From b4744f08abc262dd17da4f52bfb5fbafcddd3754 Mon Sep 17 00:00:00 2001
From: Rob Harrison <48765695+robjharrison@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:01:58 +0000
Subject: [PATCH] Data refresh 141024

---
 index.html                              |    2 +-
 ofsted_childrens_services_overview.xlsx |  Bin 45473 -> 45453 bytes
 output.log                              | 8212 +++++++++++------------
 3 files changed, 4107 insertions(+), 4107 deletions(-)

diff --git a/index.html b/index.html
index 3c8d9f6..213e084 100644
--- a/index.html
+++ b/index.html
@@ -26,7 +26,7 @@
         <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: 07 10 2024 10:17</b></p>
+        <p><b>Summary data last updated: 14 10 2024 10:01</b></p>
         <p><b>LA inspections last updated: []</b></p>
         <div class="container">
     <table border="1" class="dataframe">
diff --git a/ofsted_childrens_services_overview.xlsx b/ofsted_childrens_services_overview.xlsx
index 9b870a077f17da9c54ad1fefb29606e922299b8e..bd910e25aa35ef597a70c2d03260475c849fe2f9 100644
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diff --git a/output.log b/output.log
index 9214d99..b0c8245 100644
--- a/output.log
+++ b/output.log
@@ -1,4106 +1,4106 @@
-2024-10-07 08:47:16,402 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:47:16,406 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)
-2024-10-07 08:47:16,409 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-10-07T08:47:16.406718', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:16,411 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:47:16,411 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:47:16,411 - using serial LDA version on this node
-2024-10-07 08:47:16,412 - 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
-2024-10-07 08:47:16,412 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:47:16,416 - -8.108 per-word bound, 276.0 perplexity estimate based on a held-out corpus of 1 documents with 2696 words
-2024-10-07 08:47:16,416 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:47:16,418 - topic #0 (0.333): 0.017*"’" + 0.007*"leaders" + 0.007*"needs" + 0.006*"practice" + 0.006*"within" + 0.004*"2023" + 0.004*"progress" + 0.004*"plans" + 0.004*"senior" + 0.004*"need"
-2024-10-07 08:47:16,418 - topic #1 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"Barnsley" + 0.005*"leaders" + 0.005*"practice" + 0.005*"within" + 0.004*"11" + 0.004*"experiences" + 0.004*"senior" + 0.004*"15"
-2024-10-07 08:47:16,418 - topic #2 (0.333): 0.021*"’" + 0.009*"needs" + 0.008*"leaders" + 0.007*"within" + 0.007*"Barnsley" + 0.006*"practice" + 0.005*"plans" + 0.005*"response" + 0.005*"family" + 0.004*"appropriate"
-2024-10-07 08:47:16,418 - topic diff=0.803082, rho=1.000000
-2024-10-07 08:47:16,418 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1216, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:47:16.418854', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:16,421 - Failed to import jpype dependencies. Fallback to subprocess.
