,528 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:53,529 - topic #0 (0.333): 0.008*"’" + 0.006*"practice" + 0.006*"needs" + 0.006*"well" + 0.005*"Stockport" + 0.005*"strong" + 0.005*"ensure" + 0.004*"plans" + 0.004*"risk" + 0.004*"leaders"
-2024-08-05 08:40:53,530 - topic #1 (0.333): 0.010*"’" + 0.008*"well" + 0.007*"Stockport" + 0.007*"practice" + 0.006*"needs" + 0.006*"plans" + 0.006*"risk" + 0.006*"strong" + 0.005*"range" + 0.005*"quality"
-2024-08-05 08:40:53,530 - topic #2 (0.333): 0.014*"’" + 0.010*"well" + 0.008*"practice" + 0.007*"Stockport" + 0.005*"needs" + 0.005*"strong" + 0.005*"28" + 0.005*"plans" + 0.004*"quality" + 0.004*"ensure"
-2024-08-05 08:40:53,530 - topic diff=0.795493, rho=1.000000
-2024-08-05 08:40:53,530 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1060, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:53.530463', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:54,573 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:54,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:54,574 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:54,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:54,574 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:54,574 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:54,574 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:54,575 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:54,575 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:54,575 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:54,575 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:54,575 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:56,050 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:56,053 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)
-2024-08-05 08:40:56,053 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-08-05T08:40:56.053528', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:56,054 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:56,054 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:56,054 - using serial LDA version on this node
-2024-08-05 08:40:56,055 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:56,055 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:56,058 - -7.964 per-word bound, 249.7 perplexity estimate based on a held-out corpus of 1 documents with 2269 words
-2024-08-05 08:40:56,059 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:56,060 - topic #0 (0.333): 0.024*"’" + 0.009*"plans" + 0.009*"leaders" + 0.008*"needs" + 0.007*"well" + 0.006*"quality" + 0.006*"on-Tees" + 0.006*"good" + 0.006*"Stockton" + 0.005*"6"
-2024-08-05 08:40:56,060 - topic #1 (0.333): 0.014*"’" + 0.008*"plans" + 0.008*"leaders" + 0.007*"quality" + 0.006*"Stockton" + 0.006*"well" + 0.006*"senior" + 0.006*"on-Tees" + 0.006*"needs" + 0.006*"good"
-2024-08-05 08:40:56,060 - topic #2 (0.333): 0.018*"’" + 0.008*"leaders" + 0.006*"plans" + 0.005*"on-Tees" + 0.005*"needs" + 0.005*"Stockton" + 0.005*"well" + 0.005*"good" + 0.004*"senior" + 0.004*"carers"
-2024-08-05 08:40:56,060 - topic diff=0.778284, rho=1.000000
-2024-08-05 08:40:56,061 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1044, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:56.061099', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:56,926 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:56,927 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:56,927 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:56,927 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:56,927 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:56,927 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:56,928 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:56,928 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:56,928 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:56,928 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:56,928 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:56,928 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:58,944 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:40:58,948 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)
-2024-08-05 08:40:58,948 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-08-05T08:40:58.948821', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:58,950 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:40:58,950 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:40:58,950 - using serial LDA version on this node
-2024-08-05 08:40:58,951 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:40:58,951 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:40:58,955 - -7.905 per-word bound, 239.7 perplexity estimate based on a held-out corpus of 1 documents with 2165 words
-2024-08-05 08:40:58,955 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:40:58,957 - topic #0 (0.333): 0.022*"’" + 0.007*"needs" + 0.007*"well" + 0.007*"However" + 0.007*"Stoke" + 0.007*"ensure" + 0.006*"on-Trent" + 0.006*"plans" + 0.006*"protection" + 0.005*"quality"
-2024-08-05 08:40:58,957 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"on-Trent" + 0.007*"However" + 0.006*"Stoke" + 0.006*"well" + 0.005*"ensure" + 0.005*"progress" + 0.005*"14"
-2024-08-05 08:40:58,957 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.007*"on-Trent" + 0.007*"well" + 0.007*"Stoke" + 0.006*"timely" + 0.006*"protection" + 0.005*"However" + 0.005*"plans" + 0.005*"practice"
-2024-08-05 08:40:58,958 - topic diff=0.776969, rho=1.000000
-2024-08-05 08:40:58,958 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=986, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:40:58.958219', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:40:59,874 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:40:59,874 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:59,874 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:40:59,875 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:59,875 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:40:59,875 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:59,875 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:40:59,875 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:59,876 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:40:59,876 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:40:59,877 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:40:59,877 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:01,531 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:01,533 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)
-2024-08-05 08:41:01,534 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)", 'datetime': '2024-08-05T08:41:01.534124', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:01,535 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:01,535 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:01,535 - using serial LDA version on this node
-2024-08-05 08:41:01,535 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:01,536 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:01,539 - -8.179 per-word bound, 289.8 perplexity estimate based on a held-out corpus of 1 documents with 2286 words
-2024-08-05 08:41:01,540 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:01,541 - topic #0 (0.333): 0.013*"’" + 0.009*"well" + 0.007*"progress" + 0.006*"effective" + 0.005*"leaders" + 0.005*"ensure" + 0.005*"good" + 0.004*"practice" + 0.004*"experiences" + 0.004*"high"
-2024-08-05 08:41:01,541 - topic #1 (0.333): 0.014*"’" + 0.006*"progress" + 0.005*"well" + 0.005*"good" + 0.004*"leaders" + 0.004*"needs" + 0.004*"ensure" + 0.004*"practice" + 0.003*"carers" + 0.003*"need"
-2024-08-05 08:41:01,541 - topic #2 (0.333): 0.013*"’" + 0.005*"progress" + 0.005*"effective" + 0.004*"leaders" + 0.004*"Suffolk" + 0.004*"good" + 0.004*"practice" + 0.004*"well" + 0.004*"ensure" + 0.004*"needs"
-2024-08-05 08:41:01,541 - topic diff=0.727378, rho=1.000000
-2024-08-05 08:41:01,542 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:01.542032', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:02,497 - Got stderr: Aug 05, 2024 8:41:02 AM org.apache.pdfbox.pdmodel.font.PDTrueTypeFont <init>
+2024-08-12 12:20:17,226 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:20:17,228 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)
+2024-08-12 12:20:17,232 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-08-12T12:20:17.229000', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:17,233 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:20:17,233 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:20:17,233 - using serial LDA version on this node
+2024-08-12 12:20:17,234 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:20:17,234 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:20:17,238 - -8.104 per-word bound, 275.1 perplexity estimate based on a held-out corpus of 1 documents with 2696 words
+2024-08-12 12:20:17,238 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:20:17,239 - topic #0 (0.333): 0.020*"’" + 0.007*"needs" + 0.007*"leaders" + 0.007*"within" + 0.006*"practice" + 0.005*"Barnsley" + 0.005*"plans" + 0.005*"senior" + 0.004*"September" + 0.004*"appropriate"
+2024-08-12 12:20:17,240 - topic #1 (0.333): 0.017*"’" + 0.009*"leaders" + 0.008*"needs" + 0.006*"within" + 0.006*"Barnsley" + 0.006*"practice" + 0.005*"understand" + 0.004*"2023" + 0.004*"response" + 0.004*"quality"
+2024-08-12 12:20:17,240 - topic #2 (0.333): 0.020*"’" + 0.009*"needs" + 0.006*"leaders" + 0.006*"11" + 0.005*"within" + 0.005*"Barnsley" + 0.005*"practice" + 0.005*"senior" + 0.005*"progress" + 0.004*"response"
+2024-08-12 12:20:17,240 - topic diff=0.796286, rho=1.000000
+2024-08-12 12:20:17,240 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1216, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:20:17.240578', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:17,242 - Failed to import jpype dependencies. Fallback to subprocess.
+2024-08-12 12:20:17,243 - No module named 'jpype'
+2024-08-12 12:20:19,903 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:20:19,904 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:19,904 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:20:19,904 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:19,904 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:20:19,904 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:19,904 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:20:19,905 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:19,905 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:20:19,905 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:19,905 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:20:19,905 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:29,723 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:20:29,733 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)
+2024-08-12 12:20:29,734 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-08-12T12:20:29.733998', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:29,735 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:20:29,735 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:20:29,741 - using serial LDA version on this node
+2024-08-12 12:20:29,741 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:20:29,741 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:20:29,747 - -8.023 per-word bound, 260.1 perplexity estimate based on a held-out corpus of 1 documents with 2085 words
+2024-08-12 12:20:29,750 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:20:29,752 - topic #0 (0.333): 0.019*"’" + 0.010*"well" + 0.006*"needs" + 0.005*"plans" + 0.005*"leaders" + 0.005*"practice" + 0.005*"impact" + 0.005*"4" + 0.005*"East" + 0.005*"Somerset"
+2024-08-12 12:20:29,762 - topic #1 (0.333): 0.016*"’" + 0.009*"well" + 0.007*"needs" + 0.005*"leaders" + 0.005*"effective" + 0.005*"plans" + 0.005*"practice" + 0.005*"receive" + 0.005*"North" + 0.004*"‘"
+2024-08-12 12:20:29,763 - topic #2 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"practice" + 0.005*"needs" + 0.005*"plans" + 0.004*"protection" + 0.004*"effective" + 0.004*"28" + 0.004*"clear" + 0.004*"education"
+2024-08-12 12:20:29,763 - topic diff=0.745728, rho=1.000000
+2024-08-12 12:20:29,763 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.02s', 'datetime': '2024-08-12T12:20:29.763602', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:30,834 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:20:30,834 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:30,834 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:20:30,835 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:30,835 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:20:30,835 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:30,835 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:20:30,835 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:30,835 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:20:30,835 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:30,836 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:20:30,836 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:43,957 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:20:43,960 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)
+2024-08-12 12:20:43,960 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-08-12T12:20:43.960452', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:43,961 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:20:43,961 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:20:43,961 - using serial LDA version on this node
+2024-08-12 12:20:43,962 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:20:43,962 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:20:43,966 - -8.109 per-word bound, 276.2 perplexity estimate based on a held-out corpus of 1 documents with 2585 words
+2024-08-12 12:20:43,966 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:20:43,967 - topic #0 (0.333): 0.017*"’" + 0.006*"good" + 0.006*"needs" + 0.006*"ensure" + 0.005*"supported" + 0.005*"Bedford" + 0.005*"well" + 0.004*"progress" + 0.004*"family" + 0.004*"plans"
+2024-08-12 12:20:43,968 - topic #1 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"Bedford" + 0.005*"ensure" + 0.005*"well" + 0.005*"plans" + 0.005*"good" + 0.005*"15" + 0.005*"2021" + 0.004*"education"
+2024-08-12 12:20:43,968 - topic #2 (0.333): 0.022*"’" + 0.007*"ensure" + 0.007*"needs" + 0.007*"well" + 0.006*"plans" + 0.005*"family" + 0.005*"progress" + 0.005*"Borough" + 0.005*"supported" + 0.005*"need"
+2024-08-12 12:20:43,968 - topic diff=0.791616, rho=1.000000
+2024-08-12 12:20:43,968 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1202, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:20:43.968623', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:44,883 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:20:44,883 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:44,883 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:20:44,883 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:44,884 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:20:44,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:44,884 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:20:44,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:44,884 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:20:44,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:44,884 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:20:44,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:57,197 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:20:57,200 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)
+2024-08-12 12:20:57,200 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-08-12T12:20:57.200353', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:57,201 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:20:57,201 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:20:57,201 - using serial LDA version on this node
+2024-08-12 12:20:57,202 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:20:57,202 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:20:57,205 - -7.968 per-word bound, 250.4 perplexity estimate based on a held-out corpus of 1 documents with 2378 words
+2024-08-12 12:20:57,206 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:20:57,207 - topic #0 (0.333): 0.020*"’" + 0.009*"needs" + 0.006*"well" + 0.005*"trust" + 0.005*"Birmingham" + 0.005*"plans" + 0.005*"effective" + 0.004*"appropriate" + 0.004*"leaders" + 0.004*"3"
+2024-08-12 12:20:57,207 - topic #1 (0.333): 0.015*"’" + 0.010*"needs" + 0.008*"effective" + 0.008*"plans" + 0.007*"Birmingham" + 0.006*"progress" + 0.006*"well" + 0.006*"appropriate" + 0.005*"trust" + 0.005*"risk"
+2024-08-12 12:20:57,207 - topic #2 (0.333): 0.010*"’" + 0.009*"needs" + 0.007*"well" + 0.006*"effective" + 0.005*"progress" + 0.005*"trust" + 0.005*"3" + 0.004*"Birmingham" + 0.004*"leaders" + 0.004*"impact"
+2024-08-12 12:20:57,207 - topic diff=0.796210, rho=1.000000
+2024-08-12 12:20:57,208 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1065, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:20:57.208118', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:20:58,212 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:20:58,212 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:58,212 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:20:58,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:58,213 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:20:58,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:58,213 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:20:58,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:58,213 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:20:58,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:20:58,214 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:20:58,214 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:10,490 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:21:10,493 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)
+2024-08-12 12:21:10,493 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-08-12T12:21:10.493210', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:10,494 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:21:10,494 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:21:10,494 - using serial LDA version on this node
+2024-08-12 12:21:10,495 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:21:10,495 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:21:10,498 - -7.960 per-word bound, 249.0 perplexity estimate based on a held-out corpus of 1 documents with 2353 words
+2024-08-12 12:21:10,498 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:21:10,500 - topic #0 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Darwen" + 0.007*"practice" + 0.007*"quality" + 0.007*"impact" + 0.006*"Blackburn" + 0.005*"planning" + 0.005*"need"
+2024-08-12 12:21:10,500 - topic #1 (0.333): 0.015*"’" + 0.008*"Blackburn" + 0.007*"needs" + 0.007*"practice" + 0.007*"quality" + 0.006*"Darwen" + 0.006*"planning" + 0.005*"impact" + 0.005*"plans" + 0.005*"progress"
+2024-08-12 12:21:10,500 - topic #2 (0.333): 0.011*"’" + 0.007*"practice" + 0.006*"needs" + 0.006*"quality" + 0.006*"well" + 0.006*"Darwen" + 0.005*"impact" + 0.005*"February" + 0.005*"receive" + 0.005*"Blackburn"
+2024-08-12 12:21:10,500 - topic diff=0.813941, rho=1.000000
+2024-08-12 12:21:10,500 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1055, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:21:10.500855', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:11,332 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:21:11,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:11,333 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:21:11,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:11,333 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:21:11,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:11,334 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:21:11,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:11,334 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:21:11,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:11,334 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:21:11,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:23,335 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:21:23,337 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)
+2024-08-12 12:21:23,338 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-08-12T12:21:23.338119', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:23,339 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:21:23,339 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:21:23,339 - using serial LDA version on this node
+2024-08-12 12:21:23,340 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:21:23,340 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:21:23,346 - -7.927 per-word bound, 243.4 perplexity estimate based on a held-out corpus of 1 documents with 2392 words
+2024-08-12 12:21:23,346 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:21:23,349 - topic #0 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"Blackpool" + 0.007*"well" + 0.005*"supported" + 0.005*"plans" + 0.004*"experiences" + 0.004*"carers" + 0.004*"good" + 0.004*"including"
+2024-08-12 12:21:23,349 - topic #1 (0.333): 0.013*"’" + 0.012*"needs" + 0.010*"well" + 0.007*"Blackpool" + 0.006*"effective" + 0.005*"plans" + 0.005*"quality" + 0.005*"practice" + 0.005*"supported" + 0.005*"16"
+2024-08-12 12:21:23,349 - topic #2 (0.333): 0.022*"’" + 0.010*"needs" + 0.010*"well" + 0.008*"Blackpool" + 0.007*"effective" + 0.006*"practice" + 0.005*"16" + 0.005*"plans" + 0.005*"understand" + 0.005*"progress"
+2024-08-12 12:21:23,349 - topic diff=0.836721, rho=1.000000
+2024-08-12 12:21:23,350 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1037, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:21:23.350117', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:24,318 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:21:24,318 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:24,319 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:21:24,319 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:24,319 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:21:24,319 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:24,320 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:21:24,320 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:24,320 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:21:24,320 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:24,321 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:21:24,321 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:35,874 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:21:35,876 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)
+2024-08-12 12:21:35,876 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-08-12T12:21:35.876798', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:35,877 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:21:35,878 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:21:35,878 - using serial LDA version on this node
+2024-08-12 12:21:35,878 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:21:35,878 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:21:35,882 - -7.909 per-word bound, 240.4 perplexity estimate based on a held-out corpus of 1 documents with 2055 words
+2024-08-12 12:21:35,882 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:21:35,883 - topic #0 (0.333): 0.016*"’" + 0.009*"Bolton" + 0.008*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"supported" + 0.005*"11" + 0.004*"planning" + 0.004*"need" + 0.004*"carers"
+2024-08-12 12:21:35,883 - topic #1 (0.333): 0.020*"’" + 0.010*"needs" + 0.010*"well" + 0.008*"Bolton" + 0.005*"need" + 0.005*"supported" + 0.005*"plans" + 0.005*"planning" + 0.005*"experiences" + 0.004*"progress"
+2024-08-12 12:21:35,883 - topic #2 (0.333): 0.020*"’" + 0.010*"plans" + 0.010*"needs" + 0.008*"well" + 0.007*"Bolton" + 0.006*"effective" + 0.006*"planning" + 0.005*"strong" + 0.005*"supported" + 0.005*"15"
+2024-08-12 12:21:35,884 - topic diff=0.781906, rho=1.000000
+2024-08-12 12:21:35,884 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:21:35.884268', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:36,791 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:21:36,791 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:36,791 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:21:36,791 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:36,791 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:21:36,791 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:36,792 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:21:36,792 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:36,792 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:21:36,792 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:36,792 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:21:36,792 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:47,064 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:21:47,066 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)
+2024-08-12 12:21:47,066 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-08-12T12:21:47.066783', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:47,067 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:21:47,067 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:21:47,068 - using serial LDA version on this node
+2024-08-12 12:21:47,068 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:21:47,068 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:21:47,072 - -8.029 per-word bound, 261.1 perplexity estimate based on a held-out corpus of 1 documents with 2004 words
+2024-08-12 12:21:47,072 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:21:47,073 - topic #0 (0.333): 0.016*"’" + 0.007*"quality" + 0.005*"risk" + 0.005*"practice" + 0.005*"Christchurch" + 0.005*"progress" + 0.005*"17" + 0.004*"time" + 0.004*"December" + 0.004*"6"
+2024-08-12 12:21:47,073 - topic #1 (0.333): 0.018*"’" + 0.006*"practice" + 0.006*"quality" + 0.006*"progress" + 0.005*"Bournemouth" + 0.005*"Poole" + 0.005*"17" + 0.004*"Christchurch" + 0.004*"impact" + 0.004*"risk"
+2024-08-12 12:21:47,074 - topic #2 (0.333): 0.019*"’" + 0.005*"practice" + 0.005*"impact" + 0.005*"quality" + 0.005*"6" + 0.005*"However" + 0.004*"time" + 0.004*"right" + 0.004*"Poole" + 0.004*"Bournemouth"
+2024-08-12 12:21:47,074 - topic diff=0.745458, rho=1.000000
+2024-08-12 12:21:47,074 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1035, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:21:47.074290', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:49,539 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:21:49,539 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:49,539 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:21:49,539 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:49,539 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:21:49,540 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:49,540 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:21:49,540 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:49,540 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:21:49,540 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:49,540 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:21:49,540 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:21:59,775 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:21:59,777 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)
+2024-08-12 12:21:59,777 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-08-12T12:21:59.777574', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:21:59,778 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:21:59,778 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:21:59,778 - using serial LDA version on this node
+2024-08-12 12:21:59,779 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:21:59,779 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:21:59,782 - -7.851 per-word bound, 230.9 perplexity estimate based on a held-out corpus of 1 documents with 1846 words
+2024-08-12 12:21:59,782 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:21:59,783 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"Forest" + 0.006*"good" + 0.006*"provided" + 0.006*"progress" + 0.005*"need" + 0.005*"impact" + 0.005*"risk" + 0.005*"carers"
+2024-08-12 12:21:59,783 - topic #1 (0.333): 0.019*"’" + 0.008*"Bracknell" + 0.007*"Forest" + 0.007*"needs" + 0.006*"well" + 0.006*"effective" + 0.006*"plans" + 0.006*"risk" + 0.006*"quality" + 0.006*"good"
+2024-08-12 12:21:59,784 - topic #2 (0.333): 0.015*"’" + 0.008*"risk" + 0.007*"quality" + 0.006*"Bracknell" + 0.006*"Forest" + 0.006*"good" + 0.006*"needs" + 0.006*"plans" + 0.005*"effective" + 0.004*"17"
+2024-08-12 12:21:59,784 - topic diff=0.760643, rho=1.000000
+2024-08-12 12:21:59,784 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=900, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:21:59.784287', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:00,750 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:22:00,750 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:00,750 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:22:00,751 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:00,751 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:22:00,751 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:00,751 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:22:00,751 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:00,751 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:22:00,751 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:00,752 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:22:00,752 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:12,283 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:22:12,285 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)
+2024-08-12 12:22:12,285 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)", 'datetime': '2024-08-12T12:22:12.285727', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:12,286 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:22:12,286 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:22:12,287 - using serial LDA version on this node
+2024-08-12 12:22:12,287 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:22:12,287 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:22:12,291 - -8.091 per-word bound, 272.7 perplexity estimate based on a held-out corpus of 1 documents with 2249 words
+2024-08-12 12:22:12,291 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:22:12,293 - topic #0 (0.333): 0.013*"’" + 0.008*"Hove" + 0.007*"Brighton" + 0.006*"practice" + 0.006*"well" + 0.006*"needs" + 0.006*"progress" + 0.006*"relationships" + 0.006*"experiences" + 0.005*"family"
+2024-08-12 12:22:12,293 - topic #1 (0.333): 0.019*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"Brighton" + 0.006*"Hove" + 0.006*"practice" + 0.005*"relationships" + 0.005*"progress" + 0.005*"experiences" + 0.004*"11"
+2024-08-12 12:22:12,293 - topic #2 (0.333): 0.016*"’" + 0.006*"needs" + 0.006*"well" + 0.005*"practice" + 0.005*"Brighton" + 0.005*"Hove" + 0.005*"experiences" + 0.004*"progress" + 0.004*"receive" + 0.004*"family"
+2024-08-12 12:22:12,293 - topic diff=0.742841, rho=1.000000
+2024-08-12 12:22:12,293 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:22:12.293685', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:13,333 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:22:13,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:13,333 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:22:13,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:13,333 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:22:13,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:13,334 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:22:13,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:13,334 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:22:13,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:13,334 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:22:13,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:32,463 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:22:32,467 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)
+2024-08-12 12:22:32,468 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-08-12T12:22:32.467970', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:32,479 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:22:32,479 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:22:32,479 - using serial LDA version on this node
+2024-08-12 12:22:32,480 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:22:32,480 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:22:32,488 - -8.035 per-word bound, 262.3 perplexity estimate based on a held-out corpus of 1 documents with 2647 words
+2024-08-12 12:22:32,488 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:22:32,491 - topic #0 (0.333): 0.023*"’" + 0.008*"well" + 0.007*"good" + 0.007*"needs" + 0.006*"Bristol" + 0.006*"health" + 0.006*"progress" + 0.005*"leaders" + 0.005*"16" + 0.005*"receive"
+2024-08-12 12:22:32,491 - topic #1 (0.333): 0.018*"’" + 0.009*"Bristol" + 0.009*"good" + 0.008*"well" + 0.007*"needs" + 0.005*"health" + 0.005*"plans" + 0.005*"need" + 0.005*"progress" + 0.004*"ensure"
+2024-08-12 12:22:32,491 - topic #2 (0.333): 0.016*"’" + 0.011*"well" + 0.008*"needs" + 0.007*"good" + 0.007*"Bristol" + 0.005*"leaders" + 0.005*"always" + 0.005*"arrangements" + 0.005*"plans" + 0.004*"progress"
+2024-08-12 12:22:32,491 - topic diff=0.818458, rho=1.000000
+2024-08-12 12:22:32,492 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1151, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:22:32.492172', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:34,106 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:22:34,111 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:34,112 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:22:34,112 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:34,112 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:22:34,112 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:34,113 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:22:34,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:34,113 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:22:34,114 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:34,114 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:22:34,114 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:46,873 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:22:46,875 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)
+2024-08-12 12:22:46,876 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-08-12T12:22:46.876117', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:46,877 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:22:46,877 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:22:46,877 - using serial LDA version on this node
+2024-08-12 12:22:46,878 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:22:46,878 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:22:46,882 - -8.239 per-word bound, 302.1 perplexity estimate based on a held-out corpus of 1 documents with 2404 words
+2024-08-12 12:22:46,882 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:22:46,884 - topic #0 (0.333): 0.012*"’" + 0.004*"Buckinghamshire" + 0.004*"number" + 0.004*"17" + 0.004*"6" + 0.003*"plans" + 0.003*"protection" + 0.003*"December" + 0.003*"many" + 0.003*"2021"
+2024-08-12 12:22:46,884 - topic #1 (0.333): 0.014*"’" + 0.006*"number" + 0.005*"plans" + 0.005*"Buckinghamshire" + 0.005*"17" + 0.004*"well" + 0.004*"needs" + 0.004*"practice" + 0.004*"6" + 0.004*"2021"
+2024-08-12 12:22:46,884 - topic #2 (0.333): 0.014*"’" + 0.005*"plans" + 0.005*"many" + 0.005*"protection" + 0.004*"17" + 0.004*"teams" + 0.004*"number" + 0.004*"6" + 0.004*"practice" + 0.004*"2021"
+2024-08-12 12:22:46,884 - topic diff=0.735120, rho=1.000000
+2024-08-12 12:22:46,884 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1263, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:22:46.884784', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:22:47,859 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:22:47,859 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:47,860 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:22:47,860 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:47,860 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:22:47,860 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:47,860 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:22:47,860 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:47,861 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:22:47,861 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:22:47,861 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:22:47,861 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:02,279 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:23:02,281 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)
+2024-08-12 12:23:02,281 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-08-12T12:23:02.281600', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:02,283 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:23:02,283 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:23:02,283 - using serial LDA version on this node
+2024-08-12 12:23:02,284 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:23:02,284 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:23:02,290 - -7.971 per-word bound, 250.9 perplexity estimate based on a held-out corpus of 1 documents with 2427 words
+2024-08-12 12:23:02,291 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:23:02,293 - topic #0 (0.333): 0.008*"’" + 0.006*"2021" + 0.006*"protection" + 0.005*"practice" + 0.005*"team" + 0.005*"need" + 0.005*"Bury" + 0.004*"planning" + 0.004*"needs" + 0.004*"risk"
+2024-08-12 12:23:02,295 - topic #1 (0.333): 0.012*"’" + 0.007*"needs" + 0.005*"practice" + 0.005*"protection" + 0.005*"Bury" + 0.005*"quality" + 0.005*"delay" + 0.005*"impact" + 0.005*"November" + 0.005*"2021"
+2024-08-12 12:23:02,295 - topic #2 (0.333): 0.012*"’" + 0.008*"2021" + 0.008*"protection" + 0.007*"needs" + 0.007*"team" + 0.006*"impact" + 0.006*"practice" + 0.005*"need" + 0.005*"risk" + 0.005*"October"
+2024-08-12 12:23:02,295 - topic diff=0.809584, rho=1.000000
+2024-08-12 12:23:02,296 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:23:02.296040', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:03,206 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:23:03,206 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:03,207 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:23:03,207 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:03,207 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:23:03,207 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:03,207 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:23:03,207 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:03,208 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:23:03,208 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:03,208 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:23:03,208 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:16,120 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:23:16,122 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)
+2024-08-12 12:23:16,123 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-08-12T12:23:16.123149', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:16,124 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:23:16,124 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:23:16,124 - using serial LDA version on this node
+2024-08-12 12:23:16,125 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:23:16,125 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:23:16,129 - -8.032 per-word bound, 261.8 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
+2024-08-12 12:23:16,129 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:23:16,130 - topic #0 (0.333): 0.022*"’" + 0.012*"needs" + 0.008*"Calderdale" + 0.006*"well" + 0.006*"plans" + 0.006*"progress" + 0.006*"ensure" + 0.005*"risk" + 0.005*"parents" + 0.005*"19"
+2024-08-12 12:23:16,130 - topic #1 (0.333): 0.020*"’" + 0.010*"Calderdale" + 0.009*"needs" + 0.005*"ensure" + 0.005*"plans" + 0.005*"well" + 0.005*"progress" + 0.005*"parents" + 0.005*"risk" + 0.005*"information"
+2024-08-12 12:23:16,131 - topic #2 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"Calderdale" + 0.006*"plans" + 0.006*"progress" + 0.005*"ensure" + 0.004*"range" + 0.004*"risk" + 0.004*"leaders"
+2024-08-12 12:23:16,131 - topic diff=0.786196, rho=1.000000
+2024-08-12 12:23:16,131 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:23:16.131415', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:17,112 - Inspection date 2024-02-19 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:23:17,112 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:17,113 - Inspection date 2024-02-19 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:23:17,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:17,113 - Inspection date 2024-02-19 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:23:17,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:17,113 - Inspection date 2024-02-19 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:23:17,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:17,113 - Inspection date 2024-02-19 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:23:17,114 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:17,114 - Inspection date 2024-02-19 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:23:17,114 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:30,548 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:23:30,550 - built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)
+2024-08-12 12:23:30,550 - Dictionary lifecycle event {'msg': "built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)", 'datetime': '2024-08-12T12:23:30.550944', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:30,552 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:23:30,552 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:23:30,552 - using serial LDA version on this node
+2024-08-12 12:23:30,552 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:23:30,552 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:23:30,556 - -8.003 per-word bound, 256.6 perplexity estimate based on a held-out corpus of 1 documents with 2339 words
+2024-08-12 12:23:30,556 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:23:30,558 - topic #0 (0.333): 0.018*"’" + 0.009*"needs" + 0.008*"leaders" + 0.006*"Cambridgeshire" + 0.005*"effective" + 0.005*"well" + 0.005*"good" + 0.005*"practice" + 0.005*"response" + 0.004*"experiences"
+2024-08-12 12:23:30,558 - topic #1 (0.333): 0.019*"’" + 0.006*"needs" + 0.006*"Cambridgeshire" + 0.005*"good" + 0.005*"leaders" + 0.005*"15" + 0.004*"quality" + 0.004*"leadership" + 0.004*"However" + 0.004*"clear"
+2024-08-12 12:23:30,558 - topic #2 (0.333): 0.014*"’" + 0.007*"Cambridgeshire" + 0.006*"good" + 0.006*"leaders" + 0.005*"well" + 0.005*"effective" + 0.005*"4" + 0.005*"needs" + 0.005*"quality" + 0.005*"2024"
+2024-08-12 12:23:30,558 - topic diff=0.786535, rho=1.000000
+2024-08-12 12:23:30,558 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1082, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:23:30.558735', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:31,586 - Inspection date 2024-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:23:31,586 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:31,587 - Inspection date 2024-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:23:31,587 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:31,587 - Inspection date 2024-03-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:23:31,587 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:31,587 - Inspection date 2024-03-04 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:23:31,587 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:31,588 - Inspection date 2024-03-04 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:23:31,588 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:31,588 - Inspection date 2024-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:23:31,588 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:44,468 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:23:44,470 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
+2024-08-12 12:23:44,470 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-08-12T12:23:44.470568', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:44,471 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:23:44,471 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:23:44,471 - using serial LDA version on this node
+2024-08-12 12:23:44,472 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:23:44,472 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:23:44,476 - -7.961 per-word bound, 249.2 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
+2024-08-12 12:23:44,476 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:23:44,477 - topic #0 (0.333): 0.018*"’" + 0.011*"well" + 0.007*"carers" + 0.007*"plans" + 0.007*"need" + 0.007*"needs" + 0.006*"good" + 0.005*"progress" + 0.005*"Bedfordshire" + 0.005*"effective"
+2024-08-12 12:23:44,477 - topic #1 (0.333): 0.016*"’" + 0.008*"needs" + 0.008*"well" + 0.006*"need" + 0.006*"good" + 0.006*"progress" + 0.005*"decisions" + 0.005*"Bedfordshire" + 0.005*"supported" + 0.005*"plans"
+2024-08-12 12:23:44,478 - topic #2 (0.333): 0.013*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"good" + 0.006*"carers" + 0.005*"progress" + 0.005*"need" + 0.005*"plans" + 0.005*"Central" + 0.005*"education"
+2024-08-12 12:23:44,478 - topic diff=0.780576, rho=1.000000
+2024-08-12 12:23:44,478 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1030, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:23:44.478334', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:45,333 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:23:45,333 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:45,333 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:23:45,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:45,334 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:23:45,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:45,334 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:23:45,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:45,334 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:23:45,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:45,335 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:23:45,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:57,561 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:23:57,563 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)
+2024-08-12 12:23:57,563 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-08-12T12:23:57.563320', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:57,564 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:23:57,564 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:23:57,564 - using serial LDA version on this node
+2024-08-12 12:23:57,565 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:23:57,565 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:23:57,568 - -7.978 per-word bound, 252.1 perplexity estimate based on a held-out corpus of 1 documents with 2272 words
+2024-08-12 12:23:57,568 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:23:57,570 - topic #0 (0.333): 0.013*"’" + 0.009*"plans" + 0.008*"needs" + 0.008*"2024" + 0.008*"well" + 0.006*"Cheshire" + 0.006*"leaders" + 0.005*"practice" + 0.005*"need" + 0.005*"quality"
+2024-08-12 12:23:57,570 - topic #1 (0.333): 0.012*"’" + 0.008*"practice" + 0.007*"2024" + 0.007*"East" + 0.006*"effective" + 0.006*"quality" + 0.005*"Cheshire" + 0.005*"well" + 0.005*"plans" + 0.005*"leaders"
+2024-08-12 12:23:57,570 - topic #2 (0.333): 0.012*"’" + 0.008*"needs" + 0.007*"2024" + 0.006*"quality" + 0.006*"practice" + 0.006*"East" + 0.006*"well" + 0.005*"Cheshire" + 0.005*"plans" + 0.005*"protection"
+2024-08-12 12:23:57,570 - topic diff=0.778590, rho=1.000000
+2024-08-12 12:23:57,570 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:23:57.570688', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:23:58,487 - Inspection date 2024-02-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:23:58,487 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:58,488 - Inspection date 2024-02-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:23:58,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:58,488 - Inspection date 2024-02-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:23:58,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:58,488 - Inspection date 2024-02-26 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:23:58,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:58,489 - Inspection date 2024-02-26 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:23:58,489 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:23:58,489 - Inspection date 2024-02-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:23:58,489 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:09,286 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:24:09,289 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)
+2024-08-12 12:24:09,289 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)", 'datetime': '2024-08-12T12:24:09.289243', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:09,290 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:24:09,290 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:24:09,290 - using serial LDA version on this node
+2024-08-12 12:24:09,291 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:24:09,291 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:24:09,294 - -7.999 per-word bound, 255.8 perplexity estimate based on a held-out corpus of 1 documents with 2186 words
+2024-08-12 12:24:09,294 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:24:09,296 - topic #0 (0.333): 0.024*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"effective" + 0.005*"practice" + 0.004*"plans" + 0.004*"receive" + 0.004*"timely" + 0.004*"always" + 0.004*"progress"
+2024-08-12 12:24:09,296 - topic #1 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"needs" + 0.005*"learning" + 0.005*"practice" + 0.004*"information" + 0.004*"impact" + 0.004*"order" + 0.004*"good" + 0.004*"including"
+2024-08-12 12:24:09,296 - topic #2 (0.333): 0.021*"’" + 0.006*"needs" + 0.006*"well" + 0.005*"practice" + 0.005*"always" + 0.004*"effectively" + 0.004*"plans" + 0.004*"impact" + 0.004*"order" + 0.004*"early"
+2024-08-12 12:24:09,296 - topic diff=0.764141, rho=1.000000
+2024-08-12 12:24:09,296 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:24:09.296843', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:10,231 - Inspection date 2019-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:24:10,231 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:10,232 - Inspection date 2019-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:24:10,232 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:10,232 - Inspection date 2019-03-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:24:10,232 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:10,232 - Inspection date 2019-03-18 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:24:10,233 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:10,233 - Inspection date 2019-03-18 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:24:10,233 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:10,233 - Inspection date 2019-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:24:10,233 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:22,391 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:24:22,394 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)
+2024-08-12 12:24:22,394 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-08-12T12:24:22.394295', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:22,395 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:24:22,395 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:24:22,396 - using serial LDA version on this node
+2024-08-12 12:24:22,396 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:24:22,396 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:24:22,403 - -8.050 per-word bound, 265.0 perplexity estimate based on a held-out corpus of 1 documents with 2639 words
+2024-08-12 12:24:22,403 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:24:22,406 - topic #0 (0.333): 0.017*"’" + 0.006*"plans" + 0.005*"needs" + 0.005*"Bradford" + 0.005*"practice" + 0.005*"2" + 0.005*"However" + 0.004*"worker" + 0.004*"risk" + 0.004*"need"
+2024-08-12 12:24:22,406 - topic #1 (0.333): 0.023*"’" + 0.005*"Bradford" + 0.005*"plans" + 0.005*"lack" + 0.005*"needs" + 0.005*"2022" + 0.005*"quality" + 0.005*"risk" + 0.004*"Council" + 0.004*"progress"
+2024-08-12 12:24:22,406 - topic #2 (0.333): 0.022*"’" + 0.009*"plans" + 0.005*"impact" + 0.005*"2" + 0.005*"◼" + 0.005*"Borough" + 0.004*"need" + 0.004*"needs" + 0.004*"many" + 0.004*"November"
+2024-08-12 12:24:22,406 - topic diff=0.806634, rho=1.000000
+2024-08-12 12:24:22,406 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1164, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:24:22.406933', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:23,365 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:24:23,365 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:23,365 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:24:23,366 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:23,366 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:24:23,366 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:23,367 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:24:23,367 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:23,367 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:24:23,367 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:23,368 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:24:23,368 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:33,043 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:24:33,044 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)
+2024-08-12 12:24:33,045 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-08-12T12:24:33.045092', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:33,045 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:24:33,046 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:24:33,046 - using serial LDA version on this node
+2024-08-12 12:24:33,046 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:24:33,046 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:24:33,049 - -7.836 per-word bound, 228.5 perplexity estimate based on a held-out corpus of 1 documents with 1767 words
+2024-08-12 12:24:33,050 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:24:33,051 - topic #0 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"ensure" + 0.006*"effective" + 0.006*"progress" + 0.005*"supported" + 0.005*"good" + 0.004*"clear" + 0.004*"individual"
+2024-08-12 12:24:33,051 - topic #1 (0.333): 0.013*"needs" + 0.012*"’" + 0.011*"well" + 0.009*"ensure" + 0.007*"clear" + 0.007*"effective" + 0.006*"plans" + 0.006*"progress" + 0.006*"within" + 0.005*"good"
+2024-08-12 12:24:33,051 - topic #2 (0.333): 0.011*"needs" + 0.011*"’" + 0.009*"well" + 0.008*"ensure" + 0.006*"good" + 0.006*"clear" + 0.006*"effective" + 0.005*"plans" + 0.005*"individual" + 0.005*"progress"
+2024-08-12 12:24:33,051 - topic diff=0.754347, rho=1.000000
+2024-08-12 12:24:33,051 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=876, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:24:33.051925', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:34,176 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:24:34,177 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:34,177 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:24:34,177 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:34,178 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:24:34,178 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:34,178 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:24:34,178 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:34,179 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:24:34,179 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:34,179 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:24:34,179 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:45,423 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:24:45,425 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)
+2024-08-12 12:24:45,425 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-08-12T12:24:45.425422', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:45,426 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:24:45,426 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:24:45,426 - using serial LDA version on this node
+2024-08-12 12:24:45,427 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:24:45,427 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:24:45,430 - -7.901 per-word bound, 239.0 perplexity estimate based on a held-out corpus of 1 documents with 2281 words
+2024-08-12 12:24:45,430 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:24:45,432 - topic #0 (0.333): 0.021*"’" + 0.009*"Wakefield" + 0.009*"well" + 0.008*"quality" + 0.008*"November" + 0.008*"effective" + 0.007*"leaders" + 0.007*"good" + 0.006*"plans" + 0.006*"progress"
+2024-08-12 12:24:45,432 - topic #1 (0.333): 0.015*"’" + 0.008*"Wakefield" + 0.007*"November" + 0.007*"leaders" + 0.006*"well" + 0.006*"quality" + 0.006*"8" + 0.005*"needs" + 0.005*"practice" + 0.005*"good"
+2024-08-12 12:24:45,432 - topic #2 (0.333): 0.011*"’" + 0.007*"quality" + 0.007*"leaders" + 0.006*"good" + 0.006*"well" + 0.006*"effective" + 0.006*"19" + 0.005*"November" + 0.005*"plans" + 0.005*"needs"
+2024-08-12 12:24:45,432 - topic diff=0.803945, rho=1.000000
+2024-08-12 12:24:45,432 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1007, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:24:45.432816', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:46,334 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:24:46,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:46,334 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:24:46,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:46,335 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:24:46,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:46,335 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:24:46,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:46,335 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:24:46,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:46,335 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:24:46,336 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:56,699 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:24:56,701 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)
+2024-08-12 12:24:56,701 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-08-12T12:24:56.701449', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:56,702 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:24:56,702 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:24:56,702 - using serial LDA version on this node
+2024-08-12 12:24:56,703 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:24:56,703 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:24:56,706 - -7.869 per-word bound, 233.8 perplexity estimate based on a held-out corpus of 1 documents with 1855 words
+2024-08-12 12:24:56,706 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:24:56,707 - topic #0 (0.333): 0.016*"’" + 0.007*"needs" + 0.007*"quality" + 0.006*"However" + 0.006*"March" + 0.006*"effective" + 0.005*"plans" + 0.005*"training" + 0.005*"good" + 0.005*"York"
+2024-08-12 12:24:56,707 - topic #1 (0.333): 0.014*"’" + 0.008*"March" + 0.008*"quality" + 0.007*"needs" + 0.006*"effective" + 0.006*"well" + 0.006*"ensure" + 0.006*"York" + 0.005*"7" + 0.004*"However"
+2024-08-12 12:24:56,707 - topic #2 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"March" + 0.005*"quality" + 0.005*"effective" + 0.005*"appropriate" + 0.005*"York" + 0.005*"ensure" + 0.005*"need" + 0.004*"education"
+2024-08-12 12:24:56,708 - topic diff=0.768257, rho=1.000000
+2024-08-12 12:24:56,708 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=909, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:24:56.708136', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:24:57,786 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:24:57,787 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:57,787 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:24:57,787 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:57,787 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:24:57,787 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:57,788 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:24:57,788 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:57,788 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:24:57,788 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:24:57,788 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:24:57,788 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:11,338 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:25:11,340 - built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)
+2024-08-12 12:25:11,340 - Dictionary lifecycle event {'msg': "built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)", 'datetime': '2024-08-12T12:25:11.340891', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:11,341 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:25:11,341 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:25:11,342 - using serial LDA version on this node
+2024-08-12 12:25:11,342 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:25:11,342 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:25:11,346 - -7.949 per-word bound, 247.0 perplexity estimate based on a held-out corpus of 1 documents with 2157 words
+2024-08-12 12:25:11,346 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:25:11,347 - topic #0 (0.333): 0.017*"well" + 0.012*"’" + 0.010*"quality" + 0.008*"leaders" + 0.008*"effective" + 0.006*"good" + 0.006*"plans" + 0.005*"arrangements" + 0.005*"ensure" + 0.005*"Senior"
+2024-08-12 12:25:11,347 - topic #1 (0.333): 0.015*"well" + 0.011*"’" + 0.009*"leaders" + 0.009*"effective" + 0.008*"quality" + 0.006*"timely" + 0.006*"arrangements" + 0.006*"good" + 0.006*"plans" + 0.006*"high"
+2024-08-12 12:25:11,348 - topic #2 (0.333): 0.013*"’" + 0.011*"well" + 0.010*"quality" + 0.009*"effective" + 0.007*"leaders" + 0.006*"plans" + 0.005*"good" + 0.005*"timely" + 0.005*"highly" + 0.005*"arrangements"
+2024-08-12 12:25:11,348 - topic diff=0.778406, rho=1.000000
+2024-08-12 12:25:11,348 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1014, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:25:11.348274', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:12,432 - Inspection date 2019-10-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:25:12,432 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:12,433 - Inspection date 2019-10-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:25:12,433 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:12,433 - Inspection date 2019-10-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:25:12,433 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:12,433 - Inspection date 2019-10-14 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:25:12,433 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:12,434 - Inspection date 2019-10-14 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:25:12,434 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:12,434 - Inspection date 2019-10-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:25:12,434 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:20,814 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:25:20,817 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)
+2024-08-12 12:25:20,817 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-08-12T12:25:20.817842', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:20,819 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:25:20,819 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:25:20,819 - using serial LDA version on this node
+2024-08-12 12:25:20,820 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:25:20,820 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:25:20,824 - -7.687 per-word bound, 206.0 perplexity estimate based on a held-out corpus of 1 documents with 1521 words
+2024-08-12 12:25:20,825 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:25:20,827 - topic #0 (0.333): 0.018*"’" + 0.011*"Scilly" + 0.008*"Isles" + 0.007*"information" + 0.006*"practice" + 0.006*"need" + 0.005*"quality" + 0.005*"needs" + 0.005*"13" + 0.005*"protection"
+2024-08-12 12:25:20,827 - topic #1 (0.333): 0.025*"’" + 0.012*"Scilly" + 0.011*"Isles" + 0.010*"practice" + 0.010*"need" + 0.006*"protection" + 0.006*"quality" + 0.006*"11" + 0.006*"risks" + 0.005*"information"
+2024-08-12 12:25:20,827 - topic #2 (0.333): 0.019*"’" + 0.015*"Isles" + 0.012*"information" + 0.012*"Scilly" + 0.009*"practice" + 0.008*"needs" + 0.008*"protection" + 0.008*"need" + 0.008*"place" + 0.006*"quality"
+2024-08-12 12:25:20,827 - topic diff=0.762310, rho=1.000000
+2024-08-12 12:25:20,828 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=754, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:25:20.828025', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:21,774 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:25:21,775 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:21,775 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:25:21,775 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:21,775 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:25:21,775 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:21,775 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:25:21,776 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:21,776 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:25:21,776 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:21,776 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:25:21,776 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:33,824 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:25:33,827 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)
+2024-08-12 12:25:33,827 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-08-12T12:25:33.827667', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:33,829 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:25:33,829 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:25:33,829 - using serial LDA version on this node
+2024-08-12 12:25:33,830 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:25:33,830 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:25:33,836 - -7.852 per-word bound, 231.0 perplexity estimate based on a held-out corpus of 1 documents with 2074 words
+2024-08-12 12:25:33,837 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:25:33,839 - topic #0 (0.333): 0.023*"’" + 0.010*"well" + 0.008*"supported" + 0.008*"Coventry" + 0.007*"needs" + 0.006*"family" + 0.006*"strong" + 0.005*"need" + 0.005*"plans" + 0.004*"PAs"
+2024-08-12 12:25:33,839 - topic #1 (0.333): 0.015*"’" + 0.006*"Coventry" + 0.006*"plans" + 0.005*"needs" + 0.005*"supported" + 0.005*"well" + 0.004*"1" + 0.004*"training" + 0.004*"family" + 0.004*"June"
+2024-08-12 12:25:33,839 - topic #2 (0.333): 0.018*"’" + 0.009*"Coventry" + 0.008*"needs" + 0.008*"well" + 0.007*"plans" + 0.007*"family" + 0.006*"supported" + 0.006*"strong" + 0.005*"need" + 0.005*"July"
+2024-08-12 12:25:33,839 - topic diff=0.811482, rho=1.000000
+2024-08-12 12:25:33,840 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=938, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:25:33.840142', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:34,752 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:25:34,752 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:34,753 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:25:34,753 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:34,753 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:25:34,753 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:34,753 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:25:34,754 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:34,754 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:25:34,754 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:34,754 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:25:34,754 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:48,732 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:25:48,735 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)
+2024-08-12 12:25:48,736 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-08-12T12:25:48.736188', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:48,738 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:25:48,738 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:25:48,739 - using serial LDA version on this node
+2024-08-12 12:25:48,739 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:25:48,739 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:25:48,747 - -8.089 per-word bound, 272.4 perplexity estimate based on a held-out corpus of 1 documents with 2653 words
+2024-08-12 12:25:48,748 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:25:48,749 - topic #0 (0.333): 0.021*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"leaders" + 0.006*"Darlington" + 0.005*"practice" + 0.005*"quality" + 0.004*"10" + 0.004*"supported" + 0.004*"family"
+2024-08-12 12:25:48,749 - topic #1 (0.333): 0.019*"’" + 0.009*"well" + 0.009*"October" + 0.008*"leaders" + 0.008*"practice" + 0.007*"needs" + 0.007*"Darlington" + 0.005*"quality" + 0.005*"effective" + 0.005*"education"
+2024-08-12 12:25:48,750 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"supported" + 0.005*"October" + 0.005*"needs" + 0.004*"effective" + 0.004*"appropriate" + 0.004*"leaders" + 0.004*"practice" + 0.004*"protection"
+2024-08-12 12:25:48,750 - topic diff=0.812866, rho=1.000000
+2024-08-12 12:25:48,750 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1195, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:25:48.750252', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:25:49,713 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:25:49,713 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:49,713 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:25:49,714 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:49,714 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:25:49,714 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:49,714 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:25:49,714 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:49,714 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:25:49,715 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:25:49,715 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:25:49,715 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:02,263 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:26:02,265 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)
+2024-08-12 12:26:02,265 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-08-12T12:26:02.265669', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:02,266 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:26:02,266 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:26:02,267 - using serial LDA version on this node
+2024-08-12 12:26:02,267 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:26:02,267 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:26:02,271 - -8.036 per-word bound, 262.6 perplexity estimate based on a held-out corpus of 1 documents with 2396 words
+2024-08-12 12:26:02,271 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:26:02,272 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.005*"plans" + 0.005*"Derby" + 0.005*"quality" + 0.005*"progress" + 0.005*"receive" + 0.004*"leaders" + 0.004*"good" + 0.004*"carers"
+2024-08-12 12:26:02,273 - topic #1 (0.333): 0.021*"’" + 0.011*"needs" + 0.009*"Derby" + 0.008*"quality" + 0.007*"appropriate" + 0.006*"progress" + 0.006*"receive" + 0.006*"plans" + 0.006*"need" + 0.006*"oversight"
+2024-08-12 12:26:02,273 - topic #2 (0.333): 0.025*"’" + 0.008*"needs" + 0.007*"Derby" + 0.007*"receive" + 0.006*"well" + 0.005*"views" + 0.005*"good" + 0.005*"25" + 0.005*"need" + 0.005*"leaders"
+2024-08-12 12:26:02,273 - topic diff=0.781062, rho=1.000000
+2024-08-12 12:26:02,273 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1121, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:26:02.273471', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:03,225 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:26:03,225 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:03,225 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:26:03,225 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:03,226 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:26:03,226 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:03,226 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:26:03,226 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:03,226 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:26:03,226 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:03,227 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:26:03,227 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:13,260 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:26:13,262 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)
+2024-08-12 12:26:13,262 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-08-12T12:26:13.262310', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:13,263 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:26:13,263 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:26:13,263 - using serial LDA version on this node
+2024-08-12 12:26:13,264 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:26:13,264 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:26:13,267 - -8.042 per-word bound, 263.6 perplexity estimate based on a held-out corpus of 1 documents with 2035 words
+2024-08-12 12:26:13,267 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:26:13,269 - topic #0 (0.333): 0.012*"’" + 0.007*"well" + 0.006*"Derbyshire" + 0.005*"plans" + 0.005*"needs" + 0.005*"positive" + 0.005*"education" + 0.004*"effective" + 0.004*"number" + 0.004*"10"
+2024-08-12 12:26:13,269 - topic #1 (0.333): 0.016*"’" + 0.008*"Derbyshire" + 0.007*"well" + 0.005*"leaders" + 0.005*"plans" + 0.005*"needs" + 0.005*"need" + 0.004*"30" + 0.004*"good" + 0.004*"positive"
+2024-08-12 12:26:13,269 - topic #2 (0.333): 0.014*"’" + 0.009*"well" + 0.006*"Derbyshire" + 0.005*"health" + 0.005*"10" + 0.005*"positive" + 0.005*"practice" + 0.005*"effective" + 0.004*"good" + 0.004*"2023"
+2024-08-12 12:26:13,269 - topic diff=0.735931, rho=1.000000
+2024-08-12 12:26:13,269 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:26:13.269739', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:14,258 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:26:14,259 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:14,259 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:26:14,259 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:14,259 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:26:14,259 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:14,260 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:26:14,260 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:14,260 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:26:14,260 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:14,260 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:26:14,260 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:26,056 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:26:26,059 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)
+2024-08-12 12:26:26,059 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-08-12T12:26:26.059895', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:26,061 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:26:26,061 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:26:26,062 - using serial LDA version on this node
+2024-08-12 12:26:26,062 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:26:26,062 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:26:26,069 - -8.149 per-word bound, 283.8 perplexity estimate based on a held-out corpus of 1 documents with 2313 words
+2024-08-12 12:26:26,070 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:26:26,072 - topic #0 (0.333): 0.009*"’" + 0.007*"well" + 0.005*"health" + 0.005*"leaders" + 0.004*"progress" + 0.004*"practice" + 0.004*"risk" + 0.004*"risks" + 0.004*"areas" + 0.004*"quality"
+2024-08-12 12:26:26,072 - topic #1 (0.333): 0.008*"’" + 0.005*"well" + 0.005*"risk" + 0.005*"leaders" + 0.005*"health" + 0.004*"case" + 0.004*"time" + 0.004*"including" + 0.004*"progress" + 0.004*"protection"
+2024-08-12 12:26:26,072 - topic #2 (0.333): 0.010*"’" + 0.005*"progress" + 0.005*"well" + 0.005*"plans" + 0.004*"health" + 0.004*"risk" + 0.004*"Devon" + 0.004*"leaders" + 0.004*"quality" + 0.004*"protection"
+2024-08-12 12:26:26,073 - topic diff=0.729617, rho=1.000000
+2024-08-12 12:26:26,073 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:26:26.073177', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:27,105 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:26:27,105 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:27,106 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:26:27,106 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:27,106 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:26:27,106 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:27,106 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:26:27,107 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:27,107 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:26:27,107 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:27,107 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:26:27,107 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:39,155 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:26:39,157 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)
+2024-08-12 12:26:39,158 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-08-12T12:26:39.158060', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:39,159 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:26:39,159 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:26:39,159 - using serial LDA version on this node
+2024-08-12 12:26:39,159 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:26:39,160 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:26:39,164 - -8.108 per-word bound, 275.8 perplexity estimate based on a held-out corpus of 1 documents with 2429 words
+2024-08-12 12:26:39,164 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:26:39,165 - topic #0 (0.333): 0.021*"’" + 0.007*"well" + 0.005*"records" + 0.005*"Doncaster" + 0.004*"many" + 0.004*"leaders" + 0.004*"quality" + 0.004*"oversight" + 0.004*"arrangements" + 0.004*"progress"
+2024-08-12 12:26:39,165 - topic #1 (0.333): 0.013*"’" + 0.005*"Doncaster" + 0.005*"many" + 0.005*"progress" + 0.005*"plans" + 0.005*"experiences" + 0.005*"well" + 0.005*"effective" + 0.004*"oversight" + 0.004*"records"
+2024-08-12 12:26:39,166 - topic #2 (0.333): 0.024*"’" + 0.007*"Doncaster" + 0.007*"well" + 0.005*"leaders" + 0.005*"progress" + 0.005*"quality" + 0.005*"information" + 0.005*"many" + 0.005*"arrangements" + 0.005*"protection"
+2024-08-12 12:26:39,166 - topic diff=0.770395, rho=1.000000
+2024-08-12 12:26:39,166 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:26:39.166352', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:41,264 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:26:41,265 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:41,265 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:26:41,265 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:41,265 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:26:41,266 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:41,266 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:26:41,266 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:41,266 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:26:41,267 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:41,267 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:26:41,267 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:50,742 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:26:50,744 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)
+2024-08-12 12:26:50,744 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-08-12T12:26:50.744202', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:50,745 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:26:50,745 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:26:50,745 - using serial LDA version on this node
+2024-08-12 12:26:50,745 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:26:50,746 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:26:50,751 - -8.101 per-word bound, 274.5 perplexity estimate based on a held-out corpus of 1 documents with 1942 words
+2024-08-12 12:26:50,751 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:26:50,752 - topic #0 (0.333): 0.015*"’" + 0.006*"Dorset" + 0.004*"well" + 0.004*"arrangements" + 0.004*"need" + 0.004*"8" + 0.004*"protection" + 0.004*"good" + 0.004*"2021" + 0.004*"practice"
+2024-08-12 12:26:50,753 - topic #1 (0.333): 0.014*"’" + 0.009*"Dorset" + 0.008*"good" + 0.007*"well" + 0.005*"needs" + 0.005*"arrangements" + 0.004*"change" + 0.004*"including" + 0.004*"October" + 0.004*"impact"
+2024-08-12 12:26:50,753 - topic #2 (0.333): 0.012*"’" + 0.008*"Dorset" + 0.006*"good" + 0.005*"well" + 0.005*"quality" + 0.005*"8" + 0.004*"needs" + 0.004*"impact" + 0.004*"leaders" + 0.004*"27"
+2024-08-12 12:26:50,753 - topic diff=0.721151, rho=1.000000
+2024-08-12 12:26:50,753 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1067, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:26:50.753500', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:26:51,636 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:26:51,636 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:51,637 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:26:51,637 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:51,637 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:26:51,637 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:51,638 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:26:51,638 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:51,638 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:26:51,638 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:26:51,638 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:26:51,639 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:03,502 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:27:03,504 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)
+2024-08-12 12:27:03,504 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-08-12T12:27:03.504810', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:03,505 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:27:03,505 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:27:03,506 - using serial LDA version on this node
+2024-08-12 12:27:03,506 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:27:03,506 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:27:03,510 - -8.013 per-word bound, 258.4 perplexity estimate based on a held-out corpus of 1 documents with 2138 words
+2024-08-12 12:27:03,510 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:27:03,511 - topic #0 (0.333): 0.015*"’" + 0.010*"needs" + 0.008*"Dudley" + 0.005*"well" + 0.005*"plans" + 0.005*"always" + 0.004*"oversight" + 0.004*"arrangements" + 0.004*"However" + 0.004*"2022"
+2024-08-12 12:27:03,511 - topic #1 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"Dudley" + 0.005*"well" + 0.005*"arrangements" + 0.005*"ensure" + 0.005*"plans" + 0.005*"quality" + 0.004*"11" + 0.004*"experiences"
+2024-08-12 12:27:03,511 - topic #2 (0.333): 0.015*"’" + 0.014*"needs" + 0.009*"Dudley" + 0.006*"always" + 0.006*"arrangements" + 0.005*"well" + 0.005*"oversight" + 0.005*"plans" + 0.005*"quality" + 0.005*"ensure"
+2024-08-12 12:27:03,512 - topic diff=0.759674, rho=1.000000
+2024-08-12 12:27:03,512 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1050, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:27:03.512120', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:04,367 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:27:04,367 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:04,368 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:27:04,368 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:04,368 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:27:04,368 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:04,368 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:27:04,368 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:04,368 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:27:04,369 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:04,369 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:27:04,369 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:16,947 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:27:16,949 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)
+2024-08-12 12:27:16,950 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-08-12T12:27:16.949971', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:16,951 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:27:16,951 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:27:16,951 - using serial LDA version on this node
+2024-08-12 12:27:16,951 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:27:16,951 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:27:16,955 - -7.977 per-word bound, 251.9 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
+2024-08-12 12:27:16,955 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:27:16,956 - topic #0 (0.333): 0.019*"’" + 0.012*"needs" + 0.008*"Durham" + 0.008*"well" + 0.007*"plans" + 0.007*"May" + 0.006*"ensure" + 0.005*"supported" + 0.005*"practice" + 0.005*"leaders"
+2024-08-12 12:27:16,956 - topic #1 (0.333): 0.010*"’" + 0.009*"needs" + 0.007*"Durham" + 0.006*"plans" + 0.006*"well" + 0.006*"May" + 0.005*"ensure" + 0.005*"risks" + 0.005*"practice" + 0.004*"number"
+2024-08-12 12:27:16,957 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"May" + 0.006*"well" + 0.006*"Durham" + 0.006*"practice" + 0.005*"plans" + 0.005*"leaders" + 0.005*"ensure" + 0.004*"progress"
+2024-08-12 12:27:16,957 - topic diff=0.778081, rho=1.000000
+2024-08-12 12:27:16,957 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:27:16.957269', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:17,936 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:27:17,936 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:17,936 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:27:17,936 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:17,937 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:27:17,937 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:17,937 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:27:17,937 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:17,937 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:27:17,937 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:17,937 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:27:17,938 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:28,989 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:27:28,991 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)
+2024-08-12 12:27:28,991 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-08-12T12:27:28.991721', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:28,992 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:27:28,992 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:27:28,993 - using serial LDA version on this node
+2024-08-12 12:27:28,993 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:27:28,993 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:27:28,996 - -7.921 per-word bound, 242.4 perplexity estimate based on a held-out corpus of 1 documents with 2014 words
+2024-08-12 12:27:28,996 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:27:28,998 - topic #0 (0.333): 0.018*"’" + 0.011*"needs" + 0.009*"well" + 0.009*"plans" + 0.008*"progress" + 0.006*"Riding" + 0.006*"East" + 0.005*"education" + 0.005*"good" + 0.005*"partners"
+2024-08-12 12:27:28,998 - topic #1 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"East" + 0.007*"well" + 0.007*"Riding" + 0.006*"progress" + 0.005*"January" + 0.005*"partners" + 0.005*"30"
+2024-08-12 12:27:28,998 - topic #2 (0.333): 0.012*"’" + 0.009*"plans" + 0.008*"well" + 0.007*"needs" + 0.006*"10" + 0.006*"progress" + 0.005*"Riding" + 0.005*"East" + 0.004*"30" + 0.004*"development"
+2024-08-12 12:27:28,998 - topic diff=0.772752, rho=1.000000
+2024-08-12 12:27:28,998 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:27:28.998910', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:29,905 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:27:29,905 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:29,906 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:27:29,906 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:29,906 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:27:29,906 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:29,906 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:27:29,906 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:29,907 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:27:29,907 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:29,907 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:27:29,907 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:40,508 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:27:40,510 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)
+2024-08-12 12:27:40,510 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-08-12T12:27:40.510897', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:40,511 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:27:40,512 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:27:40,512 - using serial LDA version on this node
+2024-08-12 12:27:40,512 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:27:40,512 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:27:40,516 - -8.077 per-word bound, 270.1 perplexity estimate based on a held-out corpus of 1 documents with 2220 words
+2024-08-12 12:27:40,516 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:27:40,517 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"progress" + 0.006*"Sussex" + 0.006*"needs" + 0.006*"plans" + 0.005*"including" + 0.004*"impact" + 0.004*"December" + 0.004*"experiences"
+2024-08-12 12:27:40,518 - topic #1 (0.333): 0.020*"’" + 0.010*"needs" + 0.010*"well" + 0.009*"plans" + 0.008*"East" + 0.007*"progress" + 0.006*"Sussex" + 0.006*"including" + 0.005*"provide" + 0.005*"effective"
+2024-08-12 12:27:40,518 - topic #2 (0.333): 0.013*"’" + 0.010*"well" + 0.008*"plans" + 0.006*"East" + 0.006*"Sussex" + 0.006*"needs" + 0.006*"impact" + 0.005*"including" + 0.005*"effective" + 0.005*"education"
+2024-08-12 12:27:40,518 - topic diff=0.757427, rho=1.000000
+2024-08-12 12:27:40,518 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1111, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:27:40.518415', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:41,992 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:27:41,993 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:41,993 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:27:41,993 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:41,994 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:27:41,994 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:41,994 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:27:41,994 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:41,995 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:27:41,995 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:41,995 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:27:41,995 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:53,970 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:27:53,972 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)
+2024-08-12 12:27:53,972 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-08-12T12:27:53.972539', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:53,973 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:27:53,973 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:27:53,974 - using serial LDA version on this node
+2024-08-12 12:27:53,974 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:27:53,974 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:27:53,978 - -8.014 per-word bound, 258.5 perplexity estimate based on a held-out corpus of 1 documents with 2686 words
+2024-08-12 12:27:53,978 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:27:53,979 - topic #0 (0.333): 0.020*"’" + 0.007*"progress" + 0.006*"well" + 0.006*"family" + 0.006*"needs" + 0.005*"plans" + 0.005*"risk" + 0.005*"understand" + 0.005*"need" + 0.004*"helped"
+2024-08-12 12:27:53,979 - topic #1 (0.333): 0.012*"’" + 0.006*"plans" + 0.005*"well" + 0.005*"progress" + 0.005*"needs" + 0.005*"parents" + 0.004*"‘" + 0.004*"supported" + 0.004*"experiences" + 0.004*"leaders"
+2024-08-12 12:27:53,980 - topic #2 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"progress" + 0.006*"plans" + 0.006*"Essex" + 0.005*"experiences" + 0.005*"supported" + 0.005*"family" + 0.005*"understand"
+2024-08-12 12:27:53,980 - topic diff=0.818572, rho=1.000000
+2024-08-12 12:27:53,980 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:27:53.980360', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:27:54,916 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:27:54,916 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:54,917 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:27:54,917 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:54,917 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:27:54,917 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:54,917 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:27:54,917 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:54,918 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:27:54,918 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:27:54,918 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:27:54,918 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:05,686 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:28:05,688 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)
+2024-08-12 12:28:05,688 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-08-12T12:28:05.688868', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:05,689 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:28:05,690 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:28:05,690 - using serial LDA version on this node
+2024-08-12 12:28:05,690 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:28:05,690 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:28:05,694 - -8.045 per-word bound, 264.1 perplexity estimate based on a held-out corpus of 1 documents with 2356 words
+2024-08-12 12:28:05,694 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:28:05,696 - topic #0 (0.333): 0.011*"’" + 0.007*"good" + 0.007*"effective" + 0.007*"practice" + 0.006*"needs" + 0.005*"timely" + 0.005*"well" + 0.004*"quality" + 0.004*"improve" + 0.004*"focus"
+2024-08-12 12:28:05,696 - topic #1 (0.333): 0.010*"’" + 0.007*"effective" + 0.005*"practice" + 0.005*"need" + 0.005*"quality" + 0.004*"good" + 0.004*"needs" + 0.004*"timely" + 0.004*"improve" + 0.004*"home"
+2024-08-12 12:28:05,696 - topic #2 (0.333): 0.016*"’" + 0.010*"effective" + 0.008*"quality" + 0.007*"good" + 0.007*"well" + 0.006*"practice" + 0.006*"needs" + 0.006*"plans" + 0.006*"timely" + 0.005*"early"
+2024-08-12 12:28:05,696 - topic diff=0.794861, rho=1.000000
+2024-08-12 12:28:05,696 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:28:05.696760', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:06,621 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:28:06,621 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:06,621 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:28:06,621 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:06,622 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:28:06,622 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:06,622 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:28:06,622 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:06,622 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:28:06,622 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:06,623 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:28:06,623 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:18,138 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:28:18,141 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)
+2024-08-12 12:28:18,141 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-08-12T12:28:18.141224', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:18,142 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:28:18,142 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:28:18,142 - using serial LDA version on this node
+2024-08-12 12:28:18,143 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:28:18,143 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:28:18,147 - -8.060 per-word bound, 266.9 perplexity estimate based on a held-out corpus of 1 documents with 2579 words
+2024-08-12 12:28:18,147 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:28:18,148 - topic #0 (0.333): 0.019*"’" + 0.008*"needs" + 0.006*"plans" + 0.006*"progress" + 0.006*"2022" + 0.005*"need" + 0.005*"family" + 0.005*"well" + 0.005*"protection" + 0.004*"18"
+2024-08-12 12:28:18,148 - topic #1 (0.333): 0.017*"’" + 0.010*"needs" + 0.008*"2022" + 0.008*"February" + 0.007*"plans" + 0.006*"Gloucestershire" + 0.006*"well" + 0.006*"appropriate" + 0.005*"experienced" + 0.005*"timely"
+2024-08-12 12:28:18,148 - topic #2 (0.333): 0.016*"’" + 0.008*"February" + 0.007*"needs" + 0.006*"2022" + 0.006*"plans" + 0.005*"well" + 0.004*"Gloucestershire" + 0.004*"7" + 0.004*"experienced" + 0.004*"effective"
+2024-08-12 12:28:18,149 - topic diff=0.827434, rho=1.000000
+2024-08-12 12:28:18,149 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:28:18.149263', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:19,399 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:28:19,399 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:19,400 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:28:19,400 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:19,400 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:28:19,400 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:19,401 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:28:19,401 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:19,401 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:28:19,401 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:19,402 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:28:19,402 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:33,239 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:28:33,241 - built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)
+2024-08-12 12:28:33,241 - Dictionary lifecycle event {'msg': "built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)", 'datetime': '2024-08-12T12:28:33.241643', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:33,242 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:28:33,242 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:28:33,243 - using serial LDA version on this node
+2024-08-12 12:28:33,243 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:28:33,243 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:28:33,247 - -8.062 per-word bound, 267.3 perplexity estimate based on a held-out corpus of 1 documents with 2652 words
+2024-08-12 12:28:33,247 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:28:33,249 - topic #0 (0.333): 0.012*"’" + 0.006*"many" + 0.006*"Halton" + 0.006*"needs" + 0.005*"quality" + 0.005*"including" + 0.004*"Leaders" + 0.004*"need" + 0.004*"training" + 0.004*"13"
+2024-08-12 12:28:33,249 - topic #1 (0.333): 0.019*"’" + 0.007*"many" + 0.006*"needs" + 0.005*"quality" + 0.005*"including" + 0.005*"need" + 0.005*"13" + 0.005*"Halton" + 0.005*"2024" + 0.005*"plans"
+2024-08-12 12:28:33,249 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"Halton" + 0.006*"quality" + 0.006*"need" + 0.006*"protection" + 0.005*"plans" + 0.005*"including" + 0.005*"recently" + 0.005*"Leaders"
+2024-08-12 12:28:33,249 - topic diff=0.808105, rho=1.000000
+2024-08-12 12:28:33,249 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1172, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:28:33.249748', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:34,157 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:28:34,157 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:34,157 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:28:34,157 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:34,157 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:28:34,157 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:34,157 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:28:34,158 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:34,158 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:28:34,158 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:34,158 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:28:34,158 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:46,208 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:28:46,211 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)
+2024-08-12 12:28:46,211 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)", 'datetime': '2024-08-12T12:28:46.211254', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:46,212 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:28:46,212 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:28:46,212 - using serial LDA version on this node
+2024-08-12 12:28:46,213 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:28:46,213 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:28:46,216 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 2524 words
+2024-08-12 12:28:46,216 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:28:46,218 - topic #0 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"plans" + 0.007*"quality" + 0.007*"family" + 0.007*"new" + 0.006*"progress" + 0.006*"needs" + 0.005*"practice" + 0.005*"Hampshire"
+2024-08-12 12:28:46,218 - topic #1 (0.333): 0.015*"’" + 0.008*"family" + 0.007*"progress" + 0.007*"new" + 0.006*"well" + 0.005*"receive" + 0.005*"achieve" + 0.005*"plans" + 0.005*"carers" + 0.005*"June"
+2024-08-12 12:28:46,218 - topic #2 (0.333): 0.015*"’" + 0.006*"new" + 0.006*"progress" + 0.006*"family" + 0.005*"plans" + 0.005*"well" + 0.004*"understand" + 0.004*"leaders" + 0.004*"receive" + 0.004*"needs"
+2024-08-12 12:28:46,218 - topic diff=0.814089, rho=1.000000
+2024-08-12 12:28:46,219 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:28:46.219028', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:28:47,041 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:28:47,041 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:47,042 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:28:47,042 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:47,042 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:28:47,042 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:47,042 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:28:47,042 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:47,042 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:28:47,042 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:28:47,043 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:28:47,043 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:00,133 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:29:00,136 - built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)
+2024-08-12 12:29:00,136 - Dictionary lifecycle event {'msg': "built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)", 'datetime': '2024-08-12T12:29:00.136389', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:00,137 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:29:00,137 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:29:00,137 - using serial LDA version on this node
+2024-08-12 12:29:00,138 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:29:00,138 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:29:00,142 - -8.071 per-word bound, 268.9 perplexity estimate based on a held-out corpus of 1 documents with 2584 words
+2024-08-12 12:29:00,142 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:29:00,143 - topic #0 (0.333): 0.018*"’" + 0.007*"Hartlepool" + 0.007*"March" + 0.006*"needs" + 0.005*"well" + 0.005*"effective" + 0.005*"18" + 0.005*"leaders" + 0.005*"plans" + 0.005*"supported"
+2024-08-12 12:29:00,144 - topic #1 (0.333): 0.022*"’" + 0.008*"March" + 0.008*"Hartlepool" + 0.007*"needs" + 0.006*"well" + 0.006*"leaders" + 0.005*"strong" + 0.005*"18" + 0.005*"ensure" + 0.005*"clear"
+2024-08-12 12:29:00,144 - topic #2 (0.333): 0.018*"’" + 0.006*"March" + 0.006*"needs" + 0.006*"Hartlepool" + 0.006*"well" + 0.005*"leaders" + 0.004*"need" + 0.004*"plans" + 0.004*"right" + 0.004*"clear"
+2024-08-12 12:29:00,144 - topic diff=0.789920, rho=1.000000