-2024-10-07 08:47:16,421 - No module named 'jpype'
-2024-10-07 08:47:18,967 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:47:18,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:18,967 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:47:18,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:18,968 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:47:18,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:18,968 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:47:18,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:18,968 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:47:18,969 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:18,969 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:47:18,969 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:28,208 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:47:28,210 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)
-2024-10-07 08:47:28,210 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-10-07T08:47:28.210886', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:28,211 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:47:28,211 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:47:28,212 - using serial LDA version on this node
-2024-10-07 08:47:28,212 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:47:28,212 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:47:28,216 - -8.025 per-word bound, 260.4 perplexity estimate based on a held-out corpus of 1 documents with 2085 words
-2024-10-07 08:47:28,216 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:47:28,217 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.005*"needs" + 0.005*"practice" + 0.005*"clear" + 0.005*"4" + 0.005*"plans" + 0.004*"‘" + 0.004*"protection" + 0.004*"leaders"
-2024-10-07 08:47:28,217 - topic #1 (0.333): 0.016*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"practice" + 0.006*"leaders" + 0.006*"plans" + 0.005*"impact" + 0.005*"North" + 0.004*"effective" + 0.004*"Bath"
-2024-10-07 08:47:28,217 - topic #2 (0.333): 0.022*"’" + 0.010*"well" + 0.006*"needs" + 0.005*"receive" + 0.005*"plans" + 0.005*"East" + 0.005*"practice" + 0.005*"effective" + 0.005*"28" + 0.005*"Somerset"
-2024-10-07 08:47:28,217 - topic diff=0.747855, rho=1.000000
-2024-10-07 08:47:28,218 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:47:28.218102', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:29,207 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:47:29,207 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:29,208 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:47:29,208 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:29,208 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:47:29,208 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:29,208 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:47:29,208 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:29,209 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:47:29,209 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:29,209 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:47:29,209 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:41,178 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:47:41,180 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)
-2024-10-07 08:47:41,180 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-10-07T08:47:41.180691', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:41,181 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:47:41,181 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:47:41,182 - using serial LDA version on this node
-2024-10-07 08:47:41,182 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:47:41,182 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:47:41,186 - -8.115 per-word bound, 277.3 perplexity estimate based on a held-out corpus of 1 documents with 2585 words
-2024-10-07 08:47:41,186 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:47:41,188 - topic #0 (0.333): 0.012*"’" + 0.005*"needs" + 0.005*"Bedford" + 0.005*"well" + 0.004*"plans" + 0.004*"ensure" + 0.004*"education" + 0.004*"Borough" + 0.004*"26" + 0.004*"good"
-2024-10-07 08:47:41,188 - topic #1 (0.333): 0.021*"’" + 0.007*"ensure" + 0.007*"needs" + 0.006*"well" + 0.006*"supported" + 0.005*"Bedford" + 0.005*"plans" + 0.005*"family" + 0.005*"need" + 0.005*"education"
-2024-10-07 08:47:41,188 - topic #2 (0.333): 0.020*"’" + 0.007*"needs" + 0.006*"good" + 0.006*"ensure" + 0.005*"well" + 0.005*"progress" + 0.005*"plans" + 0.005*"Borough" + 0.005*"Bedford" + 0.004*"supported"
-2024-10-07 08:47:41,188 - topic diff=0.798113, rho=1.000000
-2024-10-07 08:47:41,189 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1202, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:47:41.189007', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:42,095 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:47:42,096 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:42,096 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:47:42,096 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:42,096 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:47:42,096 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:42,097 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:47:42,097 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:42,097 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:47:42,097 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:42,097 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:47:42,097 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:54,342 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:47:54,345 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)
-2024-10-07 08:47:54,345 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-10-07T08:47:54.345188', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:54,346 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:47:54,346 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:47:54,346 - using serial LDA version on this node
-2024-10-07 08:47:54,346 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:47:54,347 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:47:54,350 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 2378 words