+2024-08-12 12:29:00,144 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1171, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:29:00.144521', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:01,071 - Inspection date 2024-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:29:01,071 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:01,071 - Inspection date 2024-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:29:01,071 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:01,072 - Inspection date 2024-03-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:29:01,072 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:01,072 - Inspection date 2024-03-18 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:29:01,072 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:01,072 - Inspection date 2024-03-18 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:29:01,072 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:01,073 - Inspection date 2024-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:29:01,073 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:13,199 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:29:13,201 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
+2024-08-12 12:29:13,201 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-08-12T12:29:13.201608', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:13,202 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:29:13,202 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:29:13,203 - using serial LDA version on this node
+2024-08-12 12:29:13,203 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:29:13,203 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:29:13,207 - -8.044 per-word bound, 263.9 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
+2024-08-12 12:29:13,207 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:29:13,208 - topic #0 (0.333): 0.019*"’" + 0.006*"lack" + 0.006*"practice" + 0.005*"Herefordshire" + 0.005*"many" + 0.004*"need" + 0.004*"needs" + 0.004*"risk" + 0.004*"quality" + 0.004*"plans"
+2024-08-12 12:29:13,209 - topic #1 (0.333): 0.019*"’" + 0.006*"impact" + 0.006*"practice" + 0.005*"Herefordshire" + 0.005*"lack" + 0.004*"oversight" + 0.004*"needs" + 0.004*"2022" + 0.004*"18" + 0.004*"management"
+2024-08-12 12:29:13,209 - topic #2 (0.333): 0.014*"’" + 0.006*"needs" + 0.005*"Herefordshire" + 0.005*"practice" + 0.005*"progress" + 0.004*"plans" + 0.004*"quality" + 0.004*"impact" + 0.004*"carers" + 0.004*"many"
+2024-08-12 12:29:13,209 - topic diff=0.786915, rho=1.000000
+2024-08-12 12:29:13,209 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:29:13.209564', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:14,268 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:29:14,269 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:14,269 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:29:14,269 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:14,269 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:29:14,270 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:14,270 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:29:14,270 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:14,271 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:29:14,271 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:14,271 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:29:14,271 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:26,274 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:29:26,276 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)
+2024-08-12 12:29:26,276 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-08-12T12:29:26.276709', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:26,277 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:29:26,277 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:29:26,278 - using serial LDA version on this node
+2024-08-12 12:29:26,278 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:29:26,278 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:29:26,282 - -8.133 per-word bound, 280.8 perplexity estimate based on a held-out corpus of 1 documents with 2456 words
+2024-08-12 12:29:26,282 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:29:26,284 - topic #0 (0.333): 0.028*"’" + 0.006*"Hertfordshire" + 0.006*"well" + 0.006*"needs" + 0.005*"receive" + 0.005*"risk" + 0.005*"positive" + 0.004*"2023" + 0.004*"27" + 0.004*"need"
+2024-08-12 12:29:26,284 - topic #1 (0.333): 0.025*"’" + 0.007*"Hertfordshire" + 0.007*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"receive" + 0.004*"need" + 0.004*"January" + 0.004*"2023" + 0.004*"Leaders"
+2024-08-12 12:29:26,284 - topic #2 (0.333): 0.012*"’" + 0.007*"well" + 0.005*"Hertfordshire" + 0.005*"needs" + 0.004*"leaders" + 0.004*"23" + 0.004*"receive" + 0.004*"‘" + 0.004*"family" + 0.004*"27"
+2024-08-12 12:29:26,284 - topic diff=0.795568, rho=1.000000
+2024-08-12 12:29:26,284 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:29:26.284930', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:27,996 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:29:27,997 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:27,997 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:29:27,997 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:27,997 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:29:27,997 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:27,998 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:29:27,998 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:27,998 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:29:27,998 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:27,998 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:29:27,999 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:37,877 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:29:37,879 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)
+2024-08-12 12:29:37,879 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-08-12T12:29:37.879911', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:37,880 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:29:37,880 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:29:37,881 - using serial LDA version on this node
+2024-08-12 12:29:37,881 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:29:37,881 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:29:37,884 - -7.958 per-word bound, 248.6 perplexity estimate based on a held-out corpus of 1 documents with 1934 words
+2024-08-12 12:29:37,885 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:29:37,886 - topic #0 (0.333): 0.020*"’" + 0.007*"leaders" + 0.007*"needs" + 0.006*"well" + 0.006*"Wight" + 0.005*"2023" + 0.005*"3" + 0.005*"Senior" + 0.005*"Isle" + 0.005*"PAs"
+2024-08-12 12:29:37,886 - topic #1 (0.333): 0.012*"’" + 0.008*"leaders" + 0.005*"Senior" + 0.005*"supported" + 0.005*"well" + 0.005*"3" + 0.005*"Isle" + 0.005*"plans" + 0.004*"PAs" + 0.004*"good"
+2024-08-12 12:29:37,886 - topic #2 (0.333): 0.019*"’" + 0.010*"leaders" + 0.005*"progress" + 0.005*"plans" + 0.005*"needs" + 0.005*"well" + 0.005*"supported" + 0.005*"information" + 0.005*"improve" + 0.005*"30"
+2024-08-12 12:29:37,886 - topic diff=0.771655, rho=1.000000
+2024-08-12 12:29:37,887 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:29:37.887035', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:38,837 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:29:38,838 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:38,838 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:29:38,838 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:38,838 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:29:38,838 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:38,838 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:29:38,839 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:38,839 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:29:38,839 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:38,839 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:29:38,839 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:51,304 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:29:51,307 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)
+2024-08-12 12:29:51,307 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-08-12T12:29:51.307489', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:51,308 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:29:51,308 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:29:51,309 - using serial LDA version on this node
+2024-08-12 12:29:51,309 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:29:51,309 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:29:51,313 - -8.164 per-word bound, 286.8 perplexity estimate based on a held-out corpus of 1 documents with 2888 words
+2024-08-12 12:29:51,313 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:29:51,315 - topic #0 (0.333): 0.022*"’" + 0.012*"Kent" + 0.008*"needs" + 0.006*"well" + 0.006*"Council" + 0.006*"progress" + 0.006*"supported" + 0.005*"County" + 0.005*"practice" + 0.004*"impact"
+2024-08-12 12:29:51,315 - topic #1 (0.333): 0.018*"’" + 0.008*"Kent" + 0.007*"needs" + 0.006*"County" + 0.006*"supported" + 0.006*"Council" + 0.006*"well" + 0.005*"9" + 0.004*"leaders" + 0.004*"practice"
+2024-08-12 12:29:51,315 - topic #2 (0.333): 0.009*"’" + 0.008*"Kent" + 0.006*"well" + 0.005*"Council" + 0.005*"supported" + 0.005*"needs" + 0.004*"leaders" + 0.004*"progress" + 0.004*"County" + 0.004*"need"
+2024-08-12 12:29:51,315 - topic diff=0.809579, rho=1.000000
+2024-08-12 12:29:51,315 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1298, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:29:51.315825', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:29:52,239 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:29:52,239 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:52,240 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:29:52,240 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:52,240 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:29:52,240 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:52,240 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:29:52,241 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:52,241 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:29:52,241 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:29:52,241 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:29:52,241 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:02,209 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:30:02,211 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)
+2024-08-12 12:30:02,211 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-08-12T12:30:02.211528', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:02,212 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:30:02,212 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:30:02,212 - using serial LDA version on this node
+2024-08-12 12:30:02,213 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:30:02,213 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:30:02,216 - -7.945 per-word bound, 246.5 perplexity estimate based on a held-out corpus of 1 documents with 1970 words
+2024-08-12 12:30:02,216 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:30:02,218 - topic #0 (0.333): 0.012*"’" + 0.006*"planning" + 0.006*"number" + 0.005*"well" + 0.005*"practice" + 0.005*"management" + 0.005*"risks" + 0.005*"small" + 0.005*"protection" + 0.005*"need"
+2024-08-12 12:30:02,218 - topic #1 (0.333): 0.017*"’" + 0.008*"number" + 0.007*"Hull" + 0.006*"planning" + 0.006*"management" + 0.006*"need" + 0.006*"protection" + 0.006*"practice" + 0.006*"well" + 0.006*"25"
+2024-08-12 12:30:02,218 - topic #2 (0.333): 0.017*"’" + 0.007*"planning" + 0.006*"well" + 0.006*"number" + 0.006*"protection" + 0.006*"practice" + 0.005*"teams" + 0.005*"need" + 0.005*"risks" + 0.005*"small"
+2024-08-12 12:30:02,218 - topic diff=0.756983, rho=1.000000
+2024-08-12 12:30:02,218 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:30:02.218873', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:03,084 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:30:03,084 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:03,085 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:30:03,085 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:03,085 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:30:03,085 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:03,085 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:30:03,085 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:03,086 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:30:03,086 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:03,086 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:30:03,086 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:15,331 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:30:15,334 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)
+2024-08-12 12:30:15,335 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)", 'datetime': '2024-08-12T12:30:15.334998', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:15,336 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:30:15,337 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:30:15,337 - using serial LDA version on this node
+2024-08-12 12:30:15,338 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:30:15,338 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:30:15,345 - -8.055 per-word bound, 266.0 perplexity estimate based on a held-out corpus of 1 documents with 2489 words
+2024-08-12 12:30:15,345 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:30:15,348 - topic #0 (0.333): 0.009*"’" + 0.005*"needs" + 0.005*"practice" + 0.005*"senior" + 0.005*"quality" + 0.004*"plans" + 0.004*"team" + 0.004*"permanence" + 0.004*"well" + 0.004*"good"
+2024-08-12 12:30:15,348 - topic #1 (0.333): 0.010*"’" + 0.006*"quality" + 0.005*"practice" + 0.005*"good" + 0.005*"needs" + 0.005*"permanence" + 0.005*"Senior" + 0.005*"training" + 0.005*"plans" + 0.005*"protection"
+2024-08-12 12:30:15,348 - topic #2 (0.333): 0.014*"’" + 0.007*"quality" + 0.007*"good" + 0.007*"practice" + 0.006*"well" + 0.006*"protection" + 0.005*"plans" + 0.005*"permanence" + 0.005*"training" + 0.005*"need"
+2024-08-12 12:30:15,348 - topic diff=0.798526, rho=1.000000
+2024-08-12 12:30:15,348 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:30:15.348771', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:16,246 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:30:16,246 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:16,247 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:30:16,247 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:16,247 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:30:16,247 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:16,247 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:30:16,247 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:16,247 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:30:16,248 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:16,248 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:30:16,248 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:24,850 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:30:24,852 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)
+2024-08-12 12:30:24,852 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-08-12T12:30:24.852194', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:24,853 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:30:24,853 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:30:24,853 - using serial LDA version on this node
+2024-08-12 12:30:24,853 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:30:24,853 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:30:24,856 - -7.831 per-word bound, 227.7 perplexity estimate based on a held-out corpus of 1 documents with 1837 words
+2024-08-12 12:30:24,857 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:30:24,858 - topic #0 (0.333): 0.012*"’" + 0.009*"progress" + 0.009*"needs" + 0.007*"quality" + 0.006*"plans" + 0.006*"Knowsley" + 0.006*"experiences" + 0.006*"22" + 0.005*"2021" + 0.005*"education"
+2024-08-12 12:30:24,858 - topic #1 (0.333): 0.012*"’" + 0.008*"progress" + 0.007*"quality" + 0.007*"plans" + 0.006*"need" + 0.006*"2021" + 0.006*"Knowsley" + 0.005*"needs" + 0.005*"11" + 0.005*"leaders"
+2024-08-12 12:30:24,858 - topic #2 (0.333): 0.019*"’" + 0.008*"plans" + 0.007*"progress" + 0.007*"needs" + 0.006*"Knowsley" + 0.006*"2021" + 0.006*"quality" + 0.005*"good" + 0.005*"11" + 0.005*"need"
+2024-08-12 12:30:24,858 - topic diff=0.744774, rho=1.000000
+2024-08-12 12:30:24,858 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=886, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:30:24.858808', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:25,999 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:30:25,999 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:26,000 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:30:26,000 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:26,000 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:30:26,000 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:26,000 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:30:26,000 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:26,000 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:30:26,001 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:26,001 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:30:26,001 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:36,640 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:30:36,642 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)
+2024-08-12 12:30:36,642 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-08-12T12:30:36.642757', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:36,643 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:30:36,643 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:30:36,644 - using serial LDA version on this node
+2024-08-12 12:30:36,644 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:30:36,644 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:30:36,648 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 2263 words
+2024-08-12 12:30:36,648 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:30:36,649 - topic #0 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"need" + 0.006*"supported" + 0.005*"homes" + 0.005*"parents" + 0.005*"information" + 0.005*"9" + 0.005*"health"
+2024-08-12 12:30:36,649 - topic #1 (0.333): 0.018*"’" + 0.009*"well" + 0.009*"needs" + 0.007*"need" + 0.007*"practice" + 0.006*"plans" + 0.006*"Lancashire" + 0.005*"positive" + 0.005*"progress" + 0.005*"number"
+2024-08-12 12:30:36,650 - topic #2 (0.333): 0.013*"’" + 0.009*"well" + 0.008*"Lancashire" + 0.007*"need" + 0.005*"live" + 0.005*"supported" + 0.005*"needs" + 0.005*"practice" + 0.005*"health" + 0.005*"positive"
+2024-08-12 12:30:36,650 - topic diff=0.780135, rho=1.000000
+2024-08-12 12:30:36,650 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:30:36.650325', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:37,572 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:30:37,572 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:37,572 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:30:37,572 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:37,573 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:30:37,573 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:37,573 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:30:37,573 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:37,573 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:30:37,573 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:37,574 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:30:37,574 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:49,563 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:30:49,565 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)
+2024-08-12 12:30:49,565 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-08-12T12:30:49.565775', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:49,566 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:30:49,566 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:30:49,567 - using serial LDA version on this node
+2024-08-12 12:30:49,567 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:30:49,567 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:30:49,571 - -8.009 per-word bound, 257.6 perplexity estimate based on a held-out corpus of 1 documents with 2261 words
+2024-08-12 12:30:49,571 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:30:49,572 - topic #0 (0.333): 0.018*"’" + 0.007*"Leeds" + 0.006*"well" + 0.005*"practice" + 0.005*"needs" + 0.004*"risk" + 0.004*"supported" + 0.004*"ensure" + 0.004*"protection" + 0.004*"plans"
+2024-08-12 12:30:49,572 - topic #1 (0.333): 0.017*"’" + 0.008*"needs" + 0.007*"Leeds" + 0.006*"well" + 0.005*"risk" + 0.005*"protection" + 0.005*"plans" + 0.005*"4" + 0.005*"21" + 0.005*"March"
+2024-08-12 12:30:49,573 - topic #2 (0.333): 0.013*"’" + 0.007*"Leeds" + 0.007*"needs" + 0.006*"risk" + 0.005*"well" + 0.005*"2022" + 0.004*"4" + 0.004*"making" + 0.004*"plans" + 0.004*"ensure"
+2024-08-12 12:30:49,573 - topic diff=0.772864, rho=1.000000
+2024-08-12 12:30:49,573 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1071, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:30:49.573256', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:30:50,433 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:30:50,433 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:50,434 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:30:50,434 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:50,434 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:30:50,434 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:50,434 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:30:50,434 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:50,435 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:30:50,435 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:30:50,435 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:30:50,435 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:00,390 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:31:00,392 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)
+2024-08-12 12:31:00,392 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-08-12T12:31:00.392452', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:00,393 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:31:00,393 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:31:00,393 - using serial LDA version on this node
+2024-08-12 12:31:00,394 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:31:00,394 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:31:00,397 - -7.878 per-word bound, 235.3 perplexity estimate based on a held-out corpus of 1 documents with 1950 words
+2024-08-12 12:31:00,397 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:31:00,398 - topic #0 (0.333): 0.012*"’" + 0.006*"2021" + 0.006*"well" + 0.006*"needs" + 0.006*"good" + 0.005*"Leicester" + 0.004*"progress" + 0.004*"ensure" + 0.004*"Council" + 0.004*"number"
+2024-08-12 12:31:00,399 - topic #1 (0.333): 0.021*"’" + 0.010*"2021" + 0.010*"well" + 0.009*"Leicester" + 0.008*"needs" + 0.007*"good" + 0.006*"ensure" + 0.006*"number" + 0.006*"including" + 0.005*"September"
+2024-08-12 12:31:00,399 - topic #2 (0.333): 0.023*"’" + 0.009*"well" + 0.007*"Leicester" + 0.007*"2021" + 0.006*"needs" + 0.006*"1" + 0.006*"improve" + 0.005*"number" + 0.005*"20" + 0.005*"good"
+2024-08-12 12:31:00,399 - topic diff=0.794509, rho=1.000000
+2024-08-12 12:31:00,399 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=932, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:31:00.399444', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:01,487 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:31:01,487 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:01,487 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:31:01,487 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:01,487 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:31:01,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:01,488 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:31:01,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:01,488 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:31:01,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:01,488 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:31:01,488 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:15,870 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:31:15,872 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)
+2024-08-12 12:31:15,872 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)", 'datetime': '2024-08-12T12:31:15.872671', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:15,873 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:31:15,873 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:31:15,874 - using serial LDA version on this node
+2024-08-12 12:31:15,874 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:31:15,874 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:31:15,878 - -8.105 per-word bound, 275.3 perplexity estimate based on a held-out corpus of 1 documents with 2745 words
+2024-08-12 12:31:15,879 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:31:15,880 - topic #0 (0.333): 0.017*"’" + 0.007*"Leicestershire" + 0.007*"well" + 0.006*"needs" + 0.005*"family" + 0.005*"experiences" + 0.005*"understand" + 0.005*"need" + 0.005*"plans" + 0.004*"progress"
+2024-08-12 12:31:15,880 - topic #1 (0.333): 0.018*"’" + 0.008*"well" + 0.006*"family" + 0.005*"Leicestershire" + 0.005*"understand" + 0.005*"PAs" + 0.005*"experiences" + 0.005*"need" + 0.005*"plans" + 0.005*"ensure"
+2024-08-12 12:31:15,880 - topic #2 (0.333): 0.019*"’" + 0.010*"well" + 0.006*"Leicestershire" + 0.006*"family" + 0.006*"need" + 0.006*"needs" + 0.005*"risk" + 0.005*"experiences" + 0.005*"plans" + 0.005*"appropriate"
+2024-08-12 12:31:15,881 - topic diff=0.810781, rho=1.000000
+2024-08-12 12:31:15,881 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:31:15.881180', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:17,097 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:31:17,098 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:17,103 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:31:17,103 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:17,103 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:31:17,103 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:17,103 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:31:17,104 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:17,104 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:31:17,104 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:17,104 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:31:17,105 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:31,579 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:31:31,582 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)
+2024-08-12 12:31:31,582 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-08-12T12:31:31.582267', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:31,583 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:31:31,583 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:31:31,583 - using serial LDA version on this node
+2024-08-12 12:31:31,584 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:31:31,584 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:31:31,588 - -8.186 per-word bound, 291.3 perplexity estimate based on a held-out corpus of 1 documents with 2927 words
+2024-08-12 12:31:31,588 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:31:31,590 - topic #0 (0.333): 0.028*"’" + 0.009*"Lincolnshire" + 0.007*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"effective" + 0.004*"family" + 0.004*"24" + 0.004*"progress" + 0.004*"April"
+2024-08-12 12:31:31,590 - topic #1 (0.333): 0.019*"’" + 0.006*"needs" + 0.006*"Lincolnshire" + 0.004*"well" + 0.004*"family" + 0.004*"28" + 0.004*"progress" + 0.004*"plans" + 0.004*"24" + 0.004*"need"
+2024-08-12 12:31:31,590 - topic #2 (0.333): 0.016*"’" + 0.006*"needs" + 0.006*"Lincolnshire" + 0.006*"well" + 0.005*"plans" + 0.005*"progress" + 0.004*"need" + 0.004*"family" + 0.004*"24" + 0.004*"28"
+2024-08-12 12:31:31,590 - topic diff=0.789999, rho=1.000000
+2024-08-12 12:31:31,591 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1323, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:31:31.591046', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:32,560 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:31:32,560 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:32,561 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:31:32,561 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:32,561 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:31:32,561 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:32,561 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:31:32,561 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:32,561 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:31:32,562 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:32,562 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:31:32,562 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:45,844 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:31:45,846 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
+2024-08-12 12:31:45,846 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-08-12T12:31:45.846644', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:45,847 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:31:45,847 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:31:45,848 - using serial LDA version on this node
+2024-08-12 12:31:45,848 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:31:45,848 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:31:45,852 - -7.996 per-word bound, 255.3 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
+2024-08-12 12:31:45,852 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:31:45,854 - topic #0 (0.333): 0.019*"’" + 0.008*"Liverpool" + 0.008*"needs" + 0.007*"need" + 0.007*"always" + 0.006*"practice" + 0.005*"protection" + 0.005*"quality" + 0.005*"24" + 0.005*"PAs"
+2024-08-12 12:31:45,854 - topic #1 (0.333): 0.016*"’" + 0.006*"needs" + 0.006*"quality" + 0.005*"practice" + 0.005*"always" + 0.004*"need" + 0.004*"timely" + 0.004*"senior" + 0.004*"harm" + 0.004*"met"
+2024-08-12 12:31:45,854 - topic #2 (0.333): 0.022*"’" + 0.008*"practice" + 0.007*"needs" + 0.007*"always" + 0.007*"need" + 0.005*"quality" + 0.005*"protection" + 0.005*"Liverpool" + 0.004*"planning" + 0.004*"13"
+2024-08-12 12:31:45,854 - topic diff=0.842649, rho=1.000000
+2024-08-12 12:31:45,854 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1134, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:31:45.854784', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:46,793 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:31:46,794 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:46,794 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:31:46,794 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:46,794 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:31:46,795 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:46,795 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:31:46,795 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:46,795 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:31:46,795 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:46,795 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:31:46,795 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:31:59,669 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:31:59,671 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)
+2024-08-12 12:31:59,672 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-08-12T12:31:59.672096', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:31:59,673 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:31:59,673 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:31:59,673 - using serial LDA version on this node
+2024-08-12 12:31:59,674 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:31:59,674 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:31:59,678 - -8.090 per-word bound, 272.5 perplexity estimate based on a held-out corpus of 1 documents with 2610 words
+2024-08-12 12:31:59,678 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:31:59,679 - topic #0 (0.333): 0.028*"’" + 0.009*"needs" + 0.007*"plans" + 0.006*"carers" + 0.005*"good" + 0.005*"practice" + 0.005*"information" + 0.005*"well" + 0.005*"planning" + 0.005*"progress"
+2024-08-12 12:31:59,679 - topic #1 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"good" + 0.005*"well" + 0.005*"plans" + 0.004*"carers" + 0.004*"risk" + 0.004*"information" + 0.004*"Barking" + 0.004*"progress"
+2024-08-12 12:31:59,679 - topic #2 (0.333): 0.018*"’" + 0.006*"needs" + 0.005*"good" + 0.005*"well" + 0.005*"practice" + 0.005*"plans" + 0.004*"London" + 0.004*"impact" + 0.004*"progress" + 0.004*"information"
+2024-08-12 12:31:59,680 - topic diff=0.807570, rho=1.000000
+2024-08-12 12:31:59,680 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1193, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:31:59.680154', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:00,855 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:32:00,855 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:00,856 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:32:00,858 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:00,859 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:32:00,859 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:00,859 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:32:00,859 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:00,860 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:32:00,860 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:00,860 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:32:00,860 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:13,516 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:32:13,519 - built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)
+2024-08-12 12:32:13,519 - Dictionary lifecycle event {'msg': "built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)", 'datetime': '2024-08-12T12:32:13.519247', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:13,520 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:32:13,520 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:32:13,520 - using serial LDA version on this node
+2024-08-12 12:32:13,521 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:32:13,521 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:32:13,525 - -8.053 per-word bound, 265.7 perplexity estimate based on a held-out corpus of 1 documents with 2445 words
+2024-08-12 12:32:13,525 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:32:13,526 - topic #0 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"Barnet" + 0.008*"plans" + 0.005*"experiences" + 0.004*"need" + 0.004*"14" + 0.004*"June" + 0.004*"carers"
+2024-08-12 12:32:13,526 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"Barnet" + 0.006*"plans" + 0.005*"risk" + 0.004*"experiences" + 0.004*"inform" + 0.004*"effective" + 0.004*"progress"
+2024-08-12 12:32:13,527 - topic #2 (0.333): 0.023*"’" + 0.008*"needs" + 0.007*"plans" + 0.007*"Barnet" + 0.005*"well" + 0.005*"2024" + 0.005*"information" + 0.005*"10" + 0.004*"experiences" + 0.004*"parents"
+2024-08-12 12:32:13,527 - topic diff=0.786059, rho=1.000000
+2024-08-12 12:32:13,527 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1132, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:32:13.527308', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:14,458 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:32:14,458 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:14,459 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:32:14,459 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:14,460 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:32:14,460 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:14,460 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:32:14,460 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:14,460 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:32:14,460 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:14,461 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:32:14,461 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:27,188 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:32:27,191 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)
+2024-08-12 12:32:27,191 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-08-12T12:32:27.191234', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:27,192 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:32:27,192 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:32:27,192 - using serial LDA version on this node
+2024-08-12 12:32:27,193 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:32:27,193 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:32:27,197 - -8.103 per-word bound, 275.0 perplexity estimate based on a held-out corpus of 1 documents with 2563 words
+2024-08-12 12:32:27,197 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:32:27,198 - topic #0 (0.333): 0.020*"’" + 0.006*"needs" + 0.006*"effective" + 0.005*"need" + 0.005*"well" + 0.005*"Bexley" + 0.005*"including" + 0.005*"10" + 0.004*"plans" + 0.004*"practice"
+2024-08-12 12:32:27,198 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"Bexley" + 0.006*"effective" + 0.005*"plans" + 0.005*"10" + 0.005*"need" + 0.005*"clear" + 0.004*"ensure"
+2024-08-12 12:32:27,198 - topic #2 (0.333): 0.018*"’" + 0.006*"need" + 0.006*"well" + 0.006*"needs" + 0.005*"plans" + 0.005*"effective" + 0.004*"2023" + 0.004*"Bexley" + 0.004*"practice" + 0.004*"oversight"
+2024-08-12 12:32:27,199 - topic diff=0.779390, rho=1.000000
+2024-08-12 12:32:27,199 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1190, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:32:27.199211', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:28,137 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:32:28,137 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:28,138 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:32:28,138 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:28,138 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:32:28,138 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:28,138 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:32:28,139 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:28,139 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:32:28,139 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:28,139 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:32:28,139 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:39,815 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:32:39,817 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)
+2024-08-12 12:32:39,817 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-08-12T12:32:39.817341', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:39,818 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:32:39,818 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:32:39,818 - using serial LDA version on this node
+2024-08-12 12:32:39,819 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:32:39,819 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:32:39,822 - -7.930 per-word bound, 243.8 perplexity estimate based on a held-out corpus of 1 documents with 2371 words
+2024-08-12 12:32:39,822 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:32:39,824 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.007*"quality" + 0.006*"progress" + 0.006*"leaders" + 0.006*"plans" + 0.005*"information" + 0.005*"Brent" + 0.005*"senior" + 0.005*"good"
+2024-08-12 12:32:39,824 - topic #1 (0.333): 0.018*"’" + 0.008*"leaders" + 0.008*"well" + 0.007*"progress" + 0.007*"plans" + 0.006*"However" + 0.006*"number" + 0.006*"Brent" + 0.005*"good" + 0.005*"senior"
+2024-08-12 12:32:39,824 - topic #2 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"plans" + 0.007*"leaders" + 0.006*"good" + 0.006*"practice" + 0.006*"number" + 0.005*"progress" + 0.005*"timely" + 0.005*"small"
+2024-08-12 12:32:39,824 - topic diff=0.821092, rho=1.000000
+2024-08-12 12:32:39,824 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:32:39.824873', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:40,722 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:32:40,722 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:40,722 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:32:40,722 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:40,722 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:32:40,723 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:40,723 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:32:40,723 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:40,723 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:32:40,723 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:40,723 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:32:40,723 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:54,443 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:32:54,445 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)
+2024-08-12 12:32:54,445 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-08-12T12:32:54.445638', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:54,446 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:32:54,446 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:32:54,447 - using serial LDA version on this node
+2024-08-12 12:32:54,447 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:32:54,447 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:32:54,451 - -8.181 per-word bound, 290.1 perplexity estimate based on a held-out corpus of 1 documents with 2640 words
+2024-08-12 12:32:54,451 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:32:54,453 - topic #0 (0.333): 0.025*"’" + 0.009*"Bromley" + 0.008*"needs" + 0.008*"well" + 0.006*"plans" + 0.006*"leaders" + 0.005*"practice" + 0.005*"progress" + 0.005*"health" + 0.004*"YPAs"
+2024-08-12 12:32:54,453 - topic #1 (0.333): 0.017*"’" + 0.010*"Bromley" + 0.007*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"education" + 0.005*"leaders" + 0.004*"practice" + 0.004*"17" + 0.004*"November"
+2024-08-12 12:32:54,453 - topic #2 (0.333): 0.016*"’" + 0.008*"Bromley" + 0.006*"well" + 0.005*"leaders" + 0.005*"health" + 0.005*"practice" + 0.005*"needs" + 0.005*"education" + 0.004*"plans" + 0.004*"13"
+2024-08-12 12:32:54,453 - topic diff=0.767327, rho=1.000000
+2024-08-12 12:32:54,454 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1266, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:32:54.454098', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:32:55,681 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:32:55,682 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:55,682 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:32:55,682 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:55,682 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:32:55,682 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:55,682 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:32:55,683 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:55,683 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:32:55,683 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:32:55,683 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:32:55,683 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:04,478 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:33:04,483 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)
+2024-08-12 12:33:04,483 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-08-12T12:33:04.483546', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:04,485 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:33:04,485 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:33:04,485 - using serial LDA version on this node
+2024-08-12 12:33:04,485 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:33:04,486 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:33:04,492 - -8.058 per-word bound, 266.5 perplexity estimate based on a held-out corpus of 1 documents with 1735 words
+2024-08-12 12:33:04,492 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:33:04,494 - topic #0 (0.333): 0.012*"’" + 0.007*"leaders" + 0.007*"practice" + 0.007*"Camden" + 0.006*"needs" + 0.005*"protection" + 0.005*"well" + 0.005*"29" + 0.004*"response" + 0.004*"meetings"
+2024-08-12 12:33:04,495 - topic #1 (0.333): 0.010*"’" + 0.007*"Camden" + 0.006*"well" + 0.005*"practice" + 0.005*"leaders" + 0.005*"response" + 0.005*"protection" + 0.005*"needs" + 0.004*"appropriate" + 0.004*"25"
+2024-08-12 12:33:04,495 - topic #2 (0.333): 0.009*"’" + 0.007*"Camden" + 0.006*"leaders" + 0.005*"practice" + 0.005*"protection" + 0.005*"29" + 0.004*"well" + 0.004*"response" + 0.004*"needs" + 0.004*"progress"
+2024-08-12 12:33:04,495 - topic diff=0.701585, rho=1.000000
+2024-08-12 12:33:04,495 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=993, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:33:04.495565', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:05,384 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:33:05,384 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:05,385 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:33:05,385 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:05,385 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:33:05,385 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:05,385 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:33:05,385 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:05,386 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:33:05,386 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:05,386 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:33:05,386 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:15,990 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:33:15,992 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)
+2024-08-12 12:33:15,992 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-08-12T12:33:15.992470', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:15,993 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:33:15,993 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:33:15,993 - using serial LDA version on this node
+2024-08-12 12:33:15,994 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:33:15,994 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:33:15,999 - -7.983 per-word bound, 253.0 perplexity estimate based on a held-out corpus of 1 documents with 2209 words
+2024-08-12 12:33:15,999 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:33:16,001 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"Croydon" + 0.007*"needs" + 0.007*"quality" + 0.006*"need" + 0.005*"plans" + 0.005*"health" + 0.005*"education" + 0.005*"effective"
+2024-08-12 12:33:16,001 - topic #1 (0.333): 0.010*"’" + 0.006*"well" + 0.006*"needs" + 0.006*"Senior" + 0.005*"ensure" + 0.005*"good" + 0.005*"Croydon" + 0.005*"need" + 0.005*"effective" + 0.005*"risk"
+2024-08-12 12:33:16,002 - topic #2 (0.333): 0.010*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"Senior" + 0.005*"ensure" + 0.005*"plans" + 0.005*"good" + 0.005*"quality" + 0.005*"need" + 0.005*"risk"
+2024-08-12 12:33:16,002 - topic diff=0.773317, rho=1.000000
+2024-08-12 12:33:16,002 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:33:16.002333', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:17,014 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:33:17,014 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:17,015 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:33:17,015 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:17,015 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:33:17,015 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:17,015 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:33:17,016 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:17,016 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:33:17,016 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:17,016 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:33:17,016 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:28,597 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:33:28,599 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)
+2024-08-12 12:33:28,600 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)", 'datetime': '2024-08-12T12:33:28.600030', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:28,601 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:33:28,601 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:33:28,601 - using serial LDA version on this node
+2024-08-12 12:33:28,601 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:33:28,601 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:33:28,605 - -8.050 per-word bound, 265.1 perplexity estimate based on a held-out corpus of 1 documents with 2365 words
+2024-08-12 12:33:28,605 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:33:28,607 - topic #0 (0.333): 0.008*"’" + 0.005*"plans" + 0.005*"well" + 0.005*"Ealing" + 0.004*"needs" + 0.004*"effective" + 0.003*"impact" + 0.003*"22" + 0.003*"3" + 0.003*"need"
+2024-08-12 12:33:28,607 - topic #1 (0.333): 0.023*"’" + 0.009*"Ealing" + 0.009*"well" + 0.007*"needs" + 0.007*"progress" + 0.006*"plans" + 0.006*"need" + 0.006*"effective" + 0.005*"3" + 0.005*"quality"
+2024-08-12 12:33:28,607 - topic #2 (0.333): 0.013*"’" + 0.008*"Ealing" + 0.006*"progress" + 0.006*"well" + 0.005*"plans" + 0.005*"London" + 0.004*"needs" + 0.004*"effective" + 0.004*"need" + 0.004*"good"
+2024-08-12 12:33:28,607 - topic diff=0.826797, rho=1.000000
+2024-08-12 12:33:28,607 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:33:28.607972', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:29,580 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:33:29,580 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:29,580 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:33:29,580 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:29,580 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:33:29,580 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:29,581 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:33:29,581 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:29,581 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:33:29,581 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:29,581 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:33:29,581 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:39,661 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:33:39,663 - built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)
+2024-08-12 12:33:39,664 - Dictionary lifecycle event {'msg': "built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)", 'datetime': '2024-08-12T12:33:39.664097', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:39,665 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:33:39,665 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:33:39,665 - using serial LDA version on this node
+2024-08-12 12:33:39,665 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:33:39,665 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:33:39,669 - -7.935 per-word bound, 244.7 perplexity estimate based on a held-out corpus of 1 documents with 2104 words
+2024-08-12 12:33:39,669 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:33:39,670 - topic #0 (0.333): 0.009*"needs" + 0.008*"’" + 0.006*"ensure" + 0.006*"timely" + 0.005*"clear" + 0.005*"need" + 0.005*"Enfield" + 0.005*"appropriate" + 0.005*"practice" + 0.005*"leaders"
+2024-08-12 12:33:39,671 - topic #1 (0.333): 0.018*"’" + 0.009*"needs" + 0.009*"good" + 0.008*"ensure" + 0.008*"effective" + 0.007*"practice" + 0.007*"quality" + 0.006*"progress" + 0.006*"Enfield" + 0.006*"clear"
+2024-08-12 12:33:39,671 - topic #2 (0.333): 0.012*"’" + 0.009*"practice" + 0.008*"ensure" + 0.007*"clear" + 0.007*"Enfield" + 0.007*"needs" + 0.007*"good" + 0.006*"effective" + 0.006*"quality" + 0.006*"timely"
+2024-08-12 12:33:39,671 - topic diff=0.782279, rho=1.000000
+2024-08-12 12:33:39,671 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=999, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:33:39.671521', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:40,763 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:33:40,764 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:40,764 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:33:40,764 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:40,764 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:33:40,764 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:40,765 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:33:40,765 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:40,765 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:33:40,765 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:40,765 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:33:40,765 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:51,516 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:33:51,518 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)
+2024-08-12 12:33:51,518 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)", 'datetime': '2024-08-12T12:33:51.518330', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:51,519 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:33:51,519 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:33:51,519 - using serial LDA version on this node
+2024-08-12 12:33:51,520 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:33:51,520 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:33:51,523 - -7.986 per-word bound, 253.4 perplexity estimate based on a held-out corpus of 1 documents with 2078 words
+2024-08-12 12:33:51,523 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:33:51,525 - topic #0 (0.333): 0.018*"’" + 0.012*"Greenwich" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.005*"provide" + 0.005*"7" + 0.004*"Borough" + 0.004*"June" + 0.004*"carers"
+2024-08-12 12:33:51,525 - topic #1 (0.333): 0.020*"’" + 0.010*"Greenwich" + 0.008*"needs" + 0.007*"plans" + 0.005*"well" + 0.005*"provide" + 0.005*"progress" + 0.005*"3" + 0.005*"2024" + 0.005*"quality"
+2024-08-12 12:33:51,525 - topic #2 (0.333): 0.014*"’" + 0.010*"Greenwich" + 0.008*"well" + 0.006*"needs" + 0.004*"3" + 0.004*"plans" + 0.004*"carers" + 0.004*"progress" + 0.004*"7" + 0.004*"Royal"
+2024-08-12 12:33:51,525 - topic diff=0.754461, rho=1.000000
+2024-08-12 12:33:51,525 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:33:51.525727', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:33:52,495 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:33:52,496 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:52,496 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:33:52,496 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:52,496 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:33:52,496 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:52,497 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:33:52,497 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:52,497 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:33:52,497 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:33:52,497 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:33:52,497 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:04,307 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:34:04,309 - built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)
+2024-08-12 12:34:04,309 - Dictionary lifecycle event {'msg': "built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)", 'datetime': '2024-08-12T12:34:04.309718', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:04,310 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:34:04,310 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:34:04,311 - using serial LDA version on this node
+2024-08-12 12:34:04,311 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:34:04,311 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:34:04,315 - -8.000 per-word bound, 256.0 perplexity estimate based on a held-out corpus of 1 documents with 2603 words
+2024-08-12 12:34:04,315 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:34:04,317 - topic #0 (0.333): 0.009*"practice" + 0.009*"’" + 0.006*"However" + 0.006*"plans" + 0.006*"effective" + 0.006*"number" + 0.006*"including" + 0.006*"planning" + 0.006*"within" + 0.005*"leaders"
+2024-08-12 12:34:04,317 - topic #1 (0.333): 0.018*"’" + 0.011*"practice" + 0.008*"number" + 0.007*"planning" + 0.006*"effective" + 0.006*"within" + 0.006*"needs" + 0.006*"quality" + 0.005*"small" + 0.005*"protection"
+2024-08-12 12:34:04,317 - topic #2 (0.333): 0.009*"’" + 0.007*"practice" + 0.006*"plans" + 0.005*"planning" + 0.005*"oversight" + 0.005*"needs" + 0.005*"quality" + 0.005*"progress" + 0.005*"need" + 0.004*"including"
+2024-08-12 12:34:04,317 - topic diff=0.847414, rho=1.000000
+2024-08-12 12:34:04,317 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1122, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:34:04.317722', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:05,535 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:34:05,535 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:05,535 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:34:05,536 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:05,536 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:34:05,536 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:05,536 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:34:05,536 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:05,536 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:34:05,537 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:05,537 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:34:05,537 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:19,272 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:34:19,275 - built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
+2024-08-12 12:34:19,275 - Dictionary lifecycle event {'msg': "built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-08-12T12:34:19.275646', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:19,276 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:34:19,277 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:34:19,277 - using serial LDA version on this node
+2024-08-12 12:34:19,277 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:34:19,277 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:34:19,282 - -8.199 per-word bound, 293.9 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
+2024-08-12 12:34:19,282 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:34:19,283 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"receive" + 0.006*"needs" + 0.005*"Hammersmith" + 0.005*"effective" + 0.005*"plans" + 0.005*"11" + 0.005*"supported" + 0.005*"Leaders"
+2024-08-12 12:34:19,283 - topic #1 (0.333): 0.011*"’" + 0.007*"well" + 0.005*"protection" + 0.004*"receive" + 0.004*"need" + 0.004*"2024" + 0.004*"Hammersmith" + 0.004*"Fulham" + 0.004*"timely" + 0.004*"leaders"
+2024-08-12 12:34:19,284 - topic #2 (0.333): 0.010*"’" + 0.006*"well" + 0.005*"Fulham" + 0.005*"needs" + 0.005*"receive" + 0.004*"plans" + 0.004*"2024" + 0.004*"timely" + 0.004*"leaders" + 0.004*"progress"
+2024-08-12 12:34:19,284 - topic diff=0.810679, rho=1.000000
+2024-08-12 12:34:19,284 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1330, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:34:19.284326', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:20,343 - Inspection date 2024-03-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:34:20,343 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:20,343 - Inspection date 2024-03-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:34:20,343 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:20,344 - Inspection date 2024-03-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:34:20,344 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:20,344 - Inspection date 2024-03-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:34:20,344 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:20,345 - Inspection date 2024-03-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:34:20,345 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:20,345 - Inspection date 2024-03-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:34:20,345 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:33,533 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:34:33,536 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)
+2024-08-12 12:34:33,536 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-08-12T12:34:33.536433', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:33,537 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:34:33,537 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:34:33,537 - using serial LDA version on this node
+2024-08-12 12:34:33,538 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:34:33,538 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:34:33,542 - -8.173 per-word bound, 288.6 perplexity estimate based on a held-out corpus of 1 documents with 2620 words
+2024-08-12 12:34:33,542 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:34:33,543 - topic #0 (0.333): 0.012*"’" + 0.008*"Haringey" + 0.006*"well" + 0.006*"need" + 0.005*"good" + 0.005*"needs" + 0.005*"progress" + 0.005*"plans" + 0.004*"education" + 0.004*"24"
+2024-08-12 12:34:33,544 - topic #1 (0.333): 0.020*"’" + 0.009*"needs" + 0.009*"plans" + 0.008*"Haringey" + 0.006*"well" + 0.005*"good" + 0.005*"timely" + 0.005*"progress" + 0.005*"need" + 0.005*"supported"
+2024-08-12 12:34:33,544 - topic #2 (0.333): 0.013*"’" + 0.008*"Haringey" + 0.007*"needs" + 0.006*"plans" + 0.005*"good" + 0.005*"risk" + 0.004*"need" + 0.004*"well" + 0.004*"progress" + 0.004*"impact"
+2024-08-12 12:34:33,544 - topic diff=0.780095, rho=1.000000
+2024-08-12 12:34:33,544 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1252, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:34:33.544556', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:34,460 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:34:34,460 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:34,460 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:34:34,461 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:34,461 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:34:34,461 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:34,461 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:34:34,461 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:34,461 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:34:34,461 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:34,462 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:34:34,462 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:43,206 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:34:43,208 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)
+2024-08-12 12:34:43,208 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-08-12T12:34:43.208597', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:43,209 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:34:43,209 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:34:43,209 - using serial LDA version on this node
+2024-08-12 12:34:43,210 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:34:43,210 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:34:43,213 - -7.971 per-word bound, 250.9 perplexity estimate based on a held-out corpus of 1 documents with 1732 words
+2024-08-12 12:34:43,213 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:34:43,215 - topic #0 (0.333): 0.010*"good" + 0.009*"needs" + 0.009*"’" + 0.006*"well" + 0.005*"need" + 0.005*"experiences" + 0.005*"protection" + 0.005*"plans" + 0.004*"practice" + 0.004*"impact"
+2024-08-12 12:34:43,215 - topic #1 (0.333): 0.016*"’" + 0.009*"good" + 0.008*"well" + 0.008*"needs" + 0.005*"plans" + 0.005*"need" + 0.005*"early" + 0.005*"impact" + 0.005*"practice" + 0.004*"Harrow"
+2024-08-12 12:34:43,215 - topic #2 (0.333): 0.012*"good" + 0.009*"’" + 0.009*"well" + 0.007*"needs" + 0.007*"impact" + 0.006*"practice" + 0.005*"plans" + 0.005*"protection" + 0.004*"experiences" + 0.004*"need"
+2024-08-12 12:34:43,215 - topic diff=0.686844, rho=1.000000
+2024-08-12 12:34:43,215 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=942, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:34:43.215792', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:45,029 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:34:45,030 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:45,030 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:34:45,030 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:45,030 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:34:45,030 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:45,030 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:34:45,030 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:45,031 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:34:45,031 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:45,031 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:34:45,031 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:56,162 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:34:56,164 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)
+2024-08-12 12:34:56,164 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-08-12T12:34:56.164911', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:56,165 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:34:56,166 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:34:56,166 - using serial LDA version on this node
+2024-08-12 12:34:56,166 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:34:56,166 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:34:56,170 - -8.009 per-word bound, 257.6 perplexity estimate based on a held-out corpus of 1 documents with 2243 words
+2024-08-12 12:34:56,170 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:34:56,171 - topic #0 (0.333): 0.016*"’" + 0.012*"Havering" + 0.008*"quality" + 0.008*"plans" + 0.005*"effective" + 0.005*"oversight" + 0.005*"needs" + 0.004*"11" + 0.004*"December" + 0.004*"supported"
+2024-08-12 12:34:56,171 - topic #1 (0.333): 0.018*"’" + 0.012*"Havering" + 0.009*"quality" + 0.007*"plans" + 0.005*"effective" + 0.005*"oversight" + 0.005*"needs" + 0.005*"22" + 0.004*"11" + 0.004*"practice"
+2024-08-12 12:34:56,172 - topic #2 (0.333): 0.019*"’" + 0.009*"Havering" + 0.008*"quality" + 0.006*"plans" + 0.005*"oversight" + 0.005*"effective" + 0.005*"11" + 0.004*"2023" + 0.004*"practice" + 0.004*"needs"
+2024-08-12 12:34:56,172 - topic diff=0.763029, rho=1.000000
+2024-08-12 12:34:56,172 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:34:56.172266', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:34:57,112 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:34:57,112 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:57,112 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:34:57,112 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:57,112 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:34:57,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:57,113 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:34:57,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:57,113 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:34:57,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:34:57,113 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:34:57,113 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:08,534 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:35:08,536 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)
+2024-08-12 12:35:08,537 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-08-12T12:35:08.537039', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:08,538 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:35:08,538 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:35:08,538 - using serial LDA version on this node
+2024-08-12 12:35:08,538 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:35:08,538 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:35:08,542 - -8.078 per-word bound, 270.2 perplexity estimate based on a held-out corpus of 1 documents with 2511 words
+2024-08-12 12:35:08,542 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:35:08,544 - topic #0 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Hillingdon" + 0.006*"plans" + 0.004*"need" + 0.004*"team" + 0.004*"good" + 0.004*"2023" + 0.004*"supported"
+2024-08-12 12:35:08,544 - topic #1 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"plans" + 0.007*"needs" + 0.006*"Hillingdon" + 0.005*"need" + 0.004*"2" + 0.004*"family" + 0.004*"team" + 0.004*"6"
+2024-08-12 12:35:08,544 - topic #2 (0.333): 0.023*"’" + 0.012*"needs" + 0.009*"plans" + 0.009*"Hillingdon" + 0.008*"well" + 0.005*"team" + 0.005*"6" + 0.005*"October" + 0.005*"leaders" + 0.004*"2"
+2024-08-12 12:35:08,544 - topic diff=0.797676, rho=1.000000
+2024-08-12 12:35:08,544 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:35:08.544879', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:09,575 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:35:09,575 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:09,575 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:35:09,575 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:09,576 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:35:09,576 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:09,576 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:35:09,576 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:09,576 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:35:09,576 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:09,577 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:35:09,577 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:21,333 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:35:21,335 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)
+2024-08-12 12:35:21,335 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-08-12T12:35:21.335697', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:21,336 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:35:21,336 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:35:21,337 - using serial LDA version on this node
+2024-08-12 12:35:21,337 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:35:21,337 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:35:21,341 - -8.007 per-word bound, 257.2 perplexity estimate based on a held-out corpus of 1 documents with 2271 words
+2024-08-12 12:35:21,341 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:35:21,342 - topic #0 (0.333): 0.026*"’" + 0.013*"needs" + 0.009*"well" + 0.007*"Hounslow" + 0.006*"timely" + 0.005*"effective" + 0.005*"progress" + 0.005*"plans" + 0.005*"experiences" + 0.004*"October"
+2024-08-12 12:35:21,342 - topic #1 (0.333): 0.013*"’" + 0.009*"needs" + 0.008*"Hounslow" + 0.008*"well" + 0.007*"effective" + 0.005*"timely" + 0.004*"16" + 0.004*"plans" + 0.004*"strong" + 0.004*"20"
+2024-08-12 12:35:21,342 - topic #2 (0.333): 0.018*"’" + 0.012*"well" + 0.010*"needs" + 0.009*"effective" + 0.007*"timely" + 0.007*"plans" + 0.006*"Hounslow" + 0.005*"oversight" + 0.004*"strong" + 0.004*"experiences"
+2024-08-12 12:35:21,343 - topic diff=0.787519, rho=1.000000
+2024-08-12 12:35:21,343 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1070, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:35:21.343174', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:22,269 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:35:22,270 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:22,270 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:35:22,270 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:22,270 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:35:22,270 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:22,271 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:35:22,271 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:22,271 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:35:22,271 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:22,271 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:35:22,271 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:31,663 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:35:31,665 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)
+2024-08-12 12:35:31,665 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-08-12T12:35:31.665594', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:31,666 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:35:31,666 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:35:31,666 - using serial LDA version on this node
+2024-08-12 12:35:31,667 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:35:31,667 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:35:31,670 - -7.928 per-word bound, 243.5 perplexity estimate based on a held-out corpus of 1 documents with 1982 words
+2024-08-12 12:35:31,671 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:35:31,672 - topic #0 (0.333): 0.017*"’" + 0.013*"well" + 0.012*"needs" + 0.008*"plans" + 0.007*"highly" + 0.006*"good" + 0.006*"effective" + 0.006*"quality" + 0.005*"leaders" + 0.005*"risk"
+2024-08-12 12:35:31,672 - topic #1 (0.333): 0.011*"’" + 0.010*"needs" + 0.009*"well" + 0.006*"Islington" + 0.005*"quality" + 0.005*"good" + 0.005*"leaders" + 0.004*"highly" + 0.004*"school" + 0.004*"plans"
+2024-08-12 12:35:31,672 - topic #2 (0.333): 0.009*"needs" + 0.007*"well" + 0.007*"’" + 0.006*"plans" + 0.006*"highly" + 0.005*"good" + 0.005*"leaders" + 0.005*"quality" + 0.005*"effective" + 0.004*"risk"
+2024-08-12 12:35:31,672 - topic diff=0.756293, rho=1.000000
+2024-08-12 12:35:31,672 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:35:31.672966', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:33,667 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:35:33,667 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:33,668 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:35:33,668 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:33,668 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:35:33,668 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:33,668 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:35:33,668 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:33,668 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:35:33,669 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:33,669 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:35:33,669 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:45,455 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:35:45,456 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)
+2024-08-12 12:35:45,457 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-08-12T12:35:45.457033', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:45,457 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:35:45,458 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:35:45,458 - using serial LDA version on this node
+2024-08-12 12:35:45,458 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:35:45,458 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:35:45,462 - -7.906 per-word bound, 239.9 perplexity estimate based on a held-out corpus of 1 documents with 2090 words
+2024-08-12 12:35:45,462 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:35:45,463 - topic #0 (0.333): 0.020*"’" + 0.009*"well" + 0.009*"needs" + 0.008*"good" + 0.007*"plans" + 0.007*"progress" + 0.006*"need" + 0.006*"impact" + 0.006*"leaders" + 0.006*"Lambeth"
+2024-08-12 12:35:45,463 - topic #1 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"well" + 0.006*"good" + 0.006*"2022" + 0.006*"Lambeth" + 0.005*"4" + 0.005*"impact" + 0.005*"number"
+2024-08-12 12:35:45,463 - topic #2 (0.333): 0.011*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"Lambeth" + 0.006*"plans" + 0.005*"need" + 0.005*"good" + 0.005*"arrangements" + 0.005*"progress" + 0.005*"impact"
+2024-08-12 12:35:45,463 - topic diff=0.802509, rho=1.000000
+2024-08-12 12:35:45,464 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:35:45.464030', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:46,401 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:35:46,401 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:46,401 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:35:46,401 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:46,402 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:35:46,402 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:46,402 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:35:46,402 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:46,402 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:35:46,402 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:46,402 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:35:46,402 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:58,355 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:35:58,357 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)
+2024-08-12 12:35:58,357 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-08-12T12:35:58.357579', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:58,358 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:35:58,358 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:35:58,358 - using serial LDA version on this node
+2024-08-12 12:35:58,359 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:35:58,359 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:35:58,363 - -8.049 per-word bound, 264.8 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
+2024-08-12 12:35:58,363 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:35:58,365 - topic #0 (0.333): 0.019*"’" + 0.008*"needs" + 0.008*"well" + 0.007*"plans" + 0.006*"effective" + 0.006*"Lewisham" + 0.005*"progress" + 0.005*"arrangements" + 0.005*"4" + 0.005*"2023"
+2024-08-12 12:35:58,366 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"effective" + 0.007*"plans" + 0.006*"needs" + 0.005*"Lewisham" + 0.005*"leaders" + 0.005*"good" + 0.004*"arrangements" + 0.004*"progress"
+2024-08-12 12:35:58,366 - topic #2 (0.333): 0.018*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"Lewisham" + 0.006*"plans" + 0.006*"effective" + 0.005*"good" + 0.005*"progress" + 0.005*"4" + 0.004*"15"
+2024-08-12 12:35:58,366 - topic diff=0.768007, rho=1.000000
+2024-08-12 12:35:58,366 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:35:58.366955', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:35:59,275 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:35:59,276 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:59,276 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:35:59,276 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:59,276 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:35:59,276 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:59,276 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:35:59,276 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:59,277 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:35:59,277 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:35:59,277 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:35:59,277 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:08,977 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:36:08,994 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)
+2024-08-12 12:36:08,994 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-08-12T12:36:08.994293', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:08,998 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:36:08,998 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:36:08,999 - using serial LDA version on this node
+2024-08-12 12:36:08,999 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:36:08,999 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:36:09,008 - -7.990 per-word bound, 254.2 perplexity estimate based on a held-out corpus of 1 documents with 2032 words
+2024-08-12 12:36:09,008 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:36:09,017 - topic #0 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"family" + 0.005*"plans" + 0.005*"Merton" + 0.005*"health" + 0.005*"progress" + 0.004*"ensure" + 0.004*"information"
+2024-08-12 12:36:09,018 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.008*"Merton" + 0.006*"needs" + 0.005*"4" + 0.004*"good" + 0.004*"plans" + 0.004*"March" + 0.004*"family" + 0.004*"practice"
+2024-08-12 12:36:09,018 - topic #2 (0.333): 0.012*"’" + 0.006*"well" + 0.005*"Merton" + 0.004*"early" + 0.004*"progress" + 0.004*"needs" + 0.004*"plans" + 0.004*"good" + 0.004*"across" + 0.004*"2022"
+2024-08-12 12:36:09,018 - topic diff=0.757367, rho=1.000000
+2024-08-12 12:36:09,018 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1015, num_topics=3, decay=0.5, chunksize=2000> in 0.02s', 'datetime': '2024-08-12T12:36:09.018896', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:09,979 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:36:09,979 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:09,979 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:36:09,979 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:09,979 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:36:09,979 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:09,980 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:36:09,980 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:09,980 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:36:09,980 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:09,980 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:36:09,980 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:21,950 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:36:21,952 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)
+2024-08-12 12:36:21,952 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-08-12T12:36:21.952905', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:21,954 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:36:21,954 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:36:21,954 - using serial LDA version on this node
+2024-08-12 12:36:21,954 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:36:21,954 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:36:21,958 - -8.051 per-word bound, 265.3 perplexity estimate based on a held-out corpus of 1 documents with 2540 words
+2024-08-12 12:36:21,958 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:36:21,960 - topic #0 (0.333): 0.019*"’" + 0.008*"needs" + 0.006*"effective" + 0.006*"need" + 0.006*"Newham" + 0.006*"progress" + 0.006*"plans" + 0.005*"practice" + 0.005*"risks" + 0.004*"Leaders"
+2024-08-12 12:36:21,960 - topic #1 (0.333): 0.014*"’" + 0.006*"Newham" + 0.006*"need" + 0.006*"needs" + 0.005*"plans" + 0.005*"practice" + 0.005*"progress" + 0.004*"effective" + 0.004*"good" + 0.004*"18"
+2024-08-12 12:36:21,960 - topic #2 (0.333): 0.021*"’" + 0.009*"needs" + 0.008*"Newham" + 0.007*"practice" + 0.007*"progress" + 0.007*"plans" + 0.006*"good" + 0.006*"effective" + 0.005*"need" + 0.005*"18"
+2024-08-12 12:36:21,960 - topic diff=0.779122, rho=1.000000
+2024-08-12 12:36:21,960 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1153, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:36:21.960883', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:22,847 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:36:22,847 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:22,848 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:36:22,848 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:22,848 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:36:22,848 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:22,848 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:36:22,848 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:22,849 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:36:22,849 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:22,849 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:36:22,849 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:34,052 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:36:34,055 - built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)
+2024-08-12 12:36:34,056 - Dictionary lifecycle event {'msg': "built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-08-12T12:36:34.056171', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:34,057 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:36:34,058 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:36:34,058 - using serial LDA version on this node
+2024-08-12 12:36:34,059 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:36:34,059 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:36:34,066 - -8.165 per-word bound, 286.9 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
+2024-08-12 12:36:34,066 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:36:34,069 - topic #0 (0.333): 0.016*"’" + 0.007*"Redbridge" + 0.006*"family" + 0.006*"supported" + 0.005*"carers" + 0.005*"practice" + 0.005*"needs" + 0.005*"leaders" + 0.004*"protection" + 0.004*"14"
+2024-08-12 12:36:34,069 - topic #1 (0.333): 0.014*"’" + 0.007*"Redbridge" + 0.006*"needs" + 0.005*"practice" + 0.005*"carers" + 0.004*"leaders" + 0.004*"10" + 0.004*"supported" + 0.004*"plans" + 0.004*"risk"
+2024-08-12 12:36:34,069 - topic #2 (0.333): 0.013*"’" + 0.006*"Redbridge" + 0.005*"10" + 0.004*"family" + 0.004*"supported" + 0.004*"leaders" + 0.004*"early" + 0.004*"practice" + 0.004*"carers" + 0.004*"parents"
+2024-08-12 12:36:34,069 - topic diff=0.748697, rho=1.000000
+2024-08-12 12:36:34,069 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1204, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:36:34.069942', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:35,082 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:36:35,082 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:35,083 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:36:35,083 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:35,083 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:36:35,083 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:35,083 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:36:35,083 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:35,083 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:36:35,084 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:35,084 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:36:35,084 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:44,309 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:36:44,312 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)
+2024-08-12 12:36:44,312 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-08-12T12:36:44.312826', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:44,314 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:36:44,314 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:36:44,314 - using serial LDA version on this node
+2024-08-12 12:36:44,315 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:36:44,315 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:36:44,321 - -7.987 per-word bound, 253.7 perplexity estimate based on a held-out corpus of 1 documents with 1818 words
+2024-08-12 12:36:44,321 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:36:44,324 - topic #0 (0.333): 0.012*"’" + 0.010*"well" + 0.007*"needs" + 0.006*"Richmond" + 0.006*"ensure" + 0.006*"supported" + 0.005*"good" + 0.004*"strong" + 0.004*"team" + 0.004*"need"
+2024-08-12 12:36:44,324 - topic #1 (0.333): 0.017*"’" + 0.013*"well" + 0.008*"needs" + 0.007*"team" + 0.007*"Richmond" + 0.006*"supported" + 0.006*"good" + 0.006*"need" + 0.005*"additional" + 0.004*"upon"
+2024-08-12 12:36:44,324 - topic #2 (0.333): 0.017*"’" + 0.011*"Richmond" + 0.009*"well" + 0.007*"needs" + 0.006*"need" + 0.005*"good" + 0.005*"supported" + 0.005*"strong" + 0.005*"team" + 0.005*"4"
+2024-08-12 12:36:44,324 - topic diff=0.731064, rho=1.000000
+2024-08-12 12:36:44,324 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:36:44.324948', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:45,267 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:36:45,267 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:45,268 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:36:45,268 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:45,268 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:36:45,268 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:45,268 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:36:45,268 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:45,269 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:36:45,269 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:45,269 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:36:45,269 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:55,426 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:36:55,427 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)
+2024-08-12 12:36:55,428 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-08-12T12:36:55.428128', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:55,429 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:36:55,429 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:36:55,429 - using serial LDA version on this node
+2024-08-12 12:36:55,429 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:36:55,429 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:36:55,433 - -7.924 per-word bound, 242.9 perplexity estimate based on a held-out corpus of 1 documents with 1878 words
+2024-08-12 12:36:55,433 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:36:55,434 - topic #0 (0.333): 0.017*"’" + 0.010*"Southwark" + 0.009*"well" + 0.008*"good" + 0.006*"plans" + 0.006*"need" + 0.006*"needs" + 0.005*"strong" + 0.005*"progress" + 0.005*"effective"
+2024-08-12 12:36:55,434 - topic #1 (0.333): 0.015*"’" + 0.009*"Southwark" + 0.008*"good" + 0.008*"needs" + 0.006*"well" + 0.006*"effective" + 0.005*"need" + 0.005*"receive" + 0.005*"Leaders" + 0.005*"quality"
+2024-08-12 12:36:55,435 - topic #2 (0.333): 0.021*"’" + 0.009*"Southwark" + 0.008*"needs" + 0.008*"good" + 0.007*"well" + 0.007*"progress" + 0.006*"strong" + 0.005*"leaders" + 0.005*"plans" + 0.005*"Leaders"
+2024-08-12 12:36:55,435 - topic diff=0.733880, rho=1.000000
+2024-08-12 12:36:55,435 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=945, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:36:55.435398', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:36:56,294 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:36:56,295 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:56,295 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:36:56,295 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:56,295 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:36:56,295 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:56,295 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:36:56,296 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:56,296 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:36:56,296 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:36:56,296 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:36:56,296 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:05,432 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:37:05,435 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)
+2024-08-12 12:37:05,436 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-08-12T12:37:05.436844', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:05,438 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:37:05,438 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:37:05,438 - using serial LDA version on this node
+2024-08-12 12:37:05,439 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:37:05,439 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:37:05,446 - -7.989 per-word bound, 254.1 perplexity estimate based on a held-out corpus of 1 documents with 1847 words
+2024-08-12 12:37:05,446 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:37:05,448 - topic #0 (0.333): 0.020*"’" + 0.008*"well" + 0.006*"Sutton" + 0.006*"needs" + 0.005*"progress" + 0.005*"receive" + 0.004*"‘" + 0.004*"understand" + 0.004*"December" + 0.004*"effective"
+2024-08-12 12:37:05,449 - topic #1 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"Sutton" + 0.005*"well" + 0.005*"effective" + 0.004*"receive" + 0.004*"progress" + 0.004*"6" + 0.004*"supported" + 0.004*"good"
+2024-08-12 12:37:05,449 - topic #2 (0.333): 0.017*"’" + 0.006*"good" + 0.006*"well" + 0.006*"needs" + 0.005*"Sutton" + 0.005*"effective" + 0.005*"progress" + 0.005*"6" + 0.005*"10" + 0.005*"2021"
+2024-08-12 12:37:05,449 - topic diff=0.729479, rho=1.000000
+2024-08-12 12:37:05,449 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:37:05.449695', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:07,191 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:37:07,191 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:07,191 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:37:07,192 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:07,192 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:37:07,192 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:07,192 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:37:07,192 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:07,192 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:37:07,192 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:07,193 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:37:07,193 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:18,240 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:37:18,242 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)
+2024-08-12 12:37:18,242 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-08-12T12:37:18.242622', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:18,243 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:37:18,243 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:37:18,244 - using serial LDA version on this node
+2024-08-12 12:37:18,244 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:37:18,244 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:37:18,248 - -8.130 per-word bound, 280.1 perplexity estimate based on a held-out corpus of 1 documents with 2465 words
+2024-08-12 12:37:18,248 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:37:18,250 - topic #0 (0.333): 0.013*"’" + 0.006*"good" + 0.006*"effective" + 0.005*"plans" + 0.005*"risk" + 0.005*"need" + 0.004*"‘" + 0.004*"practice" + 0.004*"well" + 0.004*"impact"
+2024-08-12 12:37:18,250 - topic #1 (0.333): 0.019*"’" + 0.008*"good" + 0.007*"practice" + 0.007*"plans" + 0.007*"effective" + 0.007*"‘" + 0.007*"well" + 0.006*"progress" + 0.006*"early" + 0.005*"needs"
+2024-08-12 12:37:18,250 - topic #2 (0.333): 0.009*"’" + 0.005*"plans" + 0.005*"effective" + 0.005*"good" + 0.005*"well" + 0.005*"‘" + 0.004*"need" + 0.004*"education" + 0.004*"including" + 0.004*"early"
+2024-08-12 12:37:18,250 - topic diff=0.789461, rho=1.000000
+2024-08-12 12:37:18,250 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1194, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:37:18.250614', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:19,160 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:37:19,160 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:19,161 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:37:19,161 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:19,161 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:37:19,161 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:19,161 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:37:19,161 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:19,162 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:37:19,162 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:19,162 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:37:19,162 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:29,565 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:37:29,567 - built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
+2024-08-12 12:37:29,567 - Dictionary lifecycle event {'msg': "built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-08-12T12:37:29.567879', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:29,568 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:37:29,568 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:37:29,569 - using serial LDA version on this node
+2024-08-12 12:37:29,569 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:37:29,569 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:37:29,573 - -7.972 per-word bound, 251.0 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
+2024-08-12 12:37:29,573 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:37:29,574 - topic #0 (0.333): 0.016*"’" + 0.012*"well" + 0.011*"needs" + 0.010*"good" + 0.008*"effective" + 0.007*"need" + 0.006*"plans" + 0.005*"timely" + 0.005*"ensure" + 0.005*"clear"
+2024-08-12 12:37:29,574 - topic #1 (0.333): 0.012*"’" + 0.011*"well" + 0.008*"needs" + 0.007*"good" + 0.006*"effective" + 0.005*"plans" + 0.005*"need" + 0.004*"information" + 0.004*"timely" + 0.004*"protection"
+2024-08-12 12:37:29,574 - topic #2 (0.333): 0.015*"’" + 0.011*"well" + 0.007*"good" + 0.007*"effective" + 0.007*"needs" + 0.006*"need" + 0.005*"risk" + 0.004*"timely" + 0.004*"plans" + 0.004*"actions"
+2024-08-12 12:37:29,575 - topic diff=0.784949, rho=1.000000
+2024-08-12 12:37:29,575 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1036, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:37:29.575152', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:30,565 - Inspection date 2019-01-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:37:30,566 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:30,566 - Inspection date 2019-01-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:37:30,566 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:30,566 - Inspection date 2019-01-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:37:30,566 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:30,567 - Inspection date 2019-01-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:37:30,567 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:30,567 - Inspection date 2019-01-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:37:30,567 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:30,567 - Inspection date 2019-01-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:37:30,567 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:39,546 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:37:39,547 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)
+2024-08-12 12:37:39,548 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-08-12T12:37:39.548033', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:39,548 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:37:39,549 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:37:39,549 - using serial LDA version on this node
+2024-08-12 12:37:39,549 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:37:39,549 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:37:39,552 - -7.853 per-word bound, 231.2 perplexity estimate based on a held-out corpus of 1 documents with 1772 words
+2024-08-12 12:37:39,552 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:37:39,554 - topic #0 (0.333): 0.010*"’" + 0.005*"practice" + 0.005*"well" + 0.005*"supported" + 0.004*"needs" + 0.004*"protection" + 0.004*"good" + 0.004*"team" + 0.004*"Wandsworth" + 0.004*"quality"
+2024-08-12 12:37:39,554 - topic #1 (0.333): 0.014*"’" + 0.006*"well" + 0.006*"progress" + 0.005*"protection" + 0.005*"practice" + 0.005*"needs" + 0.005*"Wandsworth" + 0.005*"7" + 0.005*"receive" + 0.005*"effective"
+2024-08-12 12:37:39,554 - topic #2 (0.333): 0.011*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"Senior" + 0.006*"progress" + 0.006*"ensure" + 0.005*"Wandsworth" + 0.005*"quality" + 0.005*"18" + 0.005*"effective"
+2024-08-12 12:37:39,554 - topic diff=0.759462, rho=1.000000
+2024-08-12 12:37:39,554 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=884, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:37:39.554772', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:40,492 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:37:40,492 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:40,492 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:37:40,492 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:40,492 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:37:40,492 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:40,493 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:37:40,493 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:40,493 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:37:40,493 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:40,493 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:37:40,493 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:50,003 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:37:50,006 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)
+2024-08-12 12:37:50,007 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-08-12T12:37:50.007014', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:50,008 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:37:50,008 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:37:50,009 - using serial LDA version on this node
+2024-08-12 12:37:50,009 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:37:50,010 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:37:50,016 - -8.155 per-word bound, 285.0 perplexity estimate based on a held-out corpus of 1 documents with 2101 words
+2024-08-12 12:37:50,017 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:37:50,019 - topic #0 (0.333): 0.010*"’" + 0.007*"practice" + 0.006*"needs" + 0.005*"highly" + 0.005*"well" + 0.004*"across" + 0.004*"skilled" + 0.004*"direct" + 0.003*"many" + 0.003*"supported"
+2024-08-12 12:37:50,019 - topic #1 (0.333): 0.012*"’" + 0.006*"needs" + 0.005*"practice" + 0.005*"highly" + 0.004*"many" + 0.004*"well" + 0.004*"family" + 0.003*"across" + 0.003*"high" + 0.003*"shared"
+2024-08-12 12:37:50,020 - topic #2 (0.333): 0.016*"’" + 0.007*"practice" + 0.007*"highly" + 0.006*"well" + 0.006*"needs" + 0.004*"across" + 0.004*"many" + 0.003*"family" + 0.003*"plans" + 0.003*"Westminster"
+2024-08-12 12:37:50,020 - topic diff=0.692893, rho=1.000000
+2024-08-12 12:37:50,020 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1136, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:37:50.020516', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:37:51,284 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:37:51,284 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:51,284 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:37:51,285 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:51,285 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:37:51,285 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:51,285 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:37:51,285 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:51,285 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:37:51,286 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:37:51,286 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:37:51,286 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:03,545 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:38:03,547 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)
+2024-08-12 12:38:03,547 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-08-12T12:38:03.547887', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:03,549 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:38:03,549 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:38:03,549 - using serial LDA version on this node
+2024-08-12 12:38:03,549 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:38:03,549 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:38:03,553 - -8.106 per-word bound, 275.5 perplexity estimate based on a held-out corpus of 1 documents with 2593 words
+2024-08-12 12:38:03,553 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:38:03,555 - topic #0 (0.333): 0.017*"’" + 0.007*"need" + 0.006*"needs" + 0.006*"plans" + 0.006*"effective" + 0.005*"good" + 0.005*"impact" + 0.005*"progress" + 0.005*"well" + 0.005*"quality"
+2024-08-12 12:38:03,555 - topic #1 (0.333): 0.015*"’" + 0.007*"Luton" + 0.006*"need" + 0.005*"2022" + 0.005*"quality" + 0.005*"good" + 0.005*"needs" + 0.005*"impact" + 0.005*"receive" + 0.004*"effective"
+2024-08-12 12:38:03,555 - topic #2 (0.333): 0.018*"’" + 0.007*"plans" + 0.007*"needs" + 0.006*"Luton" + 0.006*"need" + 0.006*"effective" + 0.005*"ensure" + 0.005*"progress" + 0.005*"Leaders" + 0.005*"good"
+2024-08-12 12:38:03,555 - topic diff=0.790933, rho=1.000000
+2024-08-12 12:38:03,556 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1199, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:38:03.556031', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:04,581 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:38:04,581 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:04,582 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:38:04,582 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:04,582 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:38:04,582 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:04,582 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:38:04,582 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:04,583 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:38:04,583 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:04,583 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:38:04,583 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:13,746 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:38:13,748 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)