-2024-10-07 08:47:54,350 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:47:54,352 - topic #0 (0.333): 0.010*"’" + 0.007*"needs" + 0.006*"effective" + 0.006*"well" + 0.006*"trust" + 0.005*"progress" + 0.004*"Birmingham" + 0.004*"appropriate" + 0.004*"risk" + 0.004*"plans"
-2024-10-07 08:47:54,352 - topic #1 (0.333): 0.017*"’" + 0.011*"needs" + 0.008*"well" + 0.006*"Birmingham" + 0.006*"effective" + 0.006*"plans" + 0.005*"progress" + 0.005*"trust" + 0.005*"appropriate" + 0.005*"risk"
-2024-10-07 08:47:54,352 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.007*"plans" + 0.007*"effective" + 0.006*"3" + 0.005*"Birmingham" + 0.005*"progress" + 0.005*"leaders" + 0.005*"well" + 0.005*"trust"
-2024-10-07 08:47:54,352 - topic diff=0.804554, rho=1.000000
-2024-10-07 08:47:54,352 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1065, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:47:54.352731', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:47:55,315 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:47:55,315 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:55,315 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:47:55,315 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:55,316 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:47:55,316 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:55,316 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:47:55,316 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:55,316 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:47:55,316 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:47:55,316 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:47:55,317 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:06,578 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:48:06,580 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)
-2024-10-07 08:48:06,580 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-10-07T08:48:06.580234', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:06,581 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:48:06,581 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:48:06,582 - using serial LDA version on this node
-2024-10-07 08:48:06,582 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:48:06,582 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:48:06,586 - -7.963 per-word bound, 249.6 perplexity estimate based on a held-out corpus of 1 documents with 2353 words
-2024-10-07 08:48:06,586 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:48:06,587 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"practice" + 0.008*"quality" + 0.007*"impact" + 0.006*"Darwen" + 0.006*"well" + 0.006*"Blackburn" + 0.005*"planning" + 0.005*"receive"
-2024-10-07 08:48:06,587 - topic #1 (0.333): 0.011*"’" + 0.008*"Blackburn" + 0.007*"impact" + 0.006*"practice" + 0.005*"quality" + 0.005*"well" + 0.005*"needs" + 0.005*"planning" + 0.005*"Darwen" + 0.005*"result"
-2024-10-07 08:48:06,587 - topic #2 (0.333): 0.011*"’" + 0.007*"needs" + 0.007*"Darwen" + 0.006*"quality" + 0.006*"practice" + 0.006*"Blackburn" + 0.006*"well" + 0.005*"means" + 0.005*"plans" + 0.005*"result"
-2024-10-07 08:48:06,588 - topic diff=0.818977, rho=1.000000
-2024-10-07 08:48:06,588 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1055, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:48:06.588142', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:07,494 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:48:07,494 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:07,495 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:48:07,495 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:07,495 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:48:07,495 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:07,495 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:48:07,495 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:07,496 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:48:07,496 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:07,496 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:48:07,496 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:18,909 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:48:18,911 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)
-2024-10-07 08:48:18,912 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-10-07T08:48:18.912045', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:18,913 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:48:18,913 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:48:18,913 - using serial LDA version on this node
-2024-10-07 08:48:18,913 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:48:18,913 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:48:18,917 - -7.923 per-word bound, 242.7 perplexity estimate based on a held-out corpus of 1 documents with 2392 words
-2024-10-07 08:48:18,917 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:48:18,918 - topic #0 (0.333): 0.017*"’" + 0.012*"needs" + 0.009*"well" + 0.008*"Blackpool" + 0.007*"effective" + 0.005*"plans" + 0.005*"supported" + 0.005*"practice" + 0.005*"5" + 0.005*"team"
-2024-10-07 08:48:18,918 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.008*"well" + 0.006*"Blackpool" + 0.006*"effective" + 0.006*"supported" + 0.005*"practice" + 0.005*"16" + 0.005*"progress" + 0.005*"carers"
-2024-10-07 08:48:18,919 - topic #2 (0.333): 0.015*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"Blackpool" + 0.006*"16" + 0.005*"plans" + 0.005*"timely" + 0.005*"homes" + 0.005*"quality" + 0.005*"practice"
-2024-10-07 08:48:18,919 - topic diff=0.827000, rho=1.000000
-2024-10-07 08:48:18,919 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1037, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:48:18.919348', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:19,880 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:48:19,881 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:19,881 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:48:19,881 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:19,881 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:48:19,882 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:19,882 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:48:19,882 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:19,882 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:48:19,883 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:19,883 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:48:19,883 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:30,432 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:48:30,434 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)