+2024-08-12 12:38:13,748 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-08-12T12:38:13.748630', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:13,749 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:38:13,749 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:38:13,749 - using serial LDA version on this node
+2024-08-12 12:38:13,750 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:38:13,750 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:38:13,753 - -7.774 per-word bound, 218.8 perplexity estimate based on a held-out corpus of 1 documents with 1938 words
+2024-08-12 12:38:13,753 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:38:13,754 - topic #0 (0.333): 0.019*"’" + 0.012*"Manchester" + 0.011*"needs" + 0.009*"well" + 0.006*"effective" + 0.006*"always" + 0.006*"plans" + 0.006*"supported" + 0.006*"protection" + 0.005*"progress"
+2024-08-12 12:38:13,754 - topic #1 (0.333): 0.028*"’" + 0.009*"Manchester" + 0.008*"needs" + 0.008*"supported" + 0.006*"always" + 0.006*"well" + 0.006*"disabled" + 0.005*"education" + 0.005*"family" + 0.005*"plans"
+2024-08-12 12:38:13,755 - topic #2 (0.333): 0.015*"’" + 0.009*"Manchester" + 0.008*"needs" + 0.007*"always" + 0.006*"supported" + 0.005*"education" + 0.005*"plans" + 0.005*"protection" + 0.005*"quality" + 0.005*"well"
+2024-08-12 12:38:13,755 - topic diff=0.813708, rho=1.000000
+2024-08-12 12:38:13,755 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=871, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:38:13.755363', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:14,600 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:38:14,600 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:14,600 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:38:14,600 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:14,601 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:38:14,601 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:14,601 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:38:14,601 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:14,601 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:38:14,601 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:14,602 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:38:14,602 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:24,631 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:38:24,634 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)
+2024-08-12 12:38:24,634 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-08-12T12:38:24.634760', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:24,636 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:38:24,636 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:38:24,636 - using serial LDA version on this node
+2024-08-12 12:38:24,637 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:38:24,637 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:38:24,640 - -7.895 per-word bound, 238.0 perplexity estimate based on a held-out corpus of 1 documents with 1857 words
+2024-08-12 12:38:24,640 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:38:24,642 - topic #0 (0.333): 0.014*"’" + 0.009*"Medway" + 0.009*"well" + 0.007*"quality" + 0.006*"practice" + 0.006*"needs" + 0.005*"risk" + 0.005*"impact" + 0.005*"leaders" + 0.005*"oversight"
+2024-08-12 12:38:24,642 - topic #1 (0.333): 0.020*"’" + 0.009*"Medway" + 0.009*"practice" + 0.008*"quality" + 0.007*"well" + 0.007*"leaders" + 0.007*"needs" + 0.007*"oversight" + 0.006*"experiences" + 0.006*"good"
+2024-08-12 12:38:24,642 - topic #2 (0.333): 0.012*"’" + 0.009*"Medway" + 0.008*"practice" + 0.007*"quality" + 0.006*"well" + 0.006*"leaders" + 0.006*"impact" + 0.005*"oversight" + 0.005*"needs" + 0.005*"good"
+2024-08-12 12:38:24,642 - topic diff=0.760605, rho=1.000000
+2024-08-12 12:38:24,642 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=922, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:38:24.642956', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:25,568 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:38:25,568 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:25,568 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:38:25,569 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:25,569 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:38:25,569 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:25,569 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:38:25,569 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:25,569 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:38:25,569 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:25,570 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:38:25,570 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:38,387 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:38:38,389 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)
+2024-08-12 12:38:38,390 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-08-12T12:38:38.390010', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:38,391 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:38:38,391 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:38:38,391 - using serial LDA version on this node
+2024-08-12 12:38:38,391 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:38:38,391 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:38:38,395 - -7.995 per-word bound, 255.1 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
+2024-08-12 12:38:38,395 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:38:38,396 - topic #0 (0.333): 0.012*"’" + 0.007*"Middlesbrough" + 0.007*"plans" + 0.007*"well" + 0.006*"effective" + 0.005*"progress" + 0.005*"needs" + 0.005*"13" + 0.005*"24" + 0.004*"place"
+2024-08-12 12:38:38,397 - topic #1 (0.333): 0.014*"’" + 0.007*"effective" + 0.007*"needs" + 0.006*"plans" + 0.006*"Middlesbrough" + 0.005*"practice" + 0.005*"well" + 0.005*"progress" + 0.005*"good" + 0.004*"impact"
+2024-08-12 12:38:38,397 - topic #2 (0.333): 0.014*"’" + 0.007*"plans" + 0.007*"effective" + 0.007*"well" + 0.007*"Middlesbrough" + 0.006*"practice" + 0.006*"needs" + 0.005*"place" + 0.005*"progress" + 0.005*"24"
+2024-08-12 12:38:38,397 - topic diff=0.779946, rho=1.000000
+2024-08-12 12:38:38,397 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1068, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:38:38.397594', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:39,337 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:38:39,338 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:39,338 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:38:39,338 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:39,338 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:38:39,338 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:39,339 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:38:39,339 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:39,339 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:38:39,339 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:39,339 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:38:39,339 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:50,426 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:38:50,429 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)
+2024-08-12 12:38:50,429 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-08-12T12:38:50.429199', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:50,430 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:38:50,430 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:38:50,430 - using serial LDA version on this node
+2024-08-12 12:38:50,431 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:38:50,431 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:38:50,434 - -8.035 per-word bound, 262.3 perplexity estimate based on a held-out corpus of 1 documents with 2328 words
+2024-08-12 12:38:50,434 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:38:50,436 - topic #0 (0.333): 0.015*"’" + 0.007*"Keynes" + 0.007*"Milton" + 0.006*"well" + 0.005*"need" + 0.005*"good" + 0.004*"practice" + 0.004*"education" + 0.004*"October" + 0.004*"2021"
+2024-08-12 12:38:50,436 - topic #1 (0.333): 0.012*"’" + 0.005*"practice" + 0.005*"Keynes" + 0.004*"plans" + 0.004*"Milton" + 0.004*"need" + 0.004*"well" + 0.004*"family" + 0.004*"education" + 0.004*"leaders"
+2024-08-12 12:38:50,436 - topic #2 (0.333): 0.017*"’" + 0.006*"well" + 0.006*"Milton" + 0.006*"Keynes" + 0.006*"need" + 0.006*"25" + 0.005*"leaders" + 0.005*"practice" + 0.005*"good" + 0.005*"team"
+2024-08-12 12:38:50,436 - topic diff=0.782105, rho=1.000000
+2024-08-12 12:38:50,436 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1101, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:38:50.436894', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:38:51,334 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:38:51,334 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:51,334 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:38:51,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:51,335 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:38:51,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:51,335 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:38:51,335 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:51,335 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:38:51,336 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:38:51,336 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:38:51,336 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:01,587 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:39:01,589 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)
+2024-08-12 12:39:01,589 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-08-12T12:39:01.589175', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:01,590 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:39:01,590 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:39:01,590 - using serial LDA version on this node
+2024-08-12 12:39:01,590 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:39:01,590 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:39:01,594 - -7.882 per-word bound, 235.9 perplexity estimate based on a held-out corpus of 1 documents with 2076 words
+2024-08-12 12:39:01,594 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:39:01,595 - topic #0 (0.333): 0.012*"’" + 0.009*"plans" + 0.007*"needs" + 0.007*"good" + 0.006*"well" + 0.006*"protection" + 0.005*"need" + 0.005*"making" + 0.005*"ensure" + 0.005*"Newcastle"
+2024-08-12 12:39:01,595 - topic #1 (0.333): 0.019*"’" + 0.010*"plans" + 0.009*"Newcastle" + 0.008*"protection" + 0.007*"well" + 0.006*"progress" + 0.006*"good" + 0.006*"needs" + 0.005*"need" + 0.005*"making"
+2024-08-12 12:39:01,596 - topic #2 (0.333): 0.016*"’" + 0.012*"plans" + 0.010*"needs" + 0.007*"good" + 0.006*"progress" + 0.006*"Newcastle" + 0.006*"ensure" + 0.006*"making" + 0.006*"management" + 0.005*"protection"
+2024-08-12 12:39:01,596 - topic diff=0.786083, rho=1.000000
+2024-08-12 12:39:01,596 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=956, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:39:01.596301', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:02,510 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:39:02,510 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:02,510 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:39:02,511 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:02,511 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:39:02,511 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:02,511 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:39:02,512 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:02,512 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:39:02,512 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:02,512 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:39:02,512 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:14,385 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:39:14,388 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)
+2024-08-12 12:39:14,388 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-08-12T12:39:14.388322', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:14,389 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:39:14,389 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:39:14,389 - using serial LDA version on this node
+2024-08-12 12:39:14,390 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:39:14,390 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:39:14,394 - -8.122 per-word bound, 278.6 perplexity estimate based on a held-out corpus of 1 documents with 2655 words
+2024-08-12 12:39:14,394 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:39:14,395 - topic #0 (0.333): 0.012*"’" + 0.009*"well" + 0.008*"Norfolk" + 0.006*"carers" + 0.006*"needs" + 0.005*"practice" + 0.004*"7" + 0.004*"including" + 0.004*"plans" + 0.004*"supported"
+2024-08-12 12:39:14,396 - topic #1 (0.333): 0.022*"’" + 0.008*"Norfolk" + 0.006*"well" + 0.006*"supported" + 0.006*"practice" + 0.006*"carers" + 0.005*"plans" + 0.005*"leaders" + 0.005*"needs" + 0.005*"18"
+2024-08-12 12:39:14,396 - topic #2 (0.333): 0.016*"’" + 0.009*"well" + 0.007*"Norfolk" + 0.006*"needs" + 0.006*"carers" + 0.005*"practice" + 0.005*"supported" + 0.004*"range" + 0.004*"family" + 0.004*"leaders"
+2024-08-12 12:39:14,396 - topic diff=0.778919, rho=1.000000
+2024-08-12 12:39:14,396 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1221, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:39:14.396560', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:15,388 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:39:15,389 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:15,389 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:39:15,389 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:15,389 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:39:15,389 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:15,389 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:39:15,390 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:15,390 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:39:15,390 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:15,390 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:39:15,390 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:25,885 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:39:25,887 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)
+2024-08-12 12:39:25,887 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-08-12T12:39:25.887453', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:25,888 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:39:25,888 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:39:25,888 - using serial LDA version on this node
+2024-08-12 12:39:25,889 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:39:25,889 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:39:25,892 - -7.888 per-word bound, 237.0 perplexity estimate based on a held-out corpus of 1 documents with 2045 words
+2024-08-12 12:39:25,892 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:39:25,893 - topic #0 (0.333): 0.013*"’" + 0.008*"leaders" + 0.007*"practice" + 0.007*"needs" + 0.006*"planning" + 0.006*"many" + 0.006*"risk" + 0.005*"2021" + 0.005*"Lincolnshire" + 0.005*"quality"
+2024-08-12 12:39:25,893 - topic #1 (0.333): 0.016*"’" + 0.008*"risk" + 0.007*"practice" + 0.006*"leaders" + 0.005*"planning" + 0.005*"needs" + 0.005*"need" + 0.005*"quality" + 0.005*"East" + 0.004*"many"
+2024-08-12 12:39:25,893 - topic #2 (0.333): 0.014*"’" + 0.009*"practice" + 0.006*"planning" + 0.006*"needs" + 0.006*"risk" + 0.006*"need" + 0.005*"leaders" + 0.005*"2021" + 0.005*"North" + 0.005*"plans"
+2024-08-12 12:39:25,894 - topic diff=0.768907, rho=1.000000
+2024-08-12 12:39:25,894 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=958, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:39:25.894232', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:26,883 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:39:26,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:26,884 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:39:26,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:26,884 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:39:26,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:26,884 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:39:26,884 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:26,885 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:39:26,885 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:26,885 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:39:26,885 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:36,961 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:39:36,965 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)
+2024-08-12 12:39:36,965 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-08-12T12:39:36.965580', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:36,967 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:39:36,967 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:39:36,967 - using serial LDA version on this node
+2024-08-12 12:39:36,968 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:39:36,968 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:39:36,975 - -8.068 per-word bound, 268.4 perplexity estimate based on a held-out corpus of 1 documents with 2174 words
+2024-08-12 12:39:36,975 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:39:36,978 - topic #0 (0.333): 0.023*"’" + 0.007*"family" + 0.007*"Lincolnshire" + 0.007*"‘" + 0.006*"approach" + 0.006*"North" + 0.005*"need" + 0.005*"10" + 0.005*"14" + 0.005*"leaders"
+2024-08-12 12:39:36,978 - topic #1 (0.333): 0.019*"’" + 0.008*"‘" + 0.005*"North" + 0.005*"well" + 0.005*"10" + 0.005*"family" + 0.005*"leaders" + 0.004*"Lincolnshire" + 0.004*"need" + 0.004*"protection"
+2024-08-12 12:39:36,978 - topic #2 (0.333): 0.018*"’" + 0.007*"‘" + 0.006*"well" + 0.005*"leaders" + 0.005*"protection" + 0.005*"family" + 0.005*"approach" + 0.004*"council" + 0.004*"Lincolnshire" + 0.004*"North"
+2024-08-12 12:39:36,979 - topic diff=0.756710, rho=1.000000
+2024-08-12 12:39:36,979 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:39:36.979222', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:37,959 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:39:37,959 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:37,959 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:39:37,959 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:37,960 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:39:37,960 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:37,960 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:39:37,960 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:37,960 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:39:37,960 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:37,960 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:39:37,961 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:48,345 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:39:48,347 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)
+2024-08-12 12:39:48,348 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-08-12T12:39:48.347997', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:48,348 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:39:48,349 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:39:48,349 - using serial LDA version on this node
+2024-08-12 12:39:48,349 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:39:48,349 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:39:48,353 - -8.034 per-word bound, 262.1 perplexity estimate based on a held-out corpus of 1 documents with 2204 words
+2024-08-12 12:39:48,353 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:39:48,355 - topic #0 (0.333): 0.020*"’" + 0.008*"North" + 0.007*"Northamptonshire" + 0.007*"well" + 0.006*"quality" + 0.005*"plans" + 0.005*"NCT" + 0.005*"Leaders" + 0.005*"3" + 0.005*"e"
+2024-08-12 12:39:48,355 - topic #1 (0.333): 0.015*"’" + 0.008*"Northamptonshire" + 0.006*"well" + 0.006*"North" + 0.006*"NCT" + 0.005*"practice" + 0.005*"quality" + 0.005*"3" + 0.005*"impact" + 0.005*"Leaders"
+2024-08-12 12:39:48,355 - topic #2 (0.333): 0.015*"’" + 0.009*"Northamptonshire" + 0.006*"need" + 0.005*"North" + 0.005*"needs" + 0.005*"well" + 0.005*"quality" + 0.005*"practice" + 0.005*"impact" + 0.005*"October"
+2024-08-12 12:39:48,355 - topic diff=0.744804, rho=1.000000
+2024-08-12 12:39:48,355 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:39:48.355685', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:39:49,390 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:39:49,390 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:49,390 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:39:49,390 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:49,391 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:39:49,391 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:49,391 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:39:49,391 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:49,391 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:39:49,391 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:39:49,391 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:39:49,392 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:02,080 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:40:02,082 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)
+2024-08-12 12:40:02,083 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-08-12T12:40:02.083091', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:02,084 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:40:02,084 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:40:02,084 - using serial LDA version on this node
+2024-08-12 12:40:02,085 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:40:02,085 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:40:02,089 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2902 words
+2024-08-12 12:40:02,089 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:40:02,090 - topic #0 (0.333): 0.020*"’" + 0.008*"quality" + 0.007*"needs" + 0.006*"number" + 0.006*"practice" + 0.005*"always" + 0.005*"plans" + 0.005*"Somerset" + 0.005*"risk" + 0.005*"experienced"
+2024-08-12 12:40:02,090 - topic #1 (0.333): 0.013*"’" + 0.007*"always" + 0.006*"quality" + 0.006*"Somerset" + 0.006*"North" + 0.006*"needs" + 0.005*"risk" + 0.005*"progress" + 0.005*"need" + 0.004*"experienced"
+2024-08-12 12:40:02,091 - topic #2 (0.333): 0.017*"’" + 0.007*"quality" + 0.007*"needs" + 0.006*"North" + 0.006*"practice" + 0.006*"progress" + 0.006*"Somerset" + 0.006*"always" + 0.005*"number" + 0.005*"need"
+2024-08-12 12:40:02,091 - topic diff=0.828252, rho=1.000000
+2024-08-12 12:40:02,091 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1219, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:40:02.091348', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:03,857 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:40:03,857 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:03,857 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:40:03,858 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:03,858 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:40:03,858 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:03,858 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:40:03,859 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:03,859 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:40:03,859 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:03,859 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:40:03,859 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:15,613 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:40:15,615 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)
+2024-08-12 12:40:15,616 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-08-12T12:40:15.616159', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:15,617 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:40:15,617 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:40:15,617 - using serial LDA version on this node
+2024-08-12 12:40:15,618 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:40:15,618 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:40:15,622 - -8.224 per-word bound, 298.9 perplexity estimate based on a held-out corpus of 1 documents with 2518 words
+2024-08-12 12:40:15,622 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:40:15,624 - topic #0 (0.333): 0.019*"’" + 0.008*"leaders" + 0.007*"well" + 0.005*"needs" + 0.005*"make" + 0.005*"quality" + 0.004*"need" + 0.004*"good" + 0.004*"impact" + 0.003*"family"
+2024-08-12 12:40:15,624 - topic #1 (0.333): 0.013*"’" + 0.006*"well" + 0.006*"need" + 0.005*"impact" + 0.004*"make" + 0.004*"protection" + 0.004*"needs" + 0.004*"early" + 0.003*"leaders" + 0.003*"foster"
+2024-08-12 12:40:15,624 - topic #2 (0.333): 0.016*"’" + 0.006*"well" + 0.005*"need" + 0.005*"quality" + 0.004*"leaders" + 0.004*"make" + 0.004*"early" + 0.004*"needs" + 0.004*"clear" + 0.004*"impact"
+2024-08-12 12:40:15,624 - topic diff=0.735173, rho=1.000000
+2024-08-12 12:40:15,624 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1273, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:40:15.624791', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:16,668 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:40:16,668 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:16,668 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:40:16,668 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:16,669 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:40:16,669 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:16,669 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:40:16,669 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:16,669 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:40:16,669 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:16,670 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:40:16,670 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:29,170 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:40:29,174 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)
+2024-08-12 12:40:29,175 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-08-12T12:40:29.175029', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:29,177 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:40:29,177 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:40:29,177 - using serial LDA version on this node
+2024-08-12 12:40:29,178 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:40:29,178 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:40:29,185 - -8.143 per-word bound, 282.6 perplexity estimate based on a held-out corpus of 1 documents with 2759 words
+2024-08-12 12:40:29,185 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:40:29,187 - topic #0 (0.333): 0.020*"’" + 0.009*"needs" + 0.008*"North" + 0.008*"Yorkshire" + 0.007*"well" + 0.006*"family" + 0.005*"practice" + 0.004*"planning" + 0.004*"‘" + 0.004*"3"
+2024-08-12 12:40:29,188 - topic #1 (0.333): 0.010*"’" + 0.009*"well" + 0.005*"‘" + 0.005*"practice" + 0.004*"family" + 0.004*"North" + 0.004*"3" + 0.004*"7" + 0.003*"supported" + 0.003*"Yorkshire"
+2024-08-12 12:40:29,188 - topic #2 (0.333): 0.026*"’" + 0.008*"well" + 0.007*"practice" + 0.006*"family" + 0.006*"North" + 0.006*"Yorkshire" + 0.005*"‘" + 0.005*"3" + 0.004*"2023" + 0.004*"7"
+2024-08-12 12:40:29,188 - topic diff=0.812523, rho=1.000000
+2024-08-12 12:40:29,188 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1259, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:40:29.188841', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:30,479 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:40:30,479 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:30,479 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:40:30,479 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:30,479 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:40:30,480 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:30,480 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:40:30,480 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:30,480 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:40:30,480 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:30,480 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:40:30,481 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:44,603 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:40:44,606 - built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)
+2024-08-12 12:40:44,606 - Dictionary lifecycle event {'msg': "built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)", 'datetime': '2024-08-12T12:40:44.606467', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:44,607 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:40:44,607 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:40:44,608 - using serial LDA version on this node
+2024-08-12 12:40:44,608 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:40:44,608 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:40:44,612 - -8.070 per-word bound, 268.7 perplexity estimate based on a held-out corpus of 1 documents with 2884 words
+2024-08-12 12:40:44,612 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:40:44,614 - topic #0 (0.333): 0.019*"’" + 0.007*"needs" + 0.007*"family" + 0.007*"experiences" + 0.006*"well" + 0.006*"progress" + 0.006*"strong" + 0.006*"leaders" + 0.005*"Northumberland" + 0.005*"effective"
+2024-08-12 12:40:44,614 - topic #1 (0.333): 0.020*"’" + 0.009*"family" + 0.008*"leaders" + 0.007*"strong" + 0.006*"needs" + 0.006*"experiences" + 0.006*"Northumberland" + 0.005*"well" + 0.005*"within" + 0.005*"plans"
+2024-08-12 12:40:44,614 - topic #2 (0.333): 0.015*"’" + 0.007*"family" + 0.006*"strong" + 0.005*"needs" + 0.005*"practice" + 0.005*"leaders" + 0.005*"well" + 0.005*"experiences" + 0.004*"Northumberland" + 0.004*"within"
+2024-08-12 12:40:44,614 - topic diff=0.845240, rho=1.000000
+2024-08-12 12:40:44,614 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1218, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:40:44.614869', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:45,594 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:40:45,594 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:45,594 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:40:45,594 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:45,595 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:40:45,595 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:45,595 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:40:45,595 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:45,595 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:40:45,595 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:45,595 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:40:45,596 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:57,398 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:40:57,400 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
+2024-08-12 12:40:57,400 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-08-12T12:40:57.400452', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:57,401 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:40:57,401 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:40:57,401 - using serial LDA version on this node
+2024-08-12 12:40:57,402 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:40:57,402 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:40:57,406 - -8.024 per-word bound, 260.3 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
+2024-08-12 12:40:57,406 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:40:57,407 - topic #0 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"plans" + 0.005*"2022" + 0.004*"oversight" + 0.004*"effective" + 0.004*"However" + 0.004*"impact" + 0.004*"Nottingham" + 0.004*"City"
+2024-08-12 12:40:57,407 - topic #1 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"Nottingham" + 0.006*"effective" + 0.005*"11" + 0.005*"plans" + 0.005*"impact" + 0.005*"City" + 0.005*"risk" + 0.004*"practice"
+2024-08-12 12:40:57,407 - topic #2 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"Nottingham" + 0.006*"effective" + 0.005*"plans" + 0.005*"impact" + 0.005*"oversight" + 0.005*"consistently" + 0.004*"City" + 0.004*"However"
+2024-08-12 12:40:57,407 - topic diff=0.764454, rho=1.000000
+2024-08-12 12:40:57,408 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:40:57.408133', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:40:58,330 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:40:58,330 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:58,331 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:40:58,331 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:58,331 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:40:58,331 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:58,331 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:40:58,331 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:58,331 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:40:58,332 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:40:58,332 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:40:58,332 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:09,638 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:41:09,640 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)
+2024-08-12 12:41:09,640 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)", 'datetime': '2024-08-12T12:41:09.640442', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:09,641 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:41:09,641 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:41:09,641 - using serial LDA version on this node
+2024-08-12 12:41:09,642 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:41:09,642 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:41:09,645 - -8.011 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2129 words
+2024-08-12 12:41:09,645 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:41:09,647 - topic #0 (0.333): 0.018*"’" + 0.007*"Nottinghamshire" + 0.007*"well" + 0.006*"needs" + 0.005*"20" + 0.004*"plans" + 0.004*"leaders" + 0.004*"benefit" + 0.004*"2024" + 0.004*"practice"
+2024-08-12 12:41:09,647 - topic #1 (0.333): 0.013*"’" + 0.009*"well" + 0.006*"needs" + 0.005*"Nottinghamshire" + 0.004*"plans" + 0.004*"24" + 0.004*"provide" + 0.004*"risks" + 0.004*"benefit" + 0.004*"2024"
+2024-08-12 12:41:09,647 - topic #2 (0.333): 0.020*"’" + 0.011*"needs" + 0.010*"well" + 0.007*"plans" + 0.006*"Nottinghamshire" + 0.006*"Leaders" + 0.006*"effective" + 0.005*"practice" + 0.005*"leaders" + 0.005*"County"
+2024-08-12 12:41:09,647 - topic diff=0.785463, rho=1.000000
+2024-08-12 12:41:09,647 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:41:09.647865', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:10,658 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:41:10,658 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:10,659 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:41:10,659 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:10,659 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:41:10,659 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:10,659 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:41:10,659 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:10,660 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:41:10,660 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:10,660 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:41:10,660 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:22,954 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:41:22,956 - built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)
+2024-08-12 12:41:22,956 - Dictionary lifecycle event {'msg': "built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)", 'datetime': '2024-08-12T12:41:22.956610', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:22,957 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:41:22,957 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:41:22,958 - using serial LDA version on this node
+2024-08-12 12:41:22,958 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:41:22,958 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:41:22,962 - -8.081 per-word bound, 270.8 perplexity estimate based on a held-out corpus of 1 documents with 2441 words
+2024-08-12 12:41:22,962 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:41:22,963 - topic #0 (0.333): 0.012*"’" + 0.007*"well" + 0.006*"plans" + 0.005*"leaders" + 0.005*"PAs" + 0.005*"needs" + 0.005*"practice" + 0.004*"Oldham" + 0.004*"effective" + 0.004*"quality"
+2024-08-12 12:41:22,964 - topic #1 (0.333): 0.013*"’" + 0.008*"plans" + 0.006*"Oldham" + 0.006*"PAs" + 0.005*"well" + 0.005*"risk" + 0.005*"leaders" + 0.005*"needs" + 0.005*"need" + 0.004*"progress"
+2024-08-12 12:41:22,964 - topic #2 (0.333): 0.013*"’" + 0.011*"well" + 0.009*"plans" + 0.008*"needs" + 0.007*"practice" + 0.006*"Oldham" + 0.006*"PAs" + 0.006*"progress" + 0.006*"leaders" + 0.005*"effective"
+2024-08-12 12:41:22,964 - topic diff=0.786959, rho=1.000000
+2024-08-12 12:41:22,964 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1152, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:41:22.964542', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:23,807 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:41:23,807 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:23,807 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:41:23,807 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:23,807 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:41:23,807 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:23,808 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:41:23,808 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:23,808 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:41:23,808 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:23,808 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:41:23,808 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:35,169 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:41:35,171 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)
+2024-08-12 12:41:35,171 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-08-12T12:41:35.171839', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:35,172 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:41:35,172 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:41:35,173 - using serial LDA version on this node
+2024-08-12 12:41:35,173 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:41:35,173 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:41:35,177 - -7.990 per-word bound, 254.2 perplexity estimate based on a held-out corpus of 1 documents with 2294 words
+2024-08-12 12:41:35,177 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:41:35,178 - topic #0 (0.333): 0.020*"’" + 0.007*"needs" + 0.007*"well" + 0.007*"Oxfordshire" + 0.006*"good" + 0.006*"arrangements" + 0.005*"progress" + 0.005*"risk" + 0.005*"12" + 0.005*"practice"
+2024-08-12 12:41:35,178 - topic #1 (0.333): 0.014*"’" + 0.012*"needs" + 0.007*"Oxfordshire" + 0.007*"well" + 0.006*"supported" + 0.006*"risk" + 0.005*"good" + 0.005*"education" + 0.005*"quality" + 0.005*"practice"
+2024-08-12 12:41:35,179 - topic #2 (0.333): 0.024*"’" + 0.010*"needs" + 0.006*"Oxfordshire" + 0.006*"risk" + 0.006*"well" + 0.005*"23" + 0.005*"supported" + 0.005*"quality" + 0.005*"good" + 0.004*"receive"
+2024-08-12 12:41:35,179 - topic diff=0.776359, rho=1.000000
+2024-08-12 12:41:35,179 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1066, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:41:35.179333', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:36,130 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:41:36,131 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:36,131 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:41:36,131 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:36,131 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:41:36,131 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:36,132 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:41:36,132 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:36,132 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:41:36,132 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:36,132 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:41:36,133 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:46,054 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:41:46,056 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)
+2024-08-12 12:41:46,056 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-08-12T12:41:46.056166', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:46,057 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:41:46,057 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:41:46,057 - using serial LDA version on this node
+2024-08-12 12:41:46,057 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:41:46,057 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:41:46,060 - -7.878 per-word bound, 235.2 perplexity estimate based on a held-out corpus of 1 documents with 1737 words
+2024-08-12 12:41:46,061 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:41:46,062 - topic #0 (0.333): 0.018*"’" + 0.017*"needs" + 0.009*"need" + 0.008*"Peterborough" + 0.007*"2023" + 0.007*"well" + 0.006*"progress" + 0.006*"supported" + 0.006*"8" + 0.006*"lack"
+2024-08-12 12:41:46,062 - topic #1 (0.333): 0.009*"’" + 0.009*"needs" + 0.006*"2023" + 0.006*"well" + 0.005*"progress" + 0.005*"Peterborough" + 0.005*"8" + 0.005*"27" + 0.005*"need" + 0.004*"good"
+2024-08-12 12:41:46,062 - topic #2 (0.333): 0.012*"’" + 0.010*"needs" + 0.006*"need" + 0.005*"well" + 0.005*"Peterborough" + 0.005*"progress" + 0.005*"receive" + 0.005*"2023" + 0.004*"plans" + 0.004*"November"
+2024-08-12 12:41:46,062 - topic diff=0.766555, rho=1.000000
+2024-08-12 12:41:46,062 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=893, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:41:46.062940', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:41:47,170 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:41:47,171 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:47,171 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:41:47,171 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:47,171 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:41:47,171 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:47,172 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:41:47,172 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:47,172 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:41:47,172 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:41:47,172 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:41:47,172 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:01,128 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:42:01,130 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
+2024-08-12 12:42:01,130 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-08-12T12:42:01.130687', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:01,131 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:42:01,132 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:42:01,132 - using serial LDA version on this node
+2024-08-12 12:42:01,132 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:42:01,132 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:42:01,136 - -8.088 per-word bound, 272.0 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
+2024-08-12 12:42:01,136 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:42:01,138 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.007*"Plymouth" + 0.007*"needs" + 0.006*"practice" + 0.005*"plans" + 0.005*"education" + 0.005*"benefit" + 0.005*"2" + 0.005*"risks"
+2024-08-12 12:42:01,138 - topic #1 (0.333): 0.015*"’" + 0.011*"needs" + 0.007*"Plymouth" + 0.006*"well" + 0.006*"practice" + 0.005*"timely" + 0.004*"February" + 0.004*"2024" + 0.004*"appropriate" + 0.004*"understand"
+2024-08-12 12:42:01,138 - topic #2 (0.333): 0.011*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"22" + 0.005*"appropriate" + 0.005*"health" + 0.004*"Plymouth" + 0.004*"2" + 0.004*"Council" + 0.004*"risks"
+2024-08-12 12:42:01,138 - topic diff=0.839625, rho=1.000000
+2024-08-12 12:42:01,139 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1232, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:42:01.139016', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:02,162 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:42:02,162 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:02,162 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:42:02,163 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:02,163 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:42:02,163 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:02,163 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:42:02,163 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:02,163 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:42:02,163 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:02,164 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:42:02,164 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:14,868 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:42:14,870 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)
+2024-08-12 12:42:14,870 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-08-12T12:42:14.870805', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:14,871 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:42:14,872 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:42:14,872 - using serial LDA version on this node
+2024-08-12 12:42:14,872 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:42:14,872 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:42:14,876 - -8.108 per-word bound, 275.9 perplexity estimate based on a held-out corpus of 1 documents with 2738 words
+2024-08-12 12:42:14,876 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:42:14,878 - topic #0 (0.333): 0.015*"’" + 0.008*"care-experienced" + 0.007*"Portsmouth" + 0.007*"well" + 0.006*"needs" + 0.005*"health" + 0.005*"family" + 0.005*"leaders" + 0.005*"carers" + 0.005*"19"
+2024-08-12 12:42:14,878 - topic #1 (0.333): 0.013*"’" + 0.008*"well" + 0.007*"care-experienced" + 0.006*"Portsmouth" + 0.006*"family" + 0.006*"health" + 0.006*"needs" + 0.005*"practice" + 0.005*"risk" + 0.005*"plans"
+2024-08-12 12:42:14,878 - topic #2 (0.333): 0.022*"’" + 0.008*"needs" + 0.008*"care-experienced" + 0.006*"Portsmouth" + 0.006*"well" + 0.006*"plans" + 0.005*"family" + 0.005*"need" + 0.004*"health" + 0.004*"leaders"
+2024-08-12 12:42:14,878 - topic diff=0.793023, rho=1.000000
+2024-08-12 12:42:14,878 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:42:14.878925', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:16,059 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:42:16,059 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:16,060 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:42:16,060 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:16,060 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:42:16,060 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:16,061 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:42:16,061 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:16,061 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:42:16,061 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:16,062 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:42:16,062 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:27,803 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:42:27,806 - built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)
+2024-08-12 12:42:27,806 - Dictionary lifecycle event {'msg': "built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)", 'datetime': '2024-08-12T12:42:27.806324', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:27,807 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:42:27,807 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:42:27,807 - using serial LDA version on this node
+2024-08-12 12:42:27,808 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:42:27,808 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:42:27,812 - -8.153 per-word bound, 284.7 perplexity estimate based on a held-out corpus of 1 documents with 2562 words
+2024-08-12 12:42:27,812 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:42:27,813 - topic #0 (0.333): 0.018*"’" + 0.008*"needs" + 0.005*"well" + 0.005*"PAs" + 0.005*"Reading" + 0.005*"plans" + 0.005*"3" + 0.004*"2024" + 0.004*"progress" + 0.004*"clear"
+2024-08-12 12:42:27,814 - topic #1 (0.333): 0.012*"’" + 0.006*"needs" + 0.005*"PAs" + 0.005*"progress" + 0.005*"well" + 0.004*"plans" + 0.004*"effective" + 0.004*"timely" + 0.004*"April" + 0.004*"22"
+2024-08-12 12:42:27,814 - topic #2 (0.333): 0.010*"’" + 0.006*"needs" + 0.006*"PAs" + 0.005*"plans" + 0.005*"progress" + 0.005*"Reading" + 0.004*"clear" + 0.004*"well" + 0.004*"arrangements" + 0.004*"risk"
+2024-08-12 12:42:27,814 - topic diff=0.759518, rho=1.000000
+2024-08-12 12:42:27,814 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1231, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:42:27.814648', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:28,693 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:42:28,693 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:28,693 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:42:28,693 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:28,693 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:42:28,693 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:28,693 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:42:28,694 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:28,694 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:42:28,694 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:28,694 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:42:28,694 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:40,408 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:42:40,410 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)
+2024-08-12 12:42:40,410 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-08-12T12:42:40.410865', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:40,411 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:42:40,412 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:42:40,412 - using serial LDA version on this node
+2024-08-12 12:42:40,412 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:42:40,412 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:42:40,416 - -8.003 per-word bound, 256.5 perplexity estimate based on a held-out corpus of 1 documents with 2515 words
+2024-08-12 12:42:40,416 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:42:40,417 - topic #0 (0.333): 0.020*"’" + 0.006*"consistently" + 0.006*"leaders" + 0.005*"plans" + 0.005*"needs" + 0.004*"Cleveland" + 0.004*"However" + 0.004*"risk" + 0.004*"2022" + 0.004*"Redcar"
+2024-08-12 12:42:40,417 - topic #1 (0.333): 0.010*"’" + 0.005*"However" + 0.005*"leaders" + 0.005*"20" + 0.005*"practice" + 0.004*"plans" + 0.004*"needs" + 0.004*"2022" + 0.004*"consistently" + 0.004*"Redcar"
+2024-08-12 12:42:40,418 - topic #2 (0.333): 0.020*"’" + 0.007*"leaders" + 0.006*"needs" + 0.006*"However" + 0.006*"plans" + 0.006*"consistently" + 0.005*"20" + 0.005*"2022" + 0.005*"Cleveland" + 0.005*"practice"
+2024-08-12 12:42:40,418 - topic diff=0.803816, rho=1.000000
+2024-08-12 12:42:40,418 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:42:40.418381', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:41,345 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:42:41,346 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:41,346 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:42:41,346 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:41,346 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:42:41,346 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:41,347 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:42:41,347 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:41,347 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:42:41,347 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:41,347 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:42:41,347 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:54,282 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:42:54,284 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)
+2024-08-12 12:42:54,285 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-08-12T12:42:54.284996', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:54,286 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:42:54,286 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:42:54,286 - using serial LDA version on this node