-2024-10-07 08:48:30,434 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-10-07T08:48:30.434689', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:30,435 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:48:30,435 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:48:30,436 - using serial LDA version on this node
-2024-10-07 08:48:30,436 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:48:30,436 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:48:30,439 - -7.909 per-word bound, 240.4 perplexity estimate based on a held-out corpus of 1 documents with 2055 words
-2024-10-07 08:48:30,439 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:48:30,441 - topic #0 (0.333): 0.017*"’" + 0.010*"Bolton" + 0.008*"needs" + 0.007*"well" + 0.006*"supported" + 0.006*"plans" + 0.005*"planning" + 0.005*"11" + 0.005*"protection" + 0.004*"strong"
-2024-10-07 08:48:30,441 - topic #1 (0.333): 0.023*"’" + 0.009*"well" + 0.009*"plans" + 0.008*"needs" + 0.007*"Bolton" + 0.006*"11" + 0.005*"effective" + 0.005*"need" + 0.005*"strong" + 0.005*"timely"
-2024-10-07 08:48:30,441 - topic #2 (0.333): 0.016*"’" + 0.011*"needs" + 0.008*"well" + 0.007*"Bolton" + 0.007*"plans" + 0.006*"need" + 0.005*"planning" + 0.005*"supported" + 0.005*"effective" + 0.005*"response"
-2024-10-07 08:48:30,441 - topic diff=0.772443, rho=1.000000
-2024-10-07 08:48:30,442 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:48:30.442035', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:31,376 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:48:31,376 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:31,376 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:48:31,376 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:31,377 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:48:31,377 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:31,377 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:48:31,377 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:31,377 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:48:31,377 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:31,377 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:48:31,378 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:40,776 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:48:40,778 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)
-2024-10-07 08:48:40,778 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-10-07T08:48:40.778699', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:40,779 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:48:40,779 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:48:40,780 - using serial LDA version on this node
-2024-10-07 08:48:40,780 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:48:40,780 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:48:40,783 - -8.030 per-word bound, 261.4 perplexity estimate based on a held-out corpus of 1 documents with 2004 words
-2024-10-07 08:48:40,784 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:48:40,785 - topic #0 (0.333): 0.018*"’" + 0.007*"quality" + 0.005*"practice" + 0.005*"6" + 0.005*"time" + 0.005*"Bournemouth" + 0.005*"Poole" + 0.004*"Christchurch" + 0.004*"impact" + 0.004*"right"
-2024-10-07 08:48:40,785 - topic #1 (0.333): 0.015*"’" + 0.006*"quality" + 0.006*"Christchurch" + 0.006*"progress" + 0.005*"practice" + 0.005*"impact" + 0.005*"risk" + 0.005*"6" + 0.004*"However" + 0.004*"2021"
-2024-10-07 08:48:40,785 - topic #2 (0.333): 0.020*"’" + 0.006*"practice" + 0.005*"progress" + 0.005*"17" + 0.005*"Bournemouth" + 0.005*"Poole" + 0.005*"December" + 0.005*"well" + 0.004*"risk" + 0.004*"time"
-2024-10-07 08:48:40,785 - topic diff=0.744346, rho=1.000000
-2024-10-07 08:48:40,786 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1035, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:48:40.786125', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:42,847 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:48:42,848 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:42,848 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:48:42,848 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:42,848 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:48:42,848 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:42,849 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:48:42,849 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:42,849 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:48:42,849 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:42,849 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:48:42,849 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:52,416 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:48:52,417 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)
-2024-10-07 08:48:52,418 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-10-07T08:48:52.418008', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:52,418 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:48:52,419 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:48:52,419 - using serial LDA version on this node
-2024-10-07 08:48:52,419 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:48:52,419 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:48:52,422 - -7.854 per-word bound, 231.4 perplexity estimate based on a held-out corpus of 1 documents with 1846 words
-2024-10-07 08:48:52,422 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:48:52,424 - topic #0 (0.333): 0.009*"’" + 0.007*"Bracknell" + 0.006*"good" + 0.005*"well" + 0.005*"plans" + 0.005*"needs" + 0.005*"Forest" + 0.005*"quality" + 0.005*"need" + 0.004*"risk"
-2024-10-07 08:48:52,424 - topic #1 (0.333): 0.014*"’" + 0.008*"Bracknell" + 0.006*"needs" + 0.006*"risk" + 0.006*"good" + 0.005*"Forest" + 0.005*"plans" + 0.005*"well" + 0.005*"need" + 0.005*"education"
-2024-10-07 08:48:52,424 - topic #2 (0.333): 0.022*"’" + 0.008*"Forest" + 0.008*"needs" + 0.008*"risk" + 0.008*"quality" + 0.007*"effective" + 0.006*"provided" + 0.006*"progress" + 0.006*"good" + 0.005*"Bracknell"
-2024-10-07 08:48:52,424 - topic diff=0.776951, rho=1.000000
-2024-10-07 08:48:52,424 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=900, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:48:52.424835', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:48:53,340 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:48:53,340 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:53,341 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:48:53,341 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:53,341 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:48:53,341 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:53,341 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:48:53,341 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:53,342 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:48:53,342 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:48:53,342 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:48:53,342 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:03,881 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:49:03,883 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)
-2024-10-07 08:49:03,884 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)", 'datetime': '2024-10-07T08:49:03.884016', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:03,885 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:49:03,885 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:49:03,885 - using serial LDA version on this node
-2024-10-07 08:49:03,885 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:49:03,885 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:49:03,889 - -8.087 per-word bound, 271.9 perplexity estimate based on a held-out corpus of 1 documents with 2249 words
-2024-10-07 08:49:03,889 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:49:03,891 - topic #0 (0.333): 0.013*"’" + 0.006*"well" + 0.005*"Brighton" + 0.005*"Hove" + 0.005*"experiences" + 0.005*"relationships" + 0.004*"needs" + 0.004*"practice" + 0.004*"progress" + 0.004*"March"
-2024-10-07 08:49:03,891 - topic #1 (0.333): 0.013*"’" + 0.006*"progress" + 0.006*"Hove" + 0.005*"practice" + 0.005*"Brighton" + 0.005*"well" + 0.005*"relationships" + 0.005*"needs" + 0.005*"experiences" + 0.004*"receive"
-2024-10-07 08:49:03,891 - topic #2 (0.333): 0.020*"’" + 0.009*"well" + 0.009*"needs" + 0.008*"Hove" + 0.007*"Brighton" + 0.007*"practice" + 0.005*"relationships" + 0.005*"experiences" + 0.005*"11" + 0.005*"progress"
-2024-10-07 08:49:03,891 - topic diff=0.775504, rho=1.000000
-2024-10-07 08:49:03,891 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:49:03.891712', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:04,847 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:49:04,847 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:04,847 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:49:04,847 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:04,847 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:49:04,847 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:04,848 - Inspection date None / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:49:04,848 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:04,848 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:49:04,848 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:04,848 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:49:04,848 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:18,642 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:49:18,644 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)
-2024-10-07 08:49:18,644 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-10-07T08:49:18.644613', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:18,645 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:49:18,645 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:49:18,646 - using serial LDA version on this node
-2024-10-07 08:49:18,646 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:49:18,646 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:49:18,652 - -8.037 per-word bound, 262.7 perplexity estimate based on a held-out corpus of 1 documents with 2647 words
-2024-10-07 08:49:18,655 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:49:18,657 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.007*"good" + 0.007*"needs" + 0.006*"Bristol" + 0.005*"health" + 0.005*"leaders" + 0.004*"progress" + 0.004*"2023" + 0.004*"plans"
-2024-10-07 08:49:18,658 - topic #1 (0.333): 0.021*"’" + 0.009*"good" + 0.007*"needs" + 0.007*"well" + 0.006*"Bristol" + 0.006*"progress" + 0.005*"16" + 0.005*"need" + 0.005*"health" + 0.005*"27"
-2024-10-07 08:49:18,658 - topic #2 (0.333): 0.021*"’" + 0.011*"well" + 0.009*"Bristol" + 0.008*"needs" + 0.007*"good" + 0.006*"plans" + 0.005*"receive" + 0.005*"always" + 0.005*"health" + 0.005*"progress"
-2024-10-07 08:49:18,658 - topic diff=0.823577, rho=1.000000
-2024-10-07 08:49:18,658 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1151, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:49:18.658746', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:19,615 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:49:19,615 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:19,615 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:49:19,615 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:19,616 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:49:19,616 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:19,616 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:49:19,616 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:19,616 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:49:19,616 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:19,617 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:49:19,617 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:30,730 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:49:30,733 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)