+2024-08-12 12:42:54,286 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:42:54,286 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:42:54,290 - -8.025 per-word bound, 260.5 perplexity estimate based on a held-out corpus of 1 documents with 2656 words
+2024-08-12 12:42:54,290 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:42:54,292 - topic #0 (0.333): 0.021*"’" + 0.009*"needs" + 0.008*"experienced" + 0.007*"practice" + 0.006*"plans" + 0.006*"Rochdale" + 0.005*"consistently" + 0.005*"3" + 0.005*"response" + 0.005*"good"
+2024-08-12 12:42:54,292 - topic #1 (0.333): 0.018*"’" + 0.011*"experienced" + 0.010*"practice" + 0.007*"needs" + 0.006*"response" + 0.006*"plans" + 0.006*"good" + 0.005*"consistently" + 0.005*"quality" + 0.005*"Rochdale"
+2024-08-12 12:42:54,292 - topic #2 (0.333): 0.021*"’" + 0.009*"experienced" + 0.008*"needs" + 0.007*"practice" + 0.006*"response" + 0.006*"progress" + 0.005*"quality" + 0.005*"plans" + 0.005*"consistently" + 0.005*"3"
+2024-08-12 12:42:54,292 - topic diff=0.813404, rho=1.000000
+2024-08-12 12:42:54,292 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1150, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:42:54.292755', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:42:55,274 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:42:55,274 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:55,274 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:42:55,274 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:55,275 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:42:55,275 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:55,275 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:42:55,275 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:55,275 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:42:55,275 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:42:55,276 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:42:55,276 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:06,893 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:43:06,895 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)
+2024-08-12 12:43:06,895 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-08-12T12:43:06.895520', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:06,896 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:43:06,896 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:43:06,896 - using serial LDA version on this node
+2024-08-12 12:43:06,897 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:43:06,897 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:43:06,901 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2366 words
+2024-08-12 12:43:06,901 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:43:06,902 - topic #0 (0.333): 0.015*"’" + 0.009*"needs" + 0.008*"Rotherham" + 0.005*"well" + 0.005*"Council" + 0.005*"plans" + 0.005*"ensure" + 0.005*"June" + 0.004*"However" + 0.004*"clear"
+2024-08-12 12:43:06,902 - topic #1 (0.333): 0.014*"’" + 0.007*"Rotherham" + 0.005*"good" + 0.005*"well" + 0.005*"However" + 0.004*"ensure" + 0.004*"needs" + 0.004*"plans" + 0.004*"Council" + 0.004*"27"
+2024-08-12 12:43:06,902 - topic #2 (0.333): 0.015*"’" + 0.010*"Rotherham" + 0.006*"good" + 0.005*"needs" + 0.005*"well" + 0.005*"ensure" + 0.004*"1" + 0.004*"Council" + 0.004*"family" + 0.004*"Borough"
+2024-08-12 12:43:06,903 - topic diff=0.774298, rho=1.000000
+2024-08-12 12:43:06,903 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1127, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:43:06.903204', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:07,773 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:43:07,773 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:07,773 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:43:07,773 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:07,774 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:43:07,774 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:07,774 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:43:07,774 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:07,774 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:43:07,774 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:07,774 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:43:07,775 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:18,466 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:43:18,468 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)
+2024-08-12 12:43:18,469 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-08-12T12:43:18.469107', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:18,470 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:43:18,470 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:43:18,470 - using serial LDA version on this node
+2024-08-12 12:43:18,470 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:43:18,471 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:43:18,474 - -8.045 per-word bound, 264.1 perplexity estimate based on a held-out corpus of 1 documents with 2380 words
+2024-08-12 12:43:18,474 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:43:18,476 - topic #0 (0.333): 0.016*"well" + 0.015*"’" + 0.011*"practice" + 0.007*"strong" + 0.007*"needs" + 0.006*"highly" + 0.006*"leaders" + 0.005*"high" + 0.005*"effective" + 0.004*"professionals"
+2024-08-12 12:43:18,476 - topic #1 (0.333): 0.013*"well" + 0.010*"practice" + 0.009*"highly" + 0.008*"’" + 0.006*"strong" + 0.006*"needs" + 0.005*"range" + 0.005*"effective" + 0.004*"high" + 0.004*"need"
+2024-08-12 12:43:18,476 - topic #2 (0.333): 0.011*"’" + 0.010*"well" + 0.010*"practice" + 0.006*"effective" + 0.006*"highly" + 0.006*"strong" + 0.005*"leaders" + 0.004*"effectively" + 0.004*"professionals" + 0.004*"risk"
+2024-08-12 12:43:18,476 - topic diff=0.771978, rho=1.000000
+2024-08-12 12:43:18,476 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:43:18.476883', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:19,508 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:43:19,508 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:19,508 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:43:19,508 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:19,509 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:43:19,509 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:19,509 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:43:19,509 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:19,509 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:43:19,509 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:19,510 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:43:19,510 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:30,098 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:43:30,100 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)
+2024-08-12 12:43:30,100 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-08-12T12:43:30.100315', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:30,101 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:43:30,101 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:43:30,101 - using serial LDA version on this node
+2024-08-12 12:43:30,102 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:43:30,102 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:43:30,105 - -8.063 per-word bound, 267.5 perplexity estimate based on a held-out corpus of 1 documents with 2257 words
+2024-08-12 12:43:30,106 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:43:30,107 - topic #0 (0.333): 0.011*"’" + 0.008*"well" + 0.007*"plans" + 0.006*"practice" + 0.005*"needs" + 0.005*"good" + 0.004*"regularly" + 0.004*"effective" + 0.004*"risk" + 0.004*"need"
+2024-08-12 12:43:30,107 - topic #1 (0.333): 0.016*"’" + 0.009*"well" + 0.009*"plans" + 0.008*"needs" + 0.006*"good" + 0.005*"effective" + 0.004*"risk" + 0.004*"range" + 0.004*"clear" + 0.004*"need"
+2024-08-12 12:43:30,107 - topic #2 (0.333): 0.012*"’" + 0.009*"well" + 0.009*"needs" + 0.008*"plans" + 0.005*"effective" + 0.005*"supported" + 0.004*"clear" + 0.004*"Kingston" + 0.004*"need" + 0.004*"good"
+2024-08-12 12:43:30,107 - topic diff=0.748150, rho=1.000000
+2024-08-12 12:43:30,108 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1107, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:43:30.108049', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:31,225 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:43:31,225 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:31,226 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:43:31,226 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:31,226 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:43:31,226 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:31,226 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:43:31,227 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:31,227 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:43:31,227 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:31,227 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:43:31,227 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:41,617 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:43:41,619 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)
+2024-08-12 12:43:41,620 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-08-12T12:43:41.619977', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:41,620 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:43:41,621 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:43:41,621 - using serial LDA version on this node
+2024-08-12 12:43:41,621 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:43:41,621 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:43:41,625 - -8.117 per-word bound, 277.6 perplexity estimate based on a held-out corpus of 1 documents with 2088 words
+2024-08-12 12:43:41,625 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:43:41,627 - topic #0 (0.333): 0.007*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"quality" + 0.004*"However" + 0.004*"information" + 0.004*"use" + 0.004*"always" + 0.004*"effective" + 0.003*"good"
+2024-08-12 12:43:41,627 - topic #1 (0.333): 0.016*"’" + 0.005*"needs" + 0.005*"effective" + 0.005*"well" + 0.004*"plans" + 0.004*"quality" + 0.004*"always" + 0.004*"information" + 0.004*"benefit" + 0.004*"case"
+2024-08-12 12:43:41,627 - topic #2 (0.333): 0.009*"’" + 0.006*"plans" + 0.006*"well" + 0.005*"quality" + 0.004*"benefit" + 0.004*"needs" + 0.004*"use" + 0.004*"actions" + 0.003*"health" + 0.003*"informed"
+2024-08-12 12:43:41,627 - topic diff=0.717557, rho=1.000000
+2024-08-12 12:43:41,627 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:43:41.627877', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:42,820 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:43:42,820 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:42,821 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:43:42,821 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:42,821 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:43:42,821 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:42,821 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:43:42,821 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:42,822 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:43:42,822 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:42,822 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:43:42,822 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:54,005 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:43:54,007 - built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)
+2024-08-12 12:43:54,007 - Dictionary lifecycle event {'msg': "built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)", 'datetime': '2024-08-12T12:43:54.007721', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:54,008 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:43:54,008 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:43:54,009 - using serial LDA version on this node
+2024-08-12 12:43:54,009 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:43:54,009 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:43:54,013 - -8.047 per-word bound, 264.4 perplexity estimate based on a held-out corpus of 1 documents with 2211 words
+2024-08-12 12:43:54,013 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:43:54,014 - topic #0 (0.333): 0.012*"’" + 0.010*"Rutland" + 0.007*"needs" + 0.006*"plans" + 0.006*"effective" + 0.005*"good" + 0.005*"positive" + 0.005*"need" + 0.005*"PAs" + 0.004*"practitioners"
+2024-08-12 12:43:54,014 - topic #1 (0.333): 0.020*"’" + 0.008*"needs" + 0.007*"Rutland" + 0.007*"effective" + 0.005*"impact" + 0.005*"plans" + 0.005*"positive" + 0.005*"practitioners" + 0.005*"practice" + 0.005*"good"
+2024-08-12 12:43:54,015 - topic #2 (0.333): 0.022*"’" + 0.009*"Rutland" + 0.008*"impact" + 0.008*"needs" + 0.007*"need" + 0.007*"positive" + 0.006*"effective" + 0.005*"family" + 0.005*"experiences" + 0.004*"2024"
+2024-08-12 12:43:54,015 - topic diff=0.765139, rho=1.000000
+2024-08-12 12:43:54,015 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1089, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:43:54.015482', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:43:54,999 - Inspection date 2024-04-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:43:54,999 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:54,999 - Inspection date 2024-04-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:43:54,999 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:54,999 - Inspection date 2024-04-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:43:54,999 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:55,000 - Inspection date 2024-04-15 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:43:55,000 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:55,000 - Inspection date 2024-04-15 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:43:55,000 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:43:55,000 - Inspection date 2024-04-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:43:55,000 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:06,311 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:44:06,313 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)
+2024-08-12 12:44:06,313 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-08-12T12:44:06.313554', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:06,314 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:44:06,314 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:44:06,314 - using serial LDA version on this node
+2024-08-12 12:44:06,315 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:44:06,315 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:44:06,319 - -8.005 per-word bound, 256.9 perplexity estimate based on a held-out corpus of 1 documents with 2253 words
+2024-08-12 12:44:06,319 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:44:06,320 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"plans" + 0.006*"needs" + 0.006*"effective" + 0.005*"practice" + 0.005*"6" + 0.005*"10" + 0.005*"leaders" + 0.005*"Salford"
+2024-08-12 12:44:06,320 - topic #1 (0.333): 0.010*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"effective" + 0.007*"plans" + 0.006*"Salford" + 0.005*"experiences" + 0.005*"2023" + 0.004*"practice" + 0.004*"quality"
+2024-08-12 12:44:06,320 - topic #2 (0.333): 0.013*"’" + 0.008*"plans" + 0.007*"Salford" + 0.006*"needs" + 0.006*"planning" + 0.005*"well" + 0.005*"effective" + 0.005*"leaders" + 0.005*"practice" + 0.004*"progress"
+2024-08-12 12:44:06,320 - topic diff=0.786276, rho=1.000000
+2024-08-12 12:44:06,321 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:44:06.321128', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:07,212 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:44:07,212 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:07,212 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:44:07,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:07,213 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:44:07,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:07,213 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:44:07,213 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:07,214 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:44:07,214 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:07,214 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:44:07,214 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:17,137 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:44:17,138 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)
+2024-08-12 12:44:17,139 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-08-12T12:44:17.139133', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:17,140 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:44:17,140 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:44:17,140 - using serial LDA version on this node
+2024-08-12 12:44:17,140 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:44:17,140 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:44:17,144 - -7.943 per-word bound, 246.1 perplexity estimate based on a held-out corpus of 1 documents with 2066 words
+2024-08-12 12:44:17,144 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:44:17,145 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"Sandwell" + 0.006*"well" + 0.006*"plans" + 0.005*"Trust" + 0.005*"effective" + 0.004*"quality" + 0.004*"9" + 0.004*"changes"
+2024-08-12 12:44:17,145 - topic #1 (0.333): 0.015*"’" + 0.009*"Sandwell" + 0.007*"needs" + 0.007*"plans" + 0.005*"quality" + 0.005*"number" + 0.005*"progress" + 0.005*"well" + 0.005*"9" + 0.004*"20"
+2024-08-12 12:44:17,146 - topic #2 (0.333): 0.013*"’" + 0.009*"needs" + 0.009*"well" + 0.008*"plans" + 0.007*"quality" + 0.006*"Sandwell" + 0.005*"Trust" + 0.004*"education" + 0.004*"20" + 0.004*"progress"
+2024-08-12 12:44:17,146 - topic diff=0.760730, rho=1.000000
+2024-08-12 12:44:17,146 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=995, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:44:17.146386', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:18,077 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:44:18,078 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:18,078 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:44:18,078 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:18,078 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:44:18,078 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:18,079 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:44:18,079 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:18,079 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:44:18,079 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:18,079 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:44:18,079 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:29,388 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:44:29,390 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)
+2024-08-12 12:44:29,391 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-08-12T12:44:29.391128', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:29,392 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:44:29,392 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:44:29,392 - using serial LDA version on this node
+2024-08-12 12:44:29,392 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:44:29,393 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:44:29,396 - -7.932 per-word bound, 244.1 perplexity estimate based on a held-out corpus of 1 documents with 2300 words
+2024-08-12 12:44:29,396 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:44:29,397 - topic #0 (0.333): 0.016*"’" + 0.009*"needs" + 0.006*"lack" + 0.005*"including" + 0.005*"many" + 0.005*"protection" + 0.005*"practice" + 0.005*"response" + 0.005*"Sefton" + 0.005*"March"
+2024-08-12 12:44:29,398 - topic #1 (0.333): 0.017*"’" + 0.010*"needs" + 0.007*"practice" + 0.006*"oversight" + 0.005*"lack" + 0.005*"4" + 0.005*"Sefton" + 0.005*"always" + 0.004*"protection" + 0.004*"management"
+2024-08-12 12:44:29,398 - topic #2 (0.333): 0.014*"’" + 0.008*"needs" + 0.007*"practice" + 0.006*"oversight" + 0.005*"including" + 0.005*"many" + 0.005*"protection" + 0.005*"always" + 0.005*"◼" + 0.005*"management"
+2024-08-12 12:44:29,398 - topic diff=0.788647, rho=1.000000
+2024-08-12 12:44:29,398 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:44:29.398687', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:30,381 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:44:30,382 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:30,382 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:44:30,382 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:30,382 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:44:30,383 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:30,383 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:44:30,383 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:30,383 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:44:30,383 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:30,384 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:44:30,384 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:41,864 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:44:41,866 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)
+2024-08-12 12:44:41,866 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-08-12T12:44:41.866819', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:41,868 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:44:41,868 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:44:41,868 - using serial LDA version on this node
+2024-08-12 12:44:41,868 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:44:41,869 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:44:41,876 - -8.071 per-word bound, 268.9 perplexity estimate based on a held-out corpus of 1 documents with 2327 words
+2024-08-12 12:44:41,876 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:44:41,878 - topic #0 (0.333): 0.023*"’" + 0.014*"Sheffield" + 0.009*"needs" + 0.006*"well" + 0.006*"practice" + 0.005*"leaders" + 0.005*"health" + 0.005*"good" + 0.005*"ensure" + 0.005*"plans"
+2024-08-12 12:44:41,878 - topic #1 (0.333): 0.011*"’" + 0.009*"needs" + 0.008*"Sheffield" + 0.004*"practice" + 0.004*"leaders" + 0.004*"well" + 0.004*"experiences" + 0.004*"health" + 0.004*"quality" + 0.004*"mental"
+2024-08-12 12:44:41,879 - topic #2 (0.333): 0.022*"’" + 0.010*"Sheffield" + 0.009*"well" + 0.008*"needs" + 0.007*"leaders" + 0.006*"health" + 0.006*"practice" + 0.005*"quality" + 0.005*"September" + 0.004*"experiences"
+2024-08-12 12:44:41,879 - topic diff=0.787351, rho=1.000000
+2024-08-12 12:44:41,879 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:44:41.879268', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:42,802 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:44:42,803 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:42,803 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:44:42,803 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:42,803 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:44:42,804 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:42,804 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:44:42,804 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:42,804 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:44:42,804 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:42,805 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:44:42,805 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:51,064 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:44:51,066 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)
+2024-08-12 12:44:51,066 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-08-12T12:44:51.066670', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:51,067 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:44:51,067 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:44:51,067 - using serial LDA version on this node
+2024-08-12 12:44:51,068 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:44:51,068 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:44:51,071 - -7.963 per-word bound, 249.5 perplexity estimate based on a held-out corpus of 1 documents with 1749 words
+2024-08-12 12:44:51,071 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:44:51,072 - topic #0 (0.333): 0.016*"’" + 0.007*"Shropshire" + 0.006*"needs" + 0.006*"well" + 0.005*"progress" + 0.005*"making" + 0.005*"effectively" + 0.005*"plans" + 0.005*"11" + 0.004*"2022"
+2024-08-12 12:44:51,073 - topic #1 (0.333): 0.020*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"Shropshire" + 0.006*"progress" + 0.006*"plans" + 0.005*"2022" + 0.005*"making" + 0.005*"7" + 0.005*"leaders"
+2024-08-12 12:44:51,073 - topic #2 (0.333): 0.014*"’" + 0.008*"needs" + 0.006*"well" + 0.006*"Shropshire" + 0.005*"plans" + 0.005*"progress" + 0.005*"2022" + 0.005*"making" + 0.004*"practice" + 0.004*"need"
+2024-08-12 12:44:51,073 - topic diff=0.718589, rho=1.000000
+2024-08-12 12:44:51,073 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=939, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:44:51.073564', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:44:51,930 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:44:51,930 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:51,930 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:44:51,931 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:51,931 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:44:51,931 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:51,931 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:44:51,931 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:51,931 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:44:51,931 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:44:51,932 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:44:51,932 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:03,916 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:45:03,918 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)
+2024-08-12 12:45:03,918 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-08-12T12:45:03.918801', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:03,919 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:45:03,919 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:45:03,920 - using serial LDA version on this node
+2024-08-12 12:45:03,920 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:45:03,920 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:45:03,924 - -8.047 per-word bound, 264.4 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
+2024-08-12 12:45:03,924 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:45:03,925 - topic #0 (0.333): 0.018*"’" + 0.010*"Slough" + 0.008*"quality" + 0.007*"plans" + 0.006*"needs" + 0.005*"need" + 0.005*"leaders" + 0.005*"practice" + 0.005*"impact" + 0.005*"However"
+2024-08-12 12:45:03,926 - topic #1 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"Slough" + 0.006*"plans" + 0.006*"practice" + 0.005*"3" + 0.005*"leaders" + 0.005*"quality" + 0.005*"23" + 0.004*"supported"
+2024-08-12 12:45:03,926 - topic #2 (0.333): 0.015*"’" + 0.006*"practice" + 0.005*"needs" + 0.005*"Slough" + 0.004*"3" + 0.004*"impact" + 0.004*"senior" + 0.004*"plans" + 0.004*"supported" + 0.004*"quality"
+2024-08-12 12:45:03,926 - topic diff=0.785770, rho=1.000000
+2024-08-12 12:45:03,926 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1113, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:45:03.926481', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:04,844 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:45:04,844 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:04,845 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:45:04,845 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:04,845 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:45:04,845 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:04,845 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:45:04,845 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:04,846 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:45:04,846 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:04,846 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:45:04,846 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:15,900 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:45:15,902 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)
+2024-08-12 12:45:15,902 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-08-12T12:45:15.902386', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:15,903 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:45:15,903 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:45:15,903 - using serial LDA version on this node
+2024-08-12 12:45:15,904 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:45:15,904 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:45:15,907 - -7.917 per-word bound, 241.6 perplexity estimate based on a held-out corpus of 1 documents with 2163 words
+2024-08-12 12:45:15,907 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:45:15,908 - topic #0 (0.333): 0.019*"’" + 0.012*"lack" + 0.007*"2022" + 0.006*"Solihull" + 0.006*"significant" + 0.006*"practice" + 0.005*"need" + 0.005*"timely" + 0.005*"effective" + 0.005*"risk"
+2024-08-12 12:45:15,909 - topic #1 (0.333): 0.013*"’" + 0.009*"lack" + 0.008*"2022" + 0.006*"Solihull" + 0.006*"need" + 0.005*"quality" + 0.005*"practice" + 0.005*"effective" + 0.005*"experiences" + 0.004*"means"
+2024-08-12 12:45:15,909 - topic #2 (0.333): 0.014*"’" + 0.011*"lack" + 0.010*"2022" + 0.008*"risk" + 0.007*"need" + 0.006*"quality" + 0.006*"Solihull" + 0.006*"experiences" + 0.005*"significant" + 0.005*"delay"
+2024-08-12 12:45:15,909 - topic diff=0.788843, rho=1.000000
+2024-08-12 12:45:15,909 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=996, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:45:15.909663', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:16,947 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:45:16,947 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:16,948 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:45:16,948 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:16,948 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:45:16,948 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:16,949 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:45:16,949 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:16,949 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:45:16,949 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:16,949 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:45:16,950 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:27,656 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:45:27,658 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)
+2024-08-12 12:45:27,658 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-08-12T12:45:27.658354', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:27,659 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:45:27,659 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:45:27,659 - using serial LDA version on this node
+2024-08-12 12:45:27,660 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:45:27,660 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:45:27,663 - -7.922 per-word bound, 242.4 perplexity estimate based on a held-out corpus of 1 documents with 2181 words
+2024-08-12 12:45:27,663 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:45:27,664 - topic #0 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"Somerset" + 0.006*"good" + 0.006*"plans" + 0.006*"leaders" + 0.005*"number" + 0.005*"progress" + 0.005*"health"
+2024-08-12 12:45:27,665 - topic #1 (0.333): 0.016*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"Somerset" + 0.006*"good" + 0.006*"supported" + 0.005*"practice" + 0.005*"plans" + 0.005*"including" + 0.005*"leaders"
+2024-08-12 12:45:27,665 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"plans" + 0.006*"regularly" + 0.006*"progress" + 0.006*"Somerset" + 0.005*"including" + 0.005*"practice" + 0.005*"number"
+2024-08-12 12:45:27,665 - topic diff=0.803872, rho=1.000000
+2024-08-12 12:45:27,665 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:45:27.665670', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:28,619 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:45:28,619 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:28,619 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:45:28,619 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:28,620 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:45:28,620 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:28,620 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:45:28,620 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:28,620 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:45:28,620 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:28,621 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:45:28,621 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:40,842 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:45:40,845 - built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)
+2024-08-12 12:45:40,845 - Dictionary lifecycle event {'msg': "built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)", 'datetime': '2024-08-12T12:45:40.845295', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:40,846 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:45:40,846 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:45:40,846 - using serial LDA version on this node
+2024-08-12 12:45:40,847 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:45:40,847 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:45:40,851 - -8.056 per-word bound, 266.1 perplexity estimate based on a held-out corpus of 1 documents with 2751 words
+2024-08-12 12:45:40,851 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:45:40,852 - topic #0 (0.333): 0.017*"’" + 0.011*"needs" + 0.008*"June" + 0.007*"2024" + 0.006*"well" + 0.006*"Gloucestershire" + 0.005*"effective" + 0.005*"ensure" + 0.005*"plans" + 0.005*"understand"
+2024-08-12 12:45:40,852 - topic #1 (0.333): 0.018*"’" + 0.009*"needs" + 0.007*"leaders" + 0.007*"2024" + 0.006*"June" + 0.006*"well" + 0.005*"understand" + 0.005*"plans" + 0.005*"South" + 0.005*"progress"
+2024-08-12 12:45:40,853 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.008*"leaders" + 0.005*"2024" + 0.005*"ensure" + 0.005*"effective" + 0.005*"June" + 0.005*"strong" + 0.005*"progress" + 0.005*"South"
+2024-08-12 12:45:40,853 - topic diff=0.832874, rho=1.000000
+2024-08-12 12:45:40,853 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1188, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:45:40.853309', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:41,801 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:45:41,802 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:41,802 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:45:41,803 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:41,803 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:45:41,803 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:41,804 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:45:41,804 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:41,804 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:45:41,804 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:41,805 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:45:41,805 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:51,665 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:45:51,667 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions)
+2024-08-12 12:45:51,667 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-08-12T12:45:51.667892', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:51,668 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:45:51,668 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:45:51,669 - using serial LDA version on this node
+2024-08-12 12:45:51,669 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:45:51,669 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:45:51,673 - -7.886 per-word bound, 236.6 perplexity estimate based on a held-out corpus of 1 documents with 2189 words
+2024-08-12 12:45:51,673 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:45:51,674 - topic #0 (0.333): 0.020*"’" + 0.009*"Tyneside" + 0.009*"needs" + 0.006*"South" + 0.005*"However" + 0.005*"effective" + 0.005*"carers" + 0.005*"plans" + 0.005*"progress" + 0.005*"2022"
+2024-08-12 12:45:51,674 - topic #1 (0.333): 0.030*"’" + 0.010*"needs" + 0.008*"South" + 0.007*"Tyneside" + 0.007*"oversight" + 0.005*"9" + 0.005*"5" + 0.005*"effective" + 0.005*"management" + 0.005*"carers"
+2024-08-12 12:45:51,674 - topic #2 (0.333): 0.019*"’" + 0.008*"needs" + 0.008*"South" + 0.005*"14" + 0.005*"Tyneside" + 0.005*"However" + 0.005*"management" + 0.004*"2022" + 0.004*"carers" + 0.004*"leaders"
+2024-08-12 12:45:51,674 - topic diff=0.800067, rho=1.000000
+2024-08-12 12:45:51,675 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=981, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:45:51.675036', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:45:52,730 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:45:52,730 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:52,731 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:45:52,731 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:52,731 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:45:52,731 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:52,732 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:45:52,732 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:52,732 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:45:52,732 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:45:52,732 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:45:52,733 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:04,037 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:46:04,040 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)
+2024-08-12 12:46:04,040 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-08-12T12:46:04.040232', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:04,041 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:46:04,041 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:46:04,041 - using serial LDA version on this node
+2024-08-12 12:46:04,042 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:46:04,042 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:46:04,046 - -8.151 per-word bound, 284.2 perplexity estimate based on a held-out corpus of 1 documents with 2318 words
+2024-08-12 12:46:04,046 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:46:04,047 - topic #0 (0.333): 0.016*"’" + 0.006*"plans" + 0.005*"Southampton" + 0.005*"including" + 0.005*"good" + 0.005*"5" + 0.004*"progress" + 0.004*"improve" + 0.004*"16" + 0.004*"2023"
+2024-08-12 12:46:04,047 - topic #1 (0.333): 0.015*"’" + 0.007*"plans" + 0.005*"Southampton" + 0.004*"5" + 0.004*"needs" + 0.004*"improve" + 0.004*"progress" + 0.004*"experiences" + 0.004*"well" + 0.004*"June"
+2024-08-12 12:46:04,048 - topic #2 (0.333): 0.017*"’" + 0.006*"Southampton" + 0.005*"improve" + 0.005*"progress" + 0.005*"needs" + 0.004*"experiences" + 0.004*"well" + 0.004*"including" + 0.004*"timely" + 0.004*"16"
+2024-08-12 12:46:04,048 - topic diff=0.742146, rho=1.000000
+2024-08-12 12:46:04,048 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1178, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:46:04.048252', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:04,971 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:46:04,972 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:04,972 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:46:04,972 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:04,972 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:46:04,972 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:04,973 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:46:04,973 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:04,973 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:46:04,973 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:04,973 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:46:04,973 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:15,302 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:46:15,304 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)
+2024-08-12 12:46:15,304 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-08-12T12:46:15.304501', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:15,305 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:46:15,305 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:46:15,305 - using serial LDA version on this node
+2024-08-12 12:46:15,306 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:46:15,306 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:46:15,309 - -7.952 per-word bound, 247.6 perplexity estimate based on a held-out corpus of 1 documents with 2086 words
+2024-08-12 12:46:15,309 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:46:15,311 - topic #0 (0.333): 0.016*"’" + 0.008*"leaders" + 0.007*"quality" + 0.007*"practice" + 0.006*"planning" + 0.005*"number" + 0.005*"need" + 0.005*"within" + 0.005*"protection" + 0.005*"risk"
+2024-08-12 12:46:15,311 - topic #1 (0.333): 0.013*"’" + 0.008*"planning" + 0.006*"practice" + 0.006*"number" + 0.005*"protection" + 0.005*"quality" + 0.005*"leaders" + 0.005*"effective" + 0.005*"needs" + 0.005*"good"
+2024-08-12 12:46:15,311 - topic #2 (0.333): 0.011*"’" + 0.009*"planning" + 0.007*"practice" + 0.007*"quality" + 0.006*"always" + 0.006*"carers" + 0.005*"within" + 0.005*"plans" + 0.005*"protection" + 0.005*"well"
+2024-08-12 12:46:15,311 - topic diff=0.772782, rho=1.000000
+2024-08-12 12:46:15,311 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:46:15.311608', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:16,995 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:46:16,996 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:16,996 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:46:16,996 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:16,996 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:46:16,996 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:16,996 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:46:16,997 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:16,997 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:46:16,997 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:16,997 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:46:16,997 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:30,352 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:46:30,354 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)
+2024-08-12 12:46:30,354 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-08-12T12:46:30.354806', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:30,355 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:46:30,355 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:46:30,356 - using serial LDA version on this node
+2024-08-12 12:46:30,356 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:46:30,356 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:46:30,360 - -8.054 per-word bound, 265.7 perplexity estimate based on a held-out corpus of 1 documents with 2218 words
+2024-08-12 12:46:30,360 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:46:30,361 - topic #0 (0.333): 0.015*"’" + 0.008*"needs" + 0.008*"St" + 0.007*"Helens" + 0.006*"receive" + 0.006*"good" + 0.006*"progress" + 0.006*"well" + 0.006*"risk" + 0.005*"21"
+2024-08-12 12:46:30,361 - topic #1 (0.333): 0.014*"’" + 0.009*"St" + 0.008*"Helens" + 0.007*"needs" + 0.007*"well" + 0.007*"21" + 0.006*"progress" + 0.005*"good" + 0.005*"10" + 0.005*"need"
+2024-08-12 12:46:30,361 - topic #2 (0.333): 0.018*"’" + 0.008*"Helens" + 0.006*"St" + 0.006*"well" + 0.006*"10" + 0.005*"need" + 0.005*"needs" + 0.005*"progress" + 0.005*"receive" + 0.005*"effective"
+2024-08-12 12:46:30,362 - topic diff=0.770985, rho=1.000000
+2024-08-12 12:46:30,362 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:46:30.362191', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:31,310 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:46:31,310 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:31,310 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:46:31,310 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:31,310 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:46:31,310 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:31,310 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:46:31,311 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:31,311 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:46:31,311 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:31,311 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:46:31,311 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:42,272 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:46:42,274 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)
+2024-08-12 12:46:42,274 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-08-12T12:46:42.274873', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:42,275 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:46:42,275 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:46:42,276 - using serial LDA version on this node
+2024-08-12 12:46:42,276 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:46:42,276 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:46:42,280 - -7.995 per-word bound, 255.2 perplexity estimate based on a held-out corpus of 1 documents with 2334 words
+2024-08-12 12:46:42,280 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:46:42,281 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.006*"quality" + 0.006*"oversight" + 0.005*"health" + 0.005*"ensure" + 0.004*"Staffordshire" + 0.004*"plans" + 0.004*"practice" + 0.004*"6"
+2024-08-12 12:46:42,281 - topic #1 (0.333): 0.019*"’" + 0.014*"needs" + 0.007*"progress" + 0.006*"oversight" + 0.006*"Staffordshire" + 0.006*"practice" + 0.006*"health" + 0.006*"quality" + 0.005*"plans" + 0.005*"ensure"
+2024-08-12 12:46:42,281 - topic #2 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"practice" + 0.006*"quality" + 0.006*"ensure" + 0.006*"progress" + 0.005*"Staffordshire" + 0.005*"oversight" + 0.005*"10" + 0.005*"plans"
+2024-08-12 12:46:42,282 - topic diff=0.806920, rho=1.000000
+2024-08-12 12:46:42,282 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:46:42.282175', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:43,157 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:46:43,157 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:43,158 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:46:43,158 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:43,158 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:46:43,158 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:43,158 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:46:43,158 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:43,158 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:46:43,159 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:43,159 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:46:43,159 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:53,213 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:46:53,215 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
+2024-08-12 12:46:53,215 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-08-12T12:46:53.215732', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:53,216 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:46:53,216 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:46:53,217 - using serial LDA version on this node
+2024-08-12 12:46:53,217 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:46:53,217 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:46:53,221 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
+2024-08-12 12:46:53,221 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:46:53,222 - topic #0 (0.333): 0.012*"’" + 0.007*"needs" + 0.006*"practice" + 0.006*"Stockport" + 0.006*"well" + 0.005*"leaders" + 0.005*"risk" + 0.005*"strong" + 0.005*"plans" + 0.005*"ensure"
+2024-08-12 12:46:53,222 - topic #1 (0.333): 0.009*"’" + 0.008*"well" + 0.007*"practice" + 0.006*"Stockport" + 0.006*"needs" + 0.006*"strong" + 0.005*"ensure" + 0.004*"plans" + 0.004*"28" + 0.004*"risk"
+2024-08-12 12:46:53,222 - topic #2 (0.333): 0.011*"’" + 0.010*"well" + 0.008*"practice" + 0.007*"Stockport" + 0.006*"plans" + 0.005*"strong" + 0.005*"needs" + 0.005*"risk" + 0.005*"28" + 0.005*"quality"
+2024-08-12 12:46:53,222 - topic diff=0.793074, rho=1.000000
+2024-08-12 12:46:53,223 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1060, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:46:53.223110', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:46:54,208 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:46:54,209 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:54,209 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:46:54,209 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:54,209 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:46:54,209 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:54,209 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:46:54,209 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:54,210 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:46:54,210 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:46:54,210 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:46:54,210 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:05,127 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:47:05,129 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)
+2024-08-12 12:47:05,129 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-08-12T12:47:05.129256', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:05,130 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:47:05,130 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:47:05,130 - using serial LDA version on this node
+2024-08-12 12:47:05,131 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:47:05,131 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:47:05,134 - -7.962 per-word bound, 249.4 perplexity estimate based on a held-out corpus of 1 documents with 2269 words
+2024-08-12 12:47:05,134 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:47:05,136 - topic #0 (0.333): 0.012*"’" + 0.009*"plans" + 0.007*"leaders" + 0.005*"needs" + 0.005*"on-Tees" + 0.005*"Stockton" + 0.005*"good" + 0.004*"senior" + 0.004*"quality" + 0.004*"receive"
+2024-08-12 12:47:05,136 - topic #1 (0.333): 0.023*"’" + 0.010*"leaders" + 0.009*"plans" + 0.008*"well" + 0.007*"quality" + 0.007*"needs" + 0.007*"on-Tees" + 0.006*"good" + 0.006*"Stockton" + 0.005*"carers"
+2024-08-12 12:47:05,136 - topic #2 (0.333): 0.019*"’" + 0.007*"leaders" + 0.007*"Stockton" + 0.006*"needs" + 0.006*"plans" + 0.006*"senior" + 0.005*"good" + 0.005*"quality" + 0.005*"well" + 0.005*"17"
+2024-08-12 12:47:05,136 - topic diff=0.796237, rho=1.000000
+2024-08-12 12:47:05,136 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1044, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:47:05.136725', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:06,056 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:47:06,057 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:06,057 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:47:06,057 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:06,057 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:47:06,057 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:06,058 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:47:06,058 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:06,058 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:47:06,058 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:06,058 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:47:06,058 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:17,181 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:47:17,183 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)
+2024-08-12 12:47:17,184 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-08-12T12:47:17.183982', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:17,184 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:47:17,185 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:47:17,185 - using serial LDA version on this node
+2024-08-12 12:47:17,185 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:47:17,185 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:47:17,189 - -7.899 per-word bound, 238.8 perplexity estimate based on a held-out corpus of 1 documents with 2165 words
+2024-08-12 12:47:17,189 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:47:17,190 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"plans" + 0.006*"ensure" + 0.006*"However" + 0.005*"protection" + 0.005*"Stoke" + 0.005*"on-Trent" + 0.005*"progress"
+2024-08-12 12:47:17,190 - topic #1 (0.333): 0.020*"’" + 0.008*"on-Trent" + 0.008*"Stoke" + 0.008*"needs" + 0.008*"plans" + 0.007*"well" + 0.006*"protection" + 0.006*"However" + 0.005*"ensure" + 0.005*"leaders"
+2024-08-12 12:47:17,190 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"However" + 0.006*"on-Trent" + 0.006*"Stoke" + 0.006*"well" + 0.005*"plans" + 0.005*"ensure" + 0.005*"quality" + 0.004*"protection"
+2024-08-12 12:47:17,191 - topic diff=0.782161, rho=1.000000
+2024-08-12 12:47:17,191 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=986, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:47:17.191237', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:18,043 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:47:18,044 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:18,044 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:47:18,044 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:18,044 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:47:18,044 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:18,044 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:47:18,044 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:18,045 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:47:18,045 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:18,045 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:47:18,045 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:29,458 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:47:29,461 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)
+2024-08-12 12:47:29,461 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)", 'datetime': '2024-08-12T12:47:29.461417', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:29,462 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:47:29,462 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:47:29,462 - using serial LDA version on this node
+2024-08-12 12:47:29,463 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:47:29,463 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:47:29,467 - -8.175 per-word bound, 289.0 perplexity estimate based on a held-out corpus of 1 documents with 2286 words
+2024-08-12 12:47:29,467 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:47:29,468 - topic #0 (0.333): 0.018*"’" + 0.008*"progress" + 0.006*"well" + 0.006*"good" + 0.005*"effective" + 0.005*"practice" + 0.005*"leaders" + 0.004*"ensure" + 0.004*"carers" + 0.004*"Suffolk"
+2024-08-12 12:47:29,469 - topic #1 (0.333): 0.008*"’" + 0.008*"well" + 0.006*"progress" + 0.005*"ensure" + 0.004*"needs" + 0.004*"effective" + 0.004*"leaders" + 0.004*"good" + 0.004*"need" + 0.004*"high"
+2024-08-12 12:47:29,469 - topic #2 (0.333): 0.011*"’" + 0.005*"leaders" + 0.005*"well" + 0.005*"effective" + 0.005*"needs" + 0.004*"progress" + 0.004*"ensure" + 0.004*"good" + 0.003*"high" + 0.003*"plans"
+2024-08-12 12:47:29,469 - topic diff=0.740348, rho=1.000000
+2024-08-12 12:47:29,469 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:47:29.469398', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:30,878 - Got stderr: Aug 12, 2024 12:47:30 PM org.apache.pdfbox.pdmodel.font.FileSystemFontProvider loadDiskCache
+WARNING: New fonts found, font cache will be re-built
+Aug 12, 2024 12:47:30 PM org.apache.pdfbox.pdmodel.font.FileSystemFontProvider <init>
+WARNING: Building on-disk font cache, this may take a while
+Aug 12, 2024 12:47:30 PM org.apache.pdfbox.pdmodel.font.FileSystemFontProvider <init>
+WARNING: Finished building on-disk font cache, found 6 fonts
+Aug 12, 2024 12:47:30 PM org.apache.pdfbox.pdmodel.font.PDTrueTypeFont <init>
 WARNING: Using fallback font 'LiberationSans' for 'TimesNewRomanPSMT'
 
-2024-08-05 08:41:02,504 - Inspection date 2019-04-08 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:02,504 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:02,504 - Inspection date 2019-04-08 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:02,504 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:02,505 - Inspection date 2019-04-08 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:02,505 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:02,505 - Inspection date 2019-04-08 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:02,505 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:02,505 - Inspection date 2019-04-08 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:02,505 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:02,506 - Inspection date 2019-04-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:02,506 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:04,133 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:04,136 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)
-2024-08-05 08:41:04,136 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-08-05T08:41:04.136553', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:04,137 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:04,137 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:04,137 - using serial LDA version on this node
-2024-08-05 08:41:04,138 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:04,138 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:04,142 - -8.060 per-word bound, 266.9 perplexity estimate based on a held-out corpus of 1 documents with 2409 words
-2024-08-05 08:41:04,142 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:04,143 - topic #0 (0.333): 0.020*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"quality" + 0.006*"Sunderland" + 0.005*"parents" + 0.004*"protection" + 0.004*"good" + 0.004*"experienced" + 0.004*"practice"
-2024-08-05 08:41:04,143 - topic #1 (0.333): 0.015*"’" + 0.007*"well" + 0.006*"Sunderland" + 0.006*"quality" + 0.005*"needs" + 0.005*"experienced" + 0.005*"robust" + 0.004*"good" + 0.004*"cared" + 0.004*"parents"
-2024-08-05 08:41:04,144 - topic #2 (0.333): 0.012*"’" + 0.006*"quality" + 0.006*"well" + 0.006*"needs" + 0.006*"council" + 0.005*"practice" + 0.005*"experienced" + 0.005*"protection" + 0.005*"TfC" + 0.005*"Sunderland"
-2024-08-05 08:41:04,144 - topic diff=0.785697, rho=1.000000
-2024-08-05 08:41:04,144 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1128, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:04.144417', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:05,304 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:05,305 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:05,305 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:05,305 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:05,305 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:05,305 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:05,306 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:05,306 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:05,306 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:05,306 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:05,306 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:05,306 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:07,028 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:07,030 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)
-2024-08-05 08:41:07,031 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-08-05T08:41:07.031011', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:07,031 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:07,032 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:07,032 - using serial LDA version on this node
-2024-08-05 08:41:07,032 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:07,032 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:07,036 - -7.963 per-word bound, 249.5 perplexity estimate based on a held-out corpus of 1 documents with 2111 words
-2024-08-05 08:41:07,036 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:07,037 - topic #0 (0.333): 0.014*"’" + 0.011*"well" + 0.011*"needs" + 0.007*"practice" + 0.007*"progress" + 0.006*"17" + 0.006*"good" + 0.005*"quality" + 0.005*"However" + 0.005*"carers"
-2024-08-05 08:41:07,037 - topic #1 (0.333): 0.015*"’" + 0.011*"needs" + 0.008*"practice" + 0.007*"well" + 0.007*"progress" + 0.007*"plans" + 0.005*"carers" + 0.005*"Surrey" + 0.005*"17" + 0.004*"supported"
-2024-08-05 08:41:07,037 - topic #2 (0.333): 0.010*"’" + 0.009*"well" + 0.006*"practice" + 0.006*"effective" + 0.005*"needs" + 0.005*"progress" + 0.005*"good" + 0.005*"quality" + 0.004*"plans" + 0.004*"2022"
-2024-08-05 08:41:07,038 - topic diff=0.763960, rho=1.000000
-2024-08-05 08:41:07,038 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1016, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:07.038176', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:08,062 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:08,062 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:08,063 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:08,063 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:08,063 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:08,063 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:08,064 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:08,064 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:08,064 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:08,064 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:08,065 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:08,065 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:10,176 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:10,179 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)
-2024-08-05 08:41:10,179 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-08-05T08:41:10.179291', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:10,180 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:10,180 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:10,180 - using serial LDA version on this node
-2024-08-05 08:41:10,181 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:10,181 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:10,184 - -7.829 per-word bound, 227.3 perplexity estimate based on a held-out corpus of 1 documents with 2229 words
-2024-08-05 08:41:10,184 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:10,185 - topic #0 (0.333): 0.010*"’" + 0.009*"needs" + 0.006*"well" + 0.006*"need" + 0.005*"Swindon" + 0.004*"health" + 0.004*"impact" + 0.004*"plans" + 0.004*"effective" + 0.003*"However"
-2024-08-05 08:41:10,186 - topic #1 (0.333): 0.026*"’" + 0.013*"needs" + 0.010*"Swindon" + 0.009*"well" + 0.009*"need" + 0.008*"always" + 0.007*"plans" + 0.006*"impact" + 0.006*"home" + 0.006*"many"
-2024-08-05 08:41:10,186 - topic #2 (0.333): 0.023*"’" + 0.015*"needs" + 0.009*"Swindon" + 0.009*"need" + 0.008*"well" + 0.007*"plans" + 0.006*"always" + 0.006*"17" + 0.005*"impact" + 0.005*"health"
-2024-08-05 08:41:10,186 - topic diff=0.867347, rho=1.000000
-2024-08-05 08:41:10,186 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=951, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:10.186479', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:11,173 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:11,173 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:11,173 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:11,174 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:11,174 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:11,174 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:11,174 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:11,174 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:11,174 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:11,174 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:11,175 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:11,175 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:12,880 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:12,882 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)
-2024-08-05 08:41:12,883 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-08-05T08:41:12.883181', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:12,884 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:12,884 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:12,884 - using serial LDA version on this node
-2024-08-05 08:41:12,884 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:12,885 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:12,888 - -7.941 per-word bound, 245.8 perplexity estimate based on a held-out corpus of 1 documents with 2491 words
-2024-08-05 08:41:12,888 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:12,890 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.005*"impact" + 0.005*"practice" + 0.005*"4" + 0.005*"plans" + 0.005*"experienced" + 0.005*"leaders" + 0.004*"quality" + 0.004*"understand"
-2024-08-05 08:41:12,890 - topic #1 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"impact" + 0.005*"risk" + 0.005*"experienced" + 0.005*"quality" + 0.005*"effective" + 0.005*"response" + 0.005*"15" + 0.005*"2023"
-2024-08-05 08:41:12,890 - topic #2 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"risk" + 0.006*"quality" + 0.006*"practice" + 0.005*"experiences" + 0.005*"Tameside" + 0.005*"2023" + 0.005*"impact" + 0.005*"response"
-2024-08-05 08:41:12,890 - topic diff=0.821596, rho=1.000000
-2024-08-05 08:41:12,890 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:12.890634', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:13,786 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:13,786 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:13,786 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:13,786 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:13,786 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:13,787 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:13,787 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:13,787 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:13,787 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:13,787 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:13,787 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:13,787 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:15,505 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:15,507 - built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)
-2024-08-05 08:41:15,507 - Dictionary lifecycle event {'msg': "built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)", 'datetime': '2024-08-05T08:41:15.507605', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:15,508 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:15,508 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:15,509 - using serial LDA version on this node
-2024-08-05 08:41:15,509 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:15,509 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:15,513 - -7.965 per-word bound, 249.9 perplexity estimate based on a held-out corpus of 1 documents with 2452 words
-2024-08-05 08:41:15,513 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:15,514 - topic #0 (0.333): 0.029*"’" + 0.010*"Telford" + 0.010*"needs" + 0.008*"Wrekin" + 0.007*"plans" + 0.007*"well" + 0.006*"benefit" + 0.006*"effective" + 0.006*"Family" + 0.005*"progress"
-2024-08-05 08:41:15,514 - topic #1 (0.333): 0.017*"’" + 0.014*"needs" + 0.007*"Wrekin" + 0.007*"Telford" + 0.006*"benefit" + 0.005*"Family" + 0.005*"well" + 0.005*"plans" + 0.004*"29" + 0.004*"3"
-2024-08-05 08:41:15,514 - topic #2 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"Wrekin" + 0.006*"Telford" + 0.005*"well" + 0.005*"effective" + 0.005*"benefit" + 0.005*"3" + 0.005*"live" + 0.005*"Family"
-2024-08-05 08:41:15,515 - topic diff=0.824103, rho=1.000000
-2024-08-05 08:41:15,515 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1077, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:15.515170', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:16,476 - Inspection date 2024-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:16,476 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:16,476 - Inspection date 2024-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:16,476 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:16,476 - Inspection date 2024-04-29 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:16,476 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:16,477 - Inspection date 2024-04-29 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:16,477 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:16,477 - Inspection date 2024-04-29 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:16,477 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:16,478 - Inspection date 2024-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:16,478 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:18,143 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:18,145 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)
-2024-08-05 08:41:18,146 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-08-05T08:41:18.145987', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:18,147 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:18,147 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:18,147 - using serial LDA version on this node
-2024-08-05 08:41:18,147 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:18,147 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:18,151 - -8.139 per-word bound, 281.8 perplexity estimate based on a held-out corpus of 1 documents with 2160 words
-2024-08-05 08:41:18,151 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:18,153 - topic #0 (0.333): 0.017*"’" + 0.009*"well" + 0.006*"carers" + 0.005*"practice" + 0.004*"needs" + 0.004*"need" + 0.004*"ensure" + 0.004*"leaders" + 0.004*"effective" + 0.004*"protection"
-2024-08-05 08:41:18,153 - topic #1 (0.333): 0.011*"’" + 0.007*"well" + 0.005*"carers" + 0.005*"need" + 0.004*"needs" + 0.004*"practice" + 0.004*"parents" + 0.003*"quality" + 0.003*"ensure" + 0.003*"effective"
-2024-08-05 08:41:18,153 - topic #2 (0.333): 0.010*"’" + 0.008*"well" + 0.005*"need" + 0.005*"carers" + 0.005*"Thurrock" + 0.004*"ensure" + 0.004*"needs" + 0.004*"leaders" + 0.003*"protect" + 0.003*"effective"
-2024-08-05 08:41:18,153 - topic diff=0.723538, rho=1.000000
-2024-08-05 08:41:18,153 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1138, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:18.153948', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:20,239 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:20,239 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:20,239 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:20,239 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:20,239 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:20,239 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:20,240 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:20,240 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:20,240 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:20,240 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:20,240 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:20,240 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:21,681 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:21,684 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)
-2024-08-05 08:41:21,684 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-08-05T08:41:21.684300', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:21,685 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:21,685 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:21,685 - using serial LDA version on this node
-2024-08-05 08:41:21,685 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:21,686 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:21,689 - -8.040 per-word bound, 263.3 perplexity estimate based on a held-out corpus of 1 documents with 2065 words
-2024-08-05 08:41:21,689 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:21,690 - topic #0 (0.333): 0.010*"well" + 0.009*"’" + 0.007*"Torbay" + 0.005*"effective" + 0.005*"good" + 0.005*"agencies" + 0.004*"progress" + 0.004*"needs" + 0.004*"2022" + 0.004*"team"
-2024-08-05 08:41:21,691 - topic #1 (0.333): 0.022*"’" + 0.009*"well" + 0.007*"Torbay" + 0.007*"good" + 0.006*"needs" + 0.005*"timely" + 0.005*"effective" + 0.004*"team" + 0.004*"April" + 0.004*"21"
-2024-08-05 08:41:21,691 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.007*"Torbay" + 0.007*"needs" + 0.006*"good" + 0.005*"1" + 0.005*"progress" + 0.004*"effective" + 0.004*"21" + 0.004*"education"
-2024-08-05 08:41:21,691 - topic diff=0.752379, rho=1.000000
-2024-08-05 08:41:21,691 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1054, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:21.691507', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:22,772 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:22,772 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:22,773 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:22,773 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:22,773 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:22,773 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:22,773 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:22,773 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:22,773 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:22,773 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:22,774 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:22,774 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:24,518 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:24,521 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)
-2024-08-05 08:41:24,521 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-08-05T08:41:24.521182', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:24,522 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:24,522 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:24,522 - using serial LDA version on this node
-2024-08-05 08:41:24,522 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:24,523 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:24,526 - -7.915 per-word bound, 241.3 perplexity estimate based on a held-out corpus of 1 documents with 2448 words
-2024-08-05 08:41:24,526 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:24,527 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.007*"Trafford" + 0.007*"quality" + 0.006*"leaders" + 0.006*"well" + 0.006*"plans" + 0.005*"impact" + 0.005*"2" + 0.005*"team"
-2024-08-05 08:41:24,528 - topic #1 (0.333): 0.010*"’" + 0.006*"needs" + 0.006*"Trafford" + 0.006*"well" + 0.006*"plans" + 0.005*"practice" + 0.005*"team" + 0.005*"leaders" + 0.004*"quality" + 0.004*"impact"
-2024-08-05 08:41:24,528 - topic #2 (0.333): 0.022*"’" + 0.011*"needs" + 0.009*"Trafford" + 0.009*"plans" + 0.008*"well" + 0.007*"quality" + 0.006*"practice" + 0.005*"placed" + 0.005*"leaders" + 0.005*"2022"
-2024-08-05 08:41:24,528 - topic diff=0.834877, rho=1.000000
-2024-08-05 08:41:24,528 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:24.528535', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:25,535 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:25,535 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:25,535 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:25,535 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:25,536 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:25,536 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:25,536 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:25,536 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:25,536 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:25,536 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:25,536 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:25,536 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:27,497 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:27,499 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions)
-2024-08-05 08:41:27,500 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-08-05T08:41:27.500184', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:27,501 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:27,501 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:27,501 - using serial LDA version on this node
-2024-08-05 08:41:27,502 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:27,502 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:27,506 - -8.052 per-word bound, 265.4 perplexity estimate based on a held-out corpus of 1 documents with 2626 words
-2024-08-05 08:41:27,506 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:27,507 - topic #0 (0.333): 0.021*"’" + 0.007*"Walsall" + 0.007*"needs" + 0.006*"leaders" + 0.005*"information" + 0.005*"Senior" + 0.005*"well" + 0.005*"oversight" + 0.004*"plans" + 0.004*"carers"
-2024-08-05 08:41:27,507 - topic #1 (0.333): 0.024*"’" + 0.008*"leaders" + 0.007*"well" + 0.007*"needs" + 0.006*"4" + 0.005*"good" + 0.004*"Walsall" + 0.004*"oversight" + 0.004*"information" + 0.004*"positive"
-2024-08-05 08:41:27,507 - topic #2 (0.333): 0.017*"’" + 0.007*"leaders" + 0.005*"needs" + 0.005*"Walsall" + 0.004*"well" + 0.004*"2021" + 0.004*"need" + 0.004*"oversight" + 0.004*"information" + 0.004*"good"
-2024-08-05 08:41:27,508 - topic diff=0.816680, rho=1.000000
-2024-08-05 08:41:27,508 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1162, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:27.508265', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:28,493 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:28,493 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:28,493 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:28,493 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:28,493 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:28,494 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:28,494 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:28,494 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:28,494 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:28,494 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:28,494 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:28,494 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:30,108 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:30,111 - built Dictionary<1158 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2700 corpus positions)
-2024-08-05 08:41:30,111 - Dictionary lifecycle event {'msg': 'built Dictionary<1158 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2700 corpus positions)', 'datetime': '2024-08-05T08:41:30.111533', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:30,112 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:30,112 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:30,113 - using serial LDA version on this node
-2024-08-05 08:41:30,113 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:30,113 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:30,117 - -8.030 per-word bound, 261.3 perplexity estimate based on a held-out corpus of 1 documents with 2700 words
-2024-08-05 08:41:30,117 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:30,118 - topic #0 (0.333): 0.013*"’" + 0.006*"Warrington" + 0.006*"needs" + 0.006*"experiences" + 0.006*"well" + 0.005*"leaders" + 0.005*"effective" + 0.005*"10" + 0.005*"practice" + 0.004*"14"
-2024-08-05 08:41:30,119 - topic #1 (0.333): 0.018*"’" + 0.007*"needs" + 0.006*"practice" + 0.006*"Warrington" + 0.006*"leaders" + 0.006*"well" + 0.006*"plans" + 0.005*"effective" + 0.005*"experiences" + 0.004*"2024"
-2024-08-05 08:41:30,119 - topic #2 (0.333): 0.024*"’" + 0.008*"needs" + 0.007*"Warrington" + 0.007*"experiences" + 0.007*"effective" + 0.006*"carers" + 0.005*"14" + 0.005*"2024" + 0.005*"leaders" + 0.005*"plans"
-2024-08-05 08:41:30,119 - topic diff=0.812586, rho=1.000000
-2024-08-05 08:41:30,119 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1158, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:30.119486', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:31,470 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:31,470 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:31,471 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:31,471 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:31,471 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:31,471 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:31,471 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:31,471 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:31,471 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:31,471 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:31,472 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:31,472 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:33,105 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:33,107 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)
-2024-08-05 08:41:33,107 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-08-05T08:41:33.107801', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:33,108 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:33,108 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:33,109 - using serial LDA version on this node
-2024-08-05 08:41:33,109 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:33,109 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:33,113 - -8.002 per-word bound, 256.4 perplexity estimate based on a held-out corpus of 1 documents with 2113 words
-2024-08-05 08:41:33,113 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:33,114 - topic #0 (0.333): 0.014*"’" + 0.007*"plans" + 0.007*"well" + 0.006*"Warwickshire" + 0.006*"needs" + 0.005*"progress" + 0.005*"good" + 0.005*"carers" + 0.005*"Senior" + 0.005*"practice"
-2024-08-05 08:41:33,114 - topic #1 (0.333): 0.010*"’" + 0.006*"plans" + 0.006*"Warwickshire" + 0.006*"needs" + 0.006*"well" + 0.004*"clear" + 0.004*"practice" + 0.004*"good" + 0.004*"supported" + 0.004*"quality"
-2024-08-05 08:41:33,115 - topic #2 (0.333): 0.011*"’" + 0.008*"needs" + 0.007*"well" + 0.005*"practice" + 0.005*"plans" + 0.005*"3" + 0.005*"Warwickshire" + 0.004*"carers" + 0.004*"ensure" + 0.004*"good"
-2024-08-05 08:41:33,115 - topic diff=0.753478, rho=1.000000
-2024-08-05 08:41:33,115 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1040, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:33.115355', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:34,000 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:34,001 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:34,001 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:34,001 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:34,001 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:34,001 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:34,001 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:34,002 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:34,002 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:34,002 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:34,002 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:34,002 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:35,371 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:35,374 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)
-2024-08-05 08:41:35,374 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-08-05T08:41:35.374565', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:35,375 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:35,375 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:35,375 - using serial LDA version on this node
-2024-08-05 08:41:35,376 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:35,376 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:35,380 - -8.106 per-word bound, 275.6 perplexity estimate based on a held-out corpus of 1 documents with 2146 words
-2024-08-05 08:41:35,380 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:35,381 - topic #0 (0.333): 0.017*"’" + 0.008*"West" + 0.007*"Berkshire" + 0.005*"well" + 0.005*"plans" + 0.005*"need" + 0.005*"education" + 0.004*"needs" + 0.004*"14" + 0.004*"early"
-2024-08-05 08:41:35,381 - topic #1 (0.333): 0.015*"’" + 0.007*"well" + 0.006*"Berkshire" + 0.005*"West" + 0.005*"18" + 0.004*"needs" + 0.004*"agency" + 0.004*"working" + 0.004*"plans" + 0.004*"practice"
-2024-08-05 08:41:35,382 - topic #2 (0.333): 0.009*"’" + 0.005*"West" + 0.005*"Berkshire" + 0.004*"well" + 0.004*"ensure" + 0.003*"March" + 0.003*"2022" + 0.003*"need" + 0.003*"working" + 0.003*"needs"
-2024-08-05 08:41:35,382 - topic diff=0.730204, rho=1.000000
-2024-08-05 08:41:35,382 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:35.382351', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:36,227 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:36,228 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:36,228 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:36,228 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:36,228 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:36,228 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:36,229 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:36,229 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:36,229 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:36,229 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:36,229 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:36,229 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:37,648 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:37,650 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)
-2024-08-05 08:41:37,651 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-08-05T08:41:37.651047', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:37,652 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:37,652 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:37,652 - using serial LDA version on this node
-2024-08-05 08:41:37,652 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:37,652 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:37,656 - -8.039 per-word bound, 263.0 perplexity estimate based on a held-out corpus of 1 documents with 2224 words
-2024-08-05 08:41:37,656 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:37,658 - topic #0 (0.333): 0.014*"’" + 0.006*"Northamptonshire" + 0.006*"quality" + 0.005*"West" + 0.005*"practice" + 0.004*"well" + 0.004*"plans" + 0.004*"NCT" + 0.004*"impact" + 0.004*"14"
-2024-08-05 08:41:37,658 - topic #1 (0.333): 0.010*"’" + 0.007*"Northamptonshire" + 0.006*"well" + 0.006*"West" + 0.005*"practice" + 0.005*"needs" + 0.005*"quality" + 0.004*"experiences" + 0.004*"NCT" + 0.004*"need"
-2024-08-05 08:41:37,658 - topic #2 (0.333): 0.023*"’" + 0.009*"Northamptonshire" + 0.007*"quality" + 0.007*"West" + 0.007*"well" + 0.005*"needs" + 0.005*"practice" + 0.005*"NCT" + 0.005*"impact" + 0.005*"However"
-2024-08-05 08:41:37,658 - topic diff=0.775337, rho=1.000000
-2024-08-05 08:41:37,658 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1087, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:37.658791', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:38,653 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:38,654 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:38,654 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:38,654 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:38,654 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:38,654 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:38,655 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:38,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:38,655 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:38,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:38,655 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:38,655 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:40,100 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:40,103 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
-2024-08-05 08:41:40,103 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-08-05T08:41:40.103890', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:40,105 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:40,105 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:40,105 - using serial LDA version on this node
-2024-08-05 08:41:40,105 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:40,105 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:40,109 - -8.127 per-word bound, 279.6 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
-2024-08-05 08:41:40,110 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:40,111 - topic #0 (0.333): 0.016*"’" + 0.006*"needs" + 0.006*"plans" + 0.005*"supported" + 0.005*"well" + 0.005*"education" + 0.004*"Sussex" + 0.004*"24" + 0.004*"practice" + 0.004*"number"
-2024-08-05 08:41:40,111 - topic #1 (0.333): 0.011*"’" + 0.006*"plans" + 0.006*"well" + 0.005*"West" + 0.004*"Sussex" + 0.004*"health" + 0.004*"impact" + 0.004*"13" + 0.004*"needs" + 0.004*"number"
-2024-08-05 08:41:40,111 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"13" + 0.006*"plans" + 0.006*"Sussex" + 0.006*"West" + 0.005*"quality" + 0.005*"number" + 0.004*"practice"
-2024-08-05 08:41:40,111 - topic diff=0.804039, rho=1.000000
-2024-08-05 08:41:40,112 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1233, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:40.112026', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:41,171 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:41,172 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:41,172 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:41,172 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:41,172 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:41,173 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:41,173 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:41,173 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:41,173 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:41,173 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:41,174 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:41,174 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:42,860 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:42,863 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)
-2024-08-05 08:41:42,863 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)", 'datetime': '2024-08-05T08:41:42.863329', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:42,864 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:42,864 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:42,864 - using serial LDA version on this node
-2024-08-05 08:41:42,865 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:42,865 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:42,868 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 2451 words
-2024-08-05 08:41:42,868 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:42,870 - topic #0 (0.333): 0.012*"’" + 0.008*"needs" + 0.007*"plans" + 0.007*"Furness" + 0.006*"appropriate" + 0.005*"need" + 0.005*"protection" + 0.005*"Westmorland" + 0.005*"quality" + 0.005*"22"
-2024-08-05 08:41:42,870 - topic #1 (0.333): 0.012*"’" + 0.007*"Westmorland" + 0.007*"plans" + 0.006*"needs" + 0.005*"Furness" + 0.005*"quality" + 0.004*"well" + 0.004*"need" + 0.004*"appropriate" + 0.004*"response"
-2024-08-05 08:41:42,870 - topic #2 (0.333): 0.014*"’" + 0.008*"plans" + 0.007*"need" + 0.007*"Furness" + 0.007*"Westmorland" + 0.006*"appropriate" + 0.006*"needs" + 0.005*"protection" + 0.005*"progress" + 0.005*"quality"
-2024-08-05 08:41:42,870 - topic diff=0.804792, rho=1.000000
-2024-08-05 08:41:42,870 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:42.870934', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:43,804 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:43,804 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:43,805 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:43,805 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:43,805 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:43,805 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:43,806 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:43,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:43,806 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:43,806 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:43,806 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:43,807 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:45,401 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:45,403 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)
-2024-08-05 08:41:45,403 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-08-05T08:41:45.403720', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:45,404 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:45,404 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:45,405 - using serial LDA version on this node
-2024-08-05 08:41:45,405 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:45,405 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:45,409 - -7.955 per-word bound, 248.2 perplexity estimate based on a held-out corpus of 1 documents with 2416 words
-2024-08-05 08:41:45,409 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:45,410 - topic #0 (0.333): 0.015*"’" + 0.008*"May" + 0.007*"plans" + 0.006*"practice" + 0.006*"needs" + 0.006*"Wigan" + 0.005*"quality" + 0.005*"appropriate" + 0.004*"9" + 0.004*"including"
-2024-08-05 08:41:45,411 - topic #1 (0.333): 0.010*"’" + 0.006*"May" + 0.005*"needs" + 0.005*"practice" + 0.005*"appropriate" + 0.004*"Wigan" + 0.004*"plans" + 0.004*"leaders" + 0.004*"timely" + 0.004*"quality"
-2024-08-05 08:41:45,411 - topic #2 (0.333): 0.011*"’" + 0.007*"practice" + 0.007*"May" + 0.007*"quality" + 0.007*"plans" + 0.006*"Wigan" + 0.005*"needs" + 0.005*"appropriate" + 0.005*"leaders" + 0.005*"timely"
-2024-08-05 08:41:45,411 - topic diff=0.793441, rho=1.000000
-2024-08-05 08:41:45,411 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:45.411531', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:46,390 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:46,390 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:46,390 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:46,390 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:46,391 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:46,391 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:46,391 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:46,391 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:46,391 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:46,391 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:46,391 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:46,392 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:48,034 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:48,037 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)
-2024-08-05 08:41:48,037 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-08-05T08:41:48.037525', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:48,038 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:48,038 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:48,038 - using serial LDA version on this node
-2024-08-05 08:41:48,039 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:48,039 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:48,043 - -7.958 per-word bound, 248.7 perplexity estimate based on a held-out corpus of 1 documents with 2600 words
-2024-08-05 08:41:48,043 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:48,044 - topic #0 (0.333): 0.016*"’" + 0.012*"well" + 0.009*"needs" + 0.007*"need" + 0.007*"including" + 0.006*"supported" + 0.006*"parents" + 0.006*"risk" + 0.006*"Wiltshire" + 0.006*"progress"
-2024-08-05 08:41:48,044 - topic #1 (0.333): 0.017*"’" + 0.010*"well" + 0.006*"parents" + 0.006*"progress" + 0.006*"plans" + 0.006*"needs" + 0.006*"supported" + 0.005*"Wiltshire" + 0.004*"need" + 0.004*"ensure"
-2024-08-05 08:41:48,044 - topic #2 (0.333): 0.013*"’" + 0.011*"well" + 0.007*"need" + 0.006*"quality" + 0.006*"risk" + 0.006*"Wiltshire" + 0.006*"needs" + 0.006*"progress" + 0.005*"ensure" + 0.005*"including"
-2024-08-05 08:41:48,045 - topic diff=0.829298, rho=1.000000
-2024-08-05 08:41:48,045 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1090, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:48.045195', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:49,046 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:49,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:49,047 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:49,047 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:49,048 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:49,048 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:49,048 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:49,048 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:49,049 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:49,049 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:49,049 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:49,049 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:50,833 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:50,836 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
-2024-08-05 08:41:50,836 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-08-05T08:41:50.836337', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:50,837 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:50,837 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:50,837 - using serial LDA version on this node
-2024-08-05 08:41:50,838 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:50,838 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:50,841 - -7.906 per-word bound, 239.9 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
-2024-08-05 08:41:50,841 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:50,843 - topic #0 (0.333): 0.010*"needs" + 0.009*"’" + 0.007*"Wirral" + 0.006*"plans" + 0.006*"well" + 0.005*"ensure" + 0.005*"18" + 0.005*"risk" + 0.005*"small" + 0.005*"September"
-2024-08-05 08:41:50,843 - topic #1 (0.333): 0.014*"’" + 0.009*"needs" + 0.009*"ensure" + 0.006*"plans" + 0.006*"practice" + 0.006*"number" + 0.006*"Wirral" + 0.005*"family" + 0.005*"small" + 0.005*"response"
-2024-08-05 08:41:50,843 - topic #2 (0.333): 0.009*"’" + 0.009*"Wirral" + 0.009*"needs" + 0.007*"plans" + 0.007*"ensure" + 0.007*"practice" + 0.006*"well" + 0.005*"29" + 0.005*"good" + 0.005*"number"
-2024-08-05 08:41:50,843 - topic diff=0.804636, rho=1.000000
-2024-08-05 08:41:50,843 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:50.843708', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:52,094 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:52,094 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:52,094 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:52,095 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:52,095 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:52,095 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:52,095 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:52,095 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:52,096 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:52,096 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:52,096 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:52,096 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:53,857 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:53,860 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)
-2024-08-05 08:41:53,860 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-08-05T08:41:53.860553', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:53,861 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:53,861 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:53,861 - using serial LDA version on this node
-2024-08-05 08:41:53,862 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:53,862 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:53,866 - -8.057 per-word bound, 266.3 perplexity estimate based on a held-out corpus of 1 documents with 2214 words
-2024-08-05 08:41:53,866 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:53,867 - topic #0 (0.333): 0.013*"’" + 0.007*"effective" + 0.006*"plans" + 0.006*"provided" + 0.005*"impact" + 0.005*"well" + 0.005*"needs" + 0.005*"parents" + 0.005*"6" + 0.004*"Council"
-2024-08-05 08:41:53,867 - topic #1 (0.333): 0.012*"’" + 0.007*"plans" + 0.006*"effective" + 0.005*"needs" + 0.005*"17" + 0.005*"well" + 0.005*"progress" + 0.005*"experiences" + 0.004*"quality" + 0.004*"March"
-2024-08-05 08:41:53,868 - topic #2 (0.333): 0.013*"’" + 0.007*"progress" + 0.007*"plans" + 0.007*"needs" + 0.005*"well" + 0.005*"provided" + 0.005*"experiences" + 0.005*"effective" + 0.005*"protection" + 0.005*"Wokingham"
-2024-08-05 08:41:53,868 - topic diff=0.753417, rho=1.000000
-2024-08-05 08:41:53,868 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1096, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:53.868286', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:54,742 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:54,742 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:54,742 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:54,742 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:54,743 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:54,743 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:54,743 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:54,743 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:54,743 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:54,743 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:54,744 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:54,744 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:56,427 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:56,429 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
-2024-08-05 08:41:56,430 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-08-05T08:41:56.429983', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:56,431 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:56,431 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:56,431 - using serial LDA version on this node
-2024-08-05 08:41:56,431 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:56,431 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:56,435 - -8.049 per-word bound, 264.9 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
-2024-08-05 08:41:56,435 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:56,436 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.005*"Wolverhampton" + 0.005*"quality" + 0.005*"28" + 0.005*"plans" + 0.004*"leaders" + 0.004*"strong" + 0.004*"effective" + 0.004*"receive"
-2024-08-05 08:41:56,437 - topic #1 (0.333): 0.017*"’" + 0.010*"needs" + 0.007*"effective" + 0.006*"Wolverhampton" + 0.005*"supported" + 0.005*"risks" + 0.005*"receive" + 0.005*"plans" + 0.005*"education" + 0.005*"strong"
-2024-08-05 08:41:56,437 - topic #2 (0.333): 0.012*"’" + 0.006*"effective" + 0.005*"needs" + 0.005*"Wolverhampton" + 0.005*"risks" + 0.005*"well" + 0.005*"plans" + 0.005*"risk" + 0.004*"quality" + 0.004*"leaders"
-2024-08-05 08:41:56,437 - topic diff=0.737279, rho=1.000000
-2024-08-05 08:41:56,437 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1095, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:56.437487', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:57,345 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:41:57,345 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:57,346 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:41:57,346 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:57,346 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:41:57,346 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:57,346 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:41:57,346 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:57,347 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:41:57,347 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:57,347 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:41:57,347 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:41:59,088 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-08-05 08:41:59,090 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)
-2024-08-05 08:41:59,090 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-08-05T08:41:59.090889', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:41:59,091 - using symmetric alpha at 0.3333333333333333
-2024-08-05 08:41:59,092 - using symmetric eta at 0.3333333333333333
-2024-08-05 08:41:59,092 - using serial LDA version on this node
-2024-08-05 08:41:59,092 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-08-05 08:41:59,092 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-08-05 08:41:59,096 - -7.941 per-word bound, 245.8 perplexity estimate based on a held-out corpus of 1 documents with 2343 words
-2024-08-05 08:41:59,096 - PROGRESS: pass 0, at document #1/1
-2024-08-05 08:41:59,097 - topic #0 (0.333): 0.021*"’" + 0.009*"plans" + 0.009*"well" + 0.007*"progress" + 0.007*"needs" + 0.007*"Worcestershire" + 0.007*"leaders" + 0.007*"ensure" + 0.006*"appropriate" + 0.005*"living"
-2024-08-05 08:41:59,097 - topic #1 (0.333): 0.019*"’" + 0.010*"well" + 0.008*"plans" + 0.008*"needs" + 0.007*"Worcestershire" + 0.007*"progress" + 0.006*"leaders" + 0.005*"ensure" + 0.005*"appropriate" + 0.005*"experiences"
-2024-08-05 08:41:59,098 - topic #2 (0.333): 0.015*"’" + 0.008*"leaders" + 0.008*"needs" + 0.007*"Worcestershire" + 0.006*"well" + 0.005*"plans" + 0.005*"progress" + 0.005*"improve" + 0.005*"ensure" + 0.004*"PAs"
-2024-08-05 08:41:59,098 - topic diff=0.806956, rho=1.000000
-2024-08-05 08:41:59,098 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1041, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-05T08:41:59.098229', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul  9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-08-05 08:42:00,130 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-08-05 08:42:00,130 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:42:00,131 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-08-05 08:42:00,131 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:42:00,131 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-08-05 08:42:00,131 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:42:00,131 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
-2024-08-05 08:42:00,132 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:42:00,132 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
-2024-08-05 08:42:00,132 - Index(['judgement', 'grade'], dtype='object')
-2024-08-05 08:42:00,132 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-08-05 08:42:00,132 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:30,886 - Inspection date 2019-04-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:47:30,887 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:30,887 - Inspection date 2019-04-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:47:30,887 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:30,887 - Inspection date 2019-04-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:47:30,888 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:30,888 - Inspection date 2019-04-08 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:47:30,888 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:30,888 - Inspection date 2019-04-08 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:47:30,888 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:30,889 - Inspection date 2019-04-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:47:30,889 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:41,852 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:47:41,855 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)
+2024-08-12 12:47:41,856 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-08-12T12:47:41.856176', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:41,857 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:47:41,858 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:47:41,858 - using serial LDA version on this node
+2024-08-12 12:47:41,859 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:47:41,859 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:47:41,865 - -8.056 per-word bound, 266.2 perplexity estimate based on a held-out corpus of 1 documents with 2409 words
+2024-08-12 12:47:41,865 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:47:41,868 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"quality" + 0.005*"Sunderland" + 0.005*"result" + 0.005*"good" + 0.004*"council" + 0.004*"highly" + 0.004*"robust"
+2024-08-12 12:47:41,868 - topic #1 (0.333): 0.021*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"quality" + 0.007*"Sunderland" + 0.007*"experienced" + 0.005*"parents" + 0.005*"practice" + 0.005*"good" + 0.005*"risk"
+2024-08-12 12:47:41,868 - topic #2 (0.333): 0.009*"’" + 0.006*"quality" + 0.006*"well" + 0.004*"council" + 0.004*"protection" + 0.004*"highly" + 0.004*"practice" + 0.004*"TfC" + 0.004*"parents" + 0.004*"Sunderland"
+2024-08-12 12:47:41,868 - topic diff=0.789329, rho=1.000000
+2024-08-12 12:47:41,869 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1128, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:47:41.869010', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:42,976 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:47:42,977 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:42,977 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:47:42,977 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:42,977 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:47:42,978 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:42,978 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:47:42,978 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:42,978 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:47:42,979 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:42,979 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:47:42,979 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:53,343 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:47:53,345 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)
+2024-08-12 12:47:53,345 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-08-12T12:47:53.345567', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:53,346 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:47:53,346 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:47:53,346 - using serial LDA version on this node
+2024-08-12 12:47:53,347 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:47:53,347 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:47:53,350 - -7.964 per-word bound, 249.7 perplexity estimate based on a held-out corpus of 1 documents with 2111 words
+2024-08-12 12:47:53,350 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:47:53,352 - topic #0 (0.333): 0.014*"’" + 0.011*"needs" + 0.010*"well" + 0.009*"practice" + 0.008*"progress" + 0.006*"effective" + 0.005*"plans" + 0.005*"good" + 0.005*"However" + 0.005*"Surrey"
+2024-08-12 12:47:53,352 - topic #1 (0.333): 0.009*"’" + 0.009*"needs" + 0.008*"well" + 0.006*"practice" + 0.006*"progress" + 0.005*"carers" + 0.005*"plans" + 0.004*"Surrey" + 0.004*"receive" + 0.004*"good"
+2024-08-12 12:47:53,352 - topic #2 (0.333): 0.016*"’" + 0.010*"well" + 0.009*"needs" + 0.006*"17" + 0.006*"quality" + 0.006*"practice" + 0.005*"progress" + 0.005*"good" + 0.005*"plans" + 0.005*"effective"
+2024-08-12 12:47:53,352 - topic diff=0.762866, rho=1.000000
+2024-08-12 12:47:53,352 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1016, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:47:53.352849', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:47:54,356 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:47:54,357 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:54,357 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:47:54,357 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:54,357 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:47:54,357 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:54,358 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:47:54,358 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:54,358 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:47:54,358 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:47:54,358 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:47:54,358 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:05,037 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:48:05,039 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)
+2024-08-12 12:48:05,039 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-08-12T12:48:05.039307', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:05,040 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:48:05,040 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:48:05,040 - using serial LDA version on this node
+2024-08-12 12:48:05,040 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:48:05,041 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:48:05,044 - -7.833 per-word bound, 228.0 perplexity estimate based on a held-out corpus of 1 documents with 2229 words
+2024-08-12 12:48:05,044 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:48:05,045 - topic #0 (0.333): 0.019*"’" + 0.011*"needs" + 0.010*"well" + 0.007*"Swindon" + 0.007*"need" + 0.006*"always" + 0.006*"effective" + 0.006*"impact" + 0.005*"Council" + 0.005*"17"
+2024-08-12 12:48:05,045 - topic #1 (0.333): 0.022*"’" + 0.015*"needs" + 0.009*"Swindon" + 0.008*"plans" + 0.008*"well" + 0.007*"need" + 0.006*"impact" + 0.006*"always" + 0.006*"lack" + 0.005*"health"
+2024-08-12 12:48:05,046 - topic #2 (0.333): 0.024*"’" + 0.013*"needs" + 0.010*"need" + 0.010*"Swindon" + 0.007*"always" + 0.006*"well" + 0.006*"plans" + 0.006*"home" + 0.005*"health" + 0.005*"Borough"
+2024-08-12 12:48:05,046 - topic diff=0.825410, rho=1.000000
+2024-08-12 12:48:05,046 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=951, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:48:05.046377', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:06,097 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:48:06,097 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:06,098 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:48:06,098 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:06,098 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:48:06,098 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:06,098 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:48:06,098 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:06,099 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:48:06,099 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:06,099 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:48:06,099 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:18,103 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:48:18,105 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)
+2024-08-12 12:48:18,106 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-08-12T12:48:18.106088', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:18,107 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:48:18,107 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:48:18,107 - using serial LDA version on this node
+2024-08-12 12:48:18,107 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:48:18,108 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:48:18,111 - -7.944 per-word bound, 246.3 perplexity estimate based on a held-out corpus of 1 documents with 2491 words
+2024-08-12 12:48:18,111 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:48:18,113 - topic #0 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"risk" + 0.006*"impact" + 0.006*"quality" + 0.006*"2023" + 0.005*"response" + 0.005*"Tameside" + 0.005*"4" + 0.005*"understand"
+2024-08-12 12:48:18,113 - topic #1 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"impact" + 0.006*"risk" + 0.006*"practice" + 0.005*"15" + 0.005*"quality" + 0.005*"experienced" + 0.005*"experiences" + 0.005*"response"
+2024-08-12 12:48:18,113 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.005*"experienced" + 0.005*"impact" + 0.005*"quality" + 0.005*"effective" + 0.005*"4" + 0.004*"risk" + 0.004*"progress" + 0.004*"plans"
+2024-08-12 12:48:18,113 - topic diff=0.822315, rho=1.000000
+2024-08-12 12:48:18,113 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:48:18.113752', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:18,974 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:48:18,974 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:18,974 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:48:18,974 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:18,975 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:48:18,975 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:18,975 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:48:18,975 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:18,975 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:48:18,975 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:18,975 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:48:18,976 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:31,309 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:48:31,311 - built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)
+2024-08-12 12:48:31,312 - Dictionary lifecycle event {'msg': "built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)", 'datetime': '2024-08-12T12:48:31.311978', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:31,313 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:48:31,313 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:48:31,313 - using serial LDA version on this node
+2024-08-12 12:48:31,313 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:48:31,313 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:48:31,317 - -7.971 per-word bound, 250.9 perplexity estimate based on a held-out corpus of 1 documents with 2452 words
+2024-08-12 12:48:31,317 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:48:31,318 - topic #0 (0.333): 0.022*"’" + 0.012*"needs" + 0.008*"Wrekin" + 0.008*"Telford" + 0.007*"benefit" + 0.007*"well" + 0.006*"Family" + 0.006*"plans" + 0.005*"effective" + 0.005*"29"
+2024-08-12 12:48:31,319 - topic #1 (0.333): 0.023*"’" + 0.009*"Wrekin" + 0.008*"needs" + 0.008*"Telford" + 0.006*"plans" + 0.005*"benefit" + 0.005*"effective" + 0.005*"well" + 0.005*"Family" + 0.005*"3"
+2024-08-12 12:48:31,319 - topic #2 (0.333): 0.018*"’" + 0.013*"needs" + 0.007*"Telford" + 0.006*"Wrekin" + 0.005*"benefit" + 0.005*"well" + 0.005*"effective" + 0.005*"Family" + 0.004*"2024" + 0.004*"development"
+2024-08-12 12:48:31,319 - topic diff=0.819769, rho=1.000000
+2024-08-12 12:48:31,319 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1077, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:48:31.319527', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:32,516 - Inspection date 2024-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:48:32,516 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:32,517 - Inspection date 2024-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:48:32,517 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:32,517 - Inspection date 2024-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:48:32,517 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:32,517 - Inspection date 2024-04-29 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:48:32,517 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:32,518 - Inspection date 2024-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:48:32,518 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:32,518 - Inspection date 2024-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:48:32,518 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:43,233 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:48:43,235 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)
+2024-08-12 12:48:43,236 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-08-12T12:48:43.235977', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:43,236 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:48:43,237 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:48:43,237 - using serial LDA version on this node
+2024-08-12 12:48:43,237 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:48:43,237 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:48:43,241 - -8.139 per-word bound, 281.9 perplexity estimate based on a held-out corpus of 1 documents with 2160 words
+2024-08-12 12:48:43,241 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:48:43,243 - topic #0 (0.333): 0.013*"’" + 0.010*"well" + 0.005*"need" + 0.005*"carers" + 0.005*"practice" + 0.004*"ensure" + 0.004*"effective" + 0.004*"Thurrock" + 0.004*"needs" + 0.003*"impact"
+2024-08-12 12:48:43,243 - topic #1 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"carers" + 0.005*"needs" + 0.005*"need" + 0.004*"leaders" + 0.004*"Thurrock" + 0.004*"protection" + 0.004*"effective" + 0.004*"practice"
+2024-08-12 12:48:43,243 - topic #2 (0.333): 0.009*"’" + 0.007*"well" + 0.005*"carers" + 0.005*"need" + 0.004*"ensure" + 0.004*"needs" + 0.004*"leaders" + 0.003*"practice" + 0.003*"protection" + 0.003*"quality"
+2024-08-12 12:48:43,243 - topic diff=0.728678, rho=1.000000
+2024-08-12 12:48:43,243 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1138, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:48:43.243822', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:45,002 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:48:45,002 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:45,002 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:48:45,003 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:45,003 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:48:45,003 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:45,003 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:48:45,003 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:45,004 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:48:45,004 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:45,004 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:48:45,004 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:54,639 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:48:54,641 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)
+2024-08-12 12:48:54,641 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-08-12T12:48:54.641339', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:54,642 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:48:54,642 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:48:54,642 - using serial LDA version on this node
+2024-08-12 12:48:54,643 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:48:54,643 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:48:54,646 - -8.039 per-word bound, 263.0 perplexity estimate based on a held-out corpus of 1 documents with 2065 words
+2024-08-12 12:48:54,647 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:48:54,648 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.006*"needs" + 0.006*"Torbay" + 0.005*"good" + 0.005*"effective" + 0.005*"team" + 0.005*"21" + 0.005*"progress" + 0.004*"agencies"
+2024-08-12 12:48:54,648 - topic #1 (0.333): 0.014*"’" + 0.011*"Torbay" + 0.010*"well" + 0.006*"good" + 0.006*"needs" + 0.005*"effective" + 0.004*"1" + 0.004*"21" + 0.004*"timely" + 0.004*"ensure"
+2024-08-12 12:48:54,648 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"Torbay" + 0.006*"good" + 0.005*"needs" + 0.005*"timely" + 0.004*"effective" + 0.004*"quality" + 0.004*"team" + 0.004*"agencies"
+2024-08-12 12:48:54,648 - topic diff=0.744022, rho=1.000000
+2024-08-12 12:48:54,649 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1054, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:48:54.648984', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:48:55,633 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:48:55,633 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:55,633 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:48:55,633 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:55,633 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:48:55,633 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:55,634 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:48:55,634 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:55,634 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:48:55,634 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:48:55,634 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:48:55,634 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:08,134 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:49:08,136 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)
+2024-08-12 12:49:08,136 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-08-12T12:49:08.136539', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:08,138 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:49:08,138 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:49:08,139 - using serial LDA version on this node
+2024-08-12 12:49:08,139 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:49:08,139 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:49:08,146 - -7.910 per-word bound, 240.5 perplexity estimate based on a held-out corpus of 1 documents with 2448 words
+2024-08-12 12:49:08,146 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:49:08,148 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.009*"Trafford" + 0.007*"well" + 0.007*"plans" + 0.006*"leaders" + 0.006*"quality" + 0.006*"practice" + 0.006*"team" + 0.005*"impact"
+2024-08-12 12:49:08,148 - topic #1 (0.333): 0.014*"’" + 0.009*"Trafford" + 0.008*"needs" + 0.007*"well" + 0.007*"plans" + 0.007*"quality" + 0.005*"practice" + 0.005*"leaders" + 0.005*"team" + 0.004*"2"
+2024-08-12 12:49:08,148 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"plans" + 0.006*"well" + 0.006*"quality" + 0.006*"Trafford" + 0.005*"leaders" + 0.005*"impact" + 0.005*"21" + 0.005*"placed"
+2024-08-12 12:49:08,148 - topic diff=0.824869, rho=1.000000
+2024-08-12 12:49:08,149 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:49:08.149015', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:08,993 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:49:08,993 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:08,993 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:49:08,993 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:08,994 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:49:08,994 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:08,994 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:49:08,994 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:08,994 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:49:08,994 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:08,995 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:49:08,995 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:20,762 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:49:20,765 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions)
+2024-08-12 12:49:20,765 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-08-12T12:49:20.765135', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:20,766 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:49:20,766 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:49:20,766 - using serial LDA version on this node
+2024-08-12 12:49:20,767 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:49:20,767 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:49:20,770 - -8.053 per-word bound, 265.5 perplexity estimate based on a held-out corpus of 1 documents with 2626 words
+2024-08-12 12:49:20,771 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:49:20,772 - topic #0 (0.333): 0.017*"’" + 0.006*"needs" + 0.005*"information" + 0.005*"well" + 0.005*"leaders" + 0.005*"Walsall" + 0.004*"2021" + 0.004*"4" + 0.004*"progress" + 0.004*"risk"
+2024-08-12 12:49:20,772 - topic #1 (0.333): 0.027*"’" + 0.008*"leaders" + 0.007*"needs" + 0.006*"well" + 0.005*"Walsall" + 0.005*"4" + 0.005*"Senior" + 0.005*"good" + 0.005*"oversight" + 0.004*"information"
+2024-08-12 12:49:20,772 - topic #2 (0.333): 0.017*"’" + 0.008*"leaders" + 0.006*"Walsall" + 0.006*"well" + 0.006*"needs" + 0.005*"oversight" + 0.004*"Senior" + 0.004*"4" + 0.004*"good" + 0.004*"information"
+2024-08-12 12:49:20,772 - topic diff=0.818866, rho=1.000000
+2024-08-12 12:49:20,772 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1162, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:49:20.772971', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:21,749 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:49:21,750 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:21,750 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:49:21,750 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:21,750 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:49:21,750 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:21,751 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:49:21,751 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:21,751 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:49:21,751 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:21,752 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:49:21,752 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:36,066 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:49:36,068 - built Dictionary<1158 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2700 corpus positions)
+2024-08-12 12:49:36,069 - Dictionary lifecycle event {'msg': 'built Dictionary<1158 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2700 corpus positions)', 'datetime': '2024-08-12T12:49:36.069001', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:36,070 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:49:36,070 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:49:36,070 - using serial LDA version on this node
+2024-08-12 12:49:36,070 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:49:36,071 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:49:36,074 - -8.029 per-word bound, 261.2 perplexity estimate based on a held-out corpus of 1 documents with 2700 words
+2024-08-12 12:49:36,075 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:49:36,076 - topic #0 (0.333): 0.021*"’" + 0.007*"needs" + 0.007*"effective" + 0.006*"experiences" + 0.006*"practice" + 0.006*"Warrington" + 0.006*"well" + 0.005*"10" + 0.005*"leaders" + 0.005*"14"
+2024-08-12 12:49:36,076 - topic #1 (0.333): 0.017*"’" + 0.007*"Warrington" + 0.006*"experiences" + 0.005*"needs" + 0.005*"well" + 0.005*"leaders" + 0.005*"practice" + 0.004*"2024" + 0.004*"carers" + 0.004*"plans"
+2024-08-12 12:49:36,076 - topic #2 (0.333): 0.019*"’" + 0.008*"needs" + 0.008*"Warrington" + 0.007*"effective" + 0.007*"experiences" + 0.006*"leaders" + 0.005*"plans" + 0.005*"well" + 0.005*"14" + 0.005*"carers"
+2024-08-12 12:49:36,076 - topic diff=0.806312, rho=1.000000
+2024-08-12 12:49:36,077 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1158, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:49:36.077005', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:37,015 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:49:37,015 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:37,015 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:49:37,015 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:37,016 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:49:37,016 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:37,016 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:49:37,016 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:37,016 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:49:37,016 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:37,017 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:49:37,017 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:47,023 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:49:47,025 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)
+2024-08-12 12:49:47,025 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-08-12T12:49:47.025420', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:47,026 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:49:47,026 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:49:47,026 - using serial LDA version on this node
+2024-08-12 12:49:47,027 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:49:47,027 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:49:47,030 - -8.007 per-word bound, 257.3 perplexity estimate based on a held-out corpus of 1 documents with 2113 words
+2024-08-12 12:49:47,030 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:49:47,032 - topic #0 (0.333): 0.011*"’" + 0.006*"Warwickshire" + 0.006*"well" + 0.006*"plans" + 0.005*"needs" + 0.004*"information" + 0.004*"progress" + 0.004*"effective" + 0.004*"supported" + 0.004*"ensure"
+2024-08-12 12:49:47,032 - topic #1 (0.333): 0.013*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"Warwickshire" + 0.006*"plans" + 0.006*"practice" + 0.005*"carers" + 0.005*"good" + 0.005*"3" + 0.005*"Senior"
+2024-08-12 12:49:47,032 - topic #2 (0.333): 0.011*"’" + 0.007*"plans" + 0.006*"needs" + 0.005*"Warwickshire" + 0.004*"practice" + 0.004*"well" + 0.004*"good" + 0.004*"clear" + 0.004*"progress" + 0.004*"education"
+2024-08-12 12:49:47,032 - topic diff=0.764607, rho=1.000000
+2024-08-12 12:49:47,032 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1040, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:49:47.032793', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:47,888 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:49:47,888 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:47,889 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:49:47,889 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:47,889 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:49:47,889 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:47,889 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:49:47,889 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:47,889 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:49:47,890 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:47,890 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:49:47,890 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:57,569 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:49:57,572 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)
+2024-08-12 12:49:57,572 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-08-12T12:49:57.572964', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:57,574 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:49:57,574 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:49:57,575 - using serial LDA version on this node
+2024-08-12 12:49:57,575 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:49:57,575 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:49:57,579 - -8.111 per-word bound, 276.4 perplexity estimate based on a held-out corpus of 1 documents with 2146 words
+2024-08-12 12:49:57,579 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:49:57,581 - topic #0 (0.333): 0.014*"’" + 0.007*"West" + 0.006*"Berkshire" + 0.006*"well" + 0.005*"plans" + 0.004*"need" + 0.004*"needs" + 0.004*"early" + 0.004*"working" + 0.004*"progress"
+2024-08-12 12:49:57,581 - topic #1 (0.333): 0.014*"’" + 0.007*"West" + 0.006*"Berkshire" + 0.006*"well" + 0.004*"need" + 0.004*"14" + 0.004*"agency" + 0.004*"plans" + 0.004*"needs" + 0.004*"education"
+2024-08-12 12:49:57,581 - topic #2 (0.333): 0.015*"’" + 0.006*"well" + 0.006*"Berkshire" + 0.005*"West" + 0.005*"18" + 0.004*"2022" + 0.004*"needs" + 0.004*"agency" + 0.004*"March" + 0.004*"early"
+2024-08-12 12:49:57,581 - topic diff=0.712066, rho=1.000000
+2024-08-12 12:49:57,581 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:49:57.581853', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:49:58,413 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:49:58,413 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:58,413 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:49:58,413 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:58,414 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:49:58,414 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:58,414 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:49:58,414 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:58,414 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:49:58,414 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:49:58,415 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:49:58,415 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:08,927 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:50:08,929 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)
+2024-08-12 12:50:08,929 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-08-12T12:50:08.929498', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:08,930 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:50:08,930 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:50:08,930 - using serial LDA version on this node
+2024-08-12 12:50:08,931 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:50:08,931 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:50:08,935 - -8.044 per-word bound, 263.9 perplexity estimate based on a held-out corpus of 1 documents with 2224 words
+2024-08-12 12:50:08,935 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:50:08,936 - topic #0 (0.333): 0.017*"’" + 0.007*"quality" + 0.006*"West" + 0.006*"Northamptonshire" + 0.006*"well" + 0.005*"NCT" + 0.005*"practice" + 0.004*"14" + 0.004*"plans" + 0.004*"health"
+2024-08-12 12:50:08,936 - topic #1 (0.333): 0.019*"’" + 0.009*"Northamptonshire" + 0.007*"West" + 0.007*"quality" + 0.006*"well" + 0.005*"3" + 0.005*"needs" + 0.005*"practice" + 0.005*"impact" + 0.004*"NCT"
+2024-08-12 12:50:08,936 - topic #2 (0.333): 0.016*"’" + 0.008*"Northamptonshire" + 0.006*"well" + 0.006*"West" + 0.005*"quality" + 0.005*"practice" + 0.005*"needs" + 0.005*"impact" + 0.004*"need" + 0.004*"14"
+2024-08-12 12:50:08,936 - topic diff=0.753278, rho=1.000000
+2024-08-12 12:50:08,937 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1087, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:50:08.937032', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:09,852 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:50:09,852 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:09,853 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:50:09,853 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:09,853 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:50:09,853 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:09,853 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:50:09,853 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:09,854 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:50:09,854 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:09,854 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:50:09,854 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:22,656 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:50:22,658 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
+2024-08-12 12:50:22,659 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-08-12T12:50:22.659124', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:22,660 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:50:22,660 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:50:22,660 - using serial LDA version on this node
+2024-08-12 12:50:22,661 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:50:22,661 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:50:22,665 - -8.120 per-word bound, 278.3 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
+2024-08-12 12:50:22,665 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:50:22,666 - topic #0 (0.333): 0.016*"’" + 0.007*"plans" + 0.007*"needs" + 0.006*"well" + 0.006*"Sussex" + 0.005*"supported" + 0.005*"planning" + 0.005*"number" + 0.005*"13" + 0.005*"West"
+2024-08-12 12:50:22,666 - topic #1 (0.333): 0.015*"’" + 0.006*"well" + 0.005*"West" + 0.005*"Sussex" + 0.005*"13" + 0.005*"plans" + 0.005*"needs" + 0.005*"24" + 0.005*"number" + 0.004*"quality"
+2024-08-12 12:50:22,667 - topic #2 (0.333): 0.008*"’" + 0.007*"well" + 0.006*"plans" + 0.005*"West" + 0.004*"needs" + 0.004*"practice" + 0.004*"health" + 0.004*"impact" + 0.004*"2023" + 0.004*"24"
+2024-08-12 12:50:22,667 - topic diff=0.802503, rho=1.000000
+2024-08-12 12:50:22,667 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1233, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:50:22.667383', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:23,885 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:50:23,886 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:23,886 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:50:23,886 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:23,887 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:50:23,887 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:23,887 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:50:23,887 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:23,888 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:50:23,888 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:23,888 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:50:23,888 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:36,702 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:50:36,704 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)
+2024-08-12 12:50:36,704 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)", 'datetime': '2024-08-12T12:50:36.704902', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:36,705 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:50:36,706 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:50:36,706 - using serial LDA version on this node
+2024-08-12 12:50:36,706 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:50:36,706 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:50:36,710 - -7.970 per-word bound, 250.7 perplexity estimate based on a held-out corpus of 1 documents with 2451 words
+2024-08-12 12:50:36,710 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:50:36,711 - topic #0 (0.333): 0.016*"’" + 0.009*"plans" + 0.007*"needs" + 0.007*"Furness" + 0.006*"Westmorland" + 0.006*"appropriate" + 0.006*"need" + 0.006*"quality" + 0.005*"progress" + 0.005*"protection"
+2024-08-12 12:50:36,712 - topic #1 (0.333): 0.010*"’" + 0.008*"plans" + 0.007*"Westmorland" + 0.006*"Furness" + 0.006*"needs" + 0.006*"need" + 0.006*"appropriate" + 0.004*"22" + 0.004*"3" + 0.004*"protection"
+2024-08-12 12:50:36,712 - topic #2 (0.333): 0.010*"’" + 0.006*"needs" + 0.005*"Westmorland" + 0.005*"appropriate" + 0.005*"need" + 0.005*"protection" + 0.004*"well" + 0.004*"plans" + 0.004*"quality" + 0.004*"Furness"
+2024-08-12 12:50:36,712 - topic diff=0.811642, rho=1.000000
+2024-08-12 12:50:36,712 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:50:36.712643', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:37,584 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:50:37,584 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:37,584 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:50:37,584 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:37,585 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:50:37,585 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:37,585 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:50:37,585 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:37,585 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:50:37,585 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:37,585 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:50:37,586 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:48,134 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:50:48,136 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)
+2024-08-12 12:50:48,136 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-08-12T12:50:48.136649', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:48,137 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:50:48,137 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:50:48,138 - using serial LDA version on this node
+2024-08-12 12:50:48,138 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:50:48,138 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:50:48,142 - -7.956 per-word bound, 248.3 perplexity estimate based on a held-out corpus of 1 documents with 2416 words
+2024-08-12 12:50:48,142 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:50:48,143 - topic #0 (0.333): 0.006*"’" + 0.006*"practice" + 0.005*"quality" + 0.005*"appropriate" + 0.005*"May" + 0.005*"leaders" + 0.005*"plans" + 0.004*"Wigan" + 0.004*"oversight" + 0.004*"needs"
+2024-08-12 12:50:48,143 - topic #1 (0.333): 0.017*"’" + 0.008*"May" + 0.008*"needs" + 0.007*"plans" + 0.007*"practice" + 0.006*"Wigan" + 0.006*"quality" + 0.006*"appropriate" + 0.005*"9" + 0.005*"20"
+2024-08-12 12:50:48,143 - topic #2 (0.333): 0.009*"’" + 0.008*"May" + 0.006*"practice" + 0.006*"Wigan" + 0.006*"plans" + 0.005*"timely" + 0.005*"leaders" + 0.005*"quality" + 0.004*"identified" + 0.004*"2022"
+2024-08-12 12:50:48,144 - topic diff=0.805360, rho=1.000000
+2024-08-12 12:50:48,144 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:50:48.144177', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:49,076 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:50:49,077 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:49,077 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:50:49,077 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:49,077 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:50:49,077 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:49,077 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:50:49,078 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:49,078 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:50:49,078 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:49,078 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:50:49,078 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:50:59,646 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:50:59,648 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)
+2024-08-12 12:50:59,648 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-08-12T12:50:59.648384', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:50:59,649 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:50:59,649 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:50:59,649 - using serial LDA version on this node
+2024-08-12 12:50:59,650 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:50:59,650 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:50:59,654 - -7.958 per-word bound, 248.6 perplexity estimate based on a held-out corpus of 1 documents with 2600 words
+2024-08-12 12:50:59,654 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:50:59,655 - topic #0 (0.333): 0.012*"’" + 0.010*"well" + 0.007*"needs" + 0.006*"including" + 0.006*"Wiltshire" + 0.006*"need" + 0.005*"parents" + 0.005*"risk" + 0.005*"progress" + 0.005*"supported"
+2024-08-12 12:50:59,655 - topic #1 (0.333): 0.017*"’" + 0.012*"well" + 0.008*"needs" + 0.007*"need" + 0.006*"progress" + 0.006*"Wiltshire" + 0.006*"parents" + 0.006*"quality" + 0.006*"risk" + 0.006*"plans"
+2024-08-12 12:50:59,655 - topic #2 (0.333): 0.016*"’" + 0.011*"well" + 0.006*"need" + 0.005*"risk" + 0.005*"progress" + 0.005*"supported" + 0.005*"Wiltshire" + 0.005*"needs" + 0.005*"plans" + 0.005*"including"
+2024-08-12 12:50:59,656 - topic diff=0.834836, rho=1.000000
+2024-08-12 12:50:59,656 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1090, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:50:59.656179', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:00,690 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:51:00,690 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:00,690 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:51:00,691 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:00,691 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:51:00,691 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:00,691 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:51:00,691 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:00,691 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:51:00,691 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:00,692 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:51:00,692 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:12,388 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:51:12,390 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
+2024-08-12 12:51:12,390 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-08-12T12:51:12.390827', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:12,391 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:51:12,391 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:51:12,392 - using serial LDA version on this node
+2024-08-12 12:51:12,392 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:51:12,392 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:51:12,396 - -7.906 per-word bound, 239.8 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
+2024-08-12 12:51:12,396 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:51:12,397 - topic #0 (0.333): 0.013*"’" + 0.010*"needs" + 0.008*"ensure" + 0.007*"Wirral" + 0.006*"plans" + 0.006*"well" + 0.006*"practice" + 0.006*"number" + 0.005*"risk" + 0.005*"18"
+2024-08-12 12:51:12,397 - topic #1 (0.333): 0.008*"Wirral" + 0.007*"plans" + 0.006*"’" + 0.006*"practice" + 0.006*"needs" + 0.006*"ensure" + 0.005*"good" + 0.004*"well" + 0.004*"18" + 0.004*"29"
+2024-08-12 12:51:12,397 - topic #2 (0.333): 0.012*"’" + 0.011*"needs" + 0.007*"Wirral" + 0.007*"ensure" + 0.007*"plans" + 0.006*"response" + 0.006*"practice" + 0.006*"small" + 0.005*"number" + 0.005*"well"
+2024-08-12 12:51:12,397 - topic diff=0.811114, rho=1.000000
+2024-08-12 12:51:12,398 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:51:12.398027', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:13,357 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:51:13,357 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:13,358 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:51:13,358 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:13,358 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:51:13,358 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:13,358 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:51:13,358 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:13,359 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:51:13,359 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:13,359 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:51:13,359 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:24,853 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:51:24,855 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)
+2024-08-12 12:51:24,855 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-08-12T12:51:24.855816', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:24,856 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:51:24,856 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:51:24,857 - using serial LDA version on this node
+2024-08-12 12:51:24,857 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:51:24,857 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:51:24,861 - -8.054 per-word bound, 265.7 perplexity estimate based on a held-out corpus of 1 documents with 2214 words
+2024-08-12 12:51:24,861 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:51:24,862 - topic #0 (0.333): 0.014*"’" + 0.007*"plans" + 0.007*"effective" + 0.007*"needs" + 0.006*"progress" + 0.005*"quality" + 0.005*"impact" + 0.005*"appropriate" + 0.005*"Wokingham" + 0.005*"well"
+2024-08-12 12:51:24,863 - topic #1 (0.333): 0.012*"’" + 0.006*"needs" + 0.006*"progress" + 0.006*"effective" + 0.005*"plans" + 0.005*"well" + 0.005*"17" + 0.005*"protection" + 0.005*"provided" + 0.005*"March"
+2024-08-12 12:51:24,863 - topic #2 (0.333): 0.011*"’" + 0.007*"plans" + 0.006*"experiences" + 0.006*"well" + 0.005*"provided" + 0.005*"effective" + 0.005*"6" + 0.005*"17" + 0.005*"progress" + 0.004*"needs"
+2024-08-12 12:51:24,863 - topic diff=0.752369, rho=1.000000
+2024-08-12 12:51:24,863 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1096, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:51:24.863457', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:25,679 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:51:25,680 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:25,680 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:51:25,680 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:25,680 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:51:25,680 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:25,680 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:51:25,680 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:25,681 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:51:25,681 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:25,681 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:51:25,681 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:35,950 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:51:35,952 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
+2024-08-12 12:51:35,952 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-08-12T12:51:35.952875', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:35,953 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:51:35,954 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:51:35,954 - using serial LDA version on this node
+2024-08-12 12:51:35,954 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:51:35,954 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:51:35,958 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
+2024-08-12 12:51:35,958 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:51:35,959 - topic #0 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"effective" + 0.005*"quality" + 0.005*"plans" + 0.005*"strong" + 0.005*"leaders" + 0.005*"receive" + 0.004*"risks" + 0.004*"well"
+2024-08-12 12:51:35,960 - topic #1 (0.333): 0.015*"’" + 0.008*"needs" + 0.005*"Wolverhampton" + 0.005*"risks" + 0.005*"plans" + 0.005*"effective" + 0.005*"risk" + 0.004*"receive" + 0.004*"City" + 0.004*"supported"
+2024-08-12 12:51:35,960 - topic #2 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"Wolverhampton" + 0.006*"effective" + 0.005*"education" + 0.005*"supported" + 0.005*"quality" + 0.005*"risks" + 0.004*"leaders" + 0.004*"receive"
+2024-08-12 12:51:35,960 - topic diff=0.734660, rho=1.000000
+2024-08-12 12:51:35,960 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1095, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:51:35.960411', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:37,011 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:51:37,011 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:37,011 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:51:37,011 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:37,011 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:51:37,011 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:37,012 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:51:37,012 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:37,012 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:51:37,012 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:37,012 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:51:37,012 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:49,008 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-08-12 12:51:49,010 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)
+2024-08-12 12:51:49,010 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-08-12T12:51:49.010767', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:49,011 - using symmetric alpha at 0.3333333333333333
+2024-08-12 12:51:49,011 - using symmetric eta at 0.3333333333333333
+2024-08-12 12:51:49,012 - using serial LDA version on this node
+2024-08-12 12:51:49,012 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-08-12 12:51:49,012 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-08-12 12:51:49,016 - -7.943 per-word bound, 246.0 perplexity estimate based on a held-out corpus of 1 documents with 2343 words
+2024-08-12 12:51:49,016 - PROGRESS: pass 0, at document #1/1
+2024-08-12 12:51:49,017 - topic #0 (0.333): 0.015*"’" + 0.010*"plans" + 0.008*"well" + 0.007*"needs" + 0.006*"leaders" + 0.006*"progress" + 0.005*"Worcestershire" + 0.005*"26" + 0.005*"ensure" + 0.005*"appropriate"
+2024-08-12 12:51:49,017 - topic #1 (0.333): 0.017*"’" + 0.008*"Worcestershire" + 0.008*"well" + 0.008*"leaders" + 0.007*"needs" + 0.007*"ensure" + 0.007*"plans" + 0.007*"progress" + 0.006*"appropriate" + 0.005*"living"
+2024-08-12 12:51:49,018 - topic #2 (0.333): 0.024*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"progress" + 0.007*"plans" + 0.006*"Worcestershire" + 0.006*"leaders" + 0.005*"15" + 0.005*"appropriate" + 0.005*"making"
+2024-08-12 12:51:49,018 - topic diff=0.802918, rho=1.000000
+2024-08-12 12:51:49,018 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1041, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-08-12T12:51:49.018427', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-08-12 12:51:49,969 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-08-12 12:51:49,969 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:49,969 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-08-12 12:51:49,969 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:49,970 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-08-12 12:51:49,970 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:49,970 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
+2024-08-12 12:51:49,970 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:49,970 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
+2024-08-12 12:51:49,970 - Index(['judgement', 'grade'], dtype='object')
+2024-08-12 12:51:49,971 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-08-12 12:51:49,971 - Index(['judgement', 'grade'], dtype='object')