-2024-10-07 08:49:30,734 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-10-07T08:49:30.734134', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:30,735 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:49:30,736 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:49:30,736 - using serial LDA version on this node
-2024-10-07 08:49:30,737 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:49:30,737 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:49:30,745 - -8.242 per-word bound, 302.8 perplexity estimate based on a held-out corpus of 1 documents with 2404 words
-2024-10-07 08:49:30,745 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:49:30,746 - topic #0 (0.333): 0.014*"’" + 0.005*"plans" + 0.005*"Buckinghamshire" + 0.005*"17" + 0.004*"many" + 0.004*"6" + 0.004*"December" + 0.004*"protection" + 0.004*"well" + 0.004*"number"
-2024-10-07 08:49:30,747 - topic #1 (0.333): 0.010*"’" + 0.004*"number" + 0.004*"Buckinghamshire" + 0.004*"17" + 0.004*"plans" + 0.004*"protection" + 0.004*"6" + 0.003*"practice" + 0.003*"many" + 0.003*"2021"
-2024-10-07 08:49:30,747 - topic #2 (0.333): 0.015*"’" + 0.006*"plans" + 0.006*"number" + 0.004*"17" + 0.004*"2021" + 0.004*"Buckinghamshire" + 0.004*"many" + 0.004*"practice" + 0.004*"protection" + 0.003*"6"
-2024-10-07 08:49:30,747 - topic diff=0.724755, rho=1.000000
-2024-10-07 08:49:30,747 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1263, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:49:30.747663', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:31,729 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:49:31,729 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:31,729 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:49:31,729 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:31,730 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:49:31,730 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:31,730 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:49:31,730 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:31,730 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:49:31,730 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:31,730 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:49:31,731 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:42,465 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:49:42,467 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)
-2024-10-07 08:49:42,467 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-10-07T08:49:42.467311', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:42,468 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:49:42,468 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:49:42,468 - using serial LDA version on this node
-2024-10-07 08:49:42,469 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:49:42,469 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:49:42,472 - -7.978 per-word bound, 252.1 perplexity estimate based on a held-out corpus of 1 documents with 2427 words
-2024-10-07 08:49:42,473 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:49:42,474 - topic #0 (0.333): 0.010*"’" + 0.007*"protection" + 0.006*"2021" + 0.006*"practice" + 0.005*"impact" + 0.005*"needs" + 0.005*"need" + 0.005*"quality" + 0.005*"5" + 0.004*"team"
-2024-10-07 08:49:42,474 - topic #1 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"2021" + 0.007*"protection" + 0.006*"team" + 0.006*"practice" + 0.006*"risk" + 0.005*"quality" + 0.005*"Bury" + 0.005*"new"
-2024-10-07 08:49:42,474 - topic #2 (0.333): 0.007*"’" + 0.006*"2021" + 0.005*"team" + 0.005*"needs" + 0.005*"protection" + 0.005*"need" + 0.004*"October" + 0.004*"impact" + 0.004*"progress" + 0.004*"Bury"
-2024-10-07 08:49:42,474 - topic diff=0.818605, rho=1.000000
-2024-10-07 08:49:42,475 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:49:42.475002', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:43,477 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:49:43,477 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:43,477 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:49:43,477 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:43,477 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:49:43,478 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:43,478 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:49:43,478 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:43,478 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:49:43,478 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:43,478 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:49:43,479 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:54,761 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:49:54,763 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)
-2024-10-07 08:49:54,764 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-10-07T08:49:54.764065', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:54,765 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:49:54,765 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:49:54,765 - using serial LDA version on this node
-2024-10-07 08:49:54,765 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:49:54,765 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:49:54,769 - -8.026 per-word bound, 260.7 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
-2024-10-07 08:49:54,769 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:49:54,771 - topic #0 (0.333): 0.024*"’" + 0.011*"needs" + 0.010*"Calderdale" + 0.008*"well" + 0.006*"ensure" + 0.006*"progress" + 0.006*"plans" + 0.005*"19" + 0.005*"information" + 0.005*"parents"
-2024-10-07 08:49:54,771 - topic #1 (0.333): 0.020*"’" + 0.009*"needs" + 0.008*"Calderdale" + 0.007*"plans" + 0.006*"risk" + 0.005*"parents" + 0.005*"progress" + 0.005*"well" + 0.005*"experiences" + 0.005*"ensure"
-2024-10-07 08:49:54,771 - topic #2 (0.333): 0.015*"’" + 0.008*"needs" + 0.006*"Calderdale" + 0.005*"ensure" + 0.005*"progress" + 0.005*"well" + 0.005*"plans" + 0.004*"risk" + 0.004*"information" + 0.004*"experiences"
-2024-10-07 08:49:54,771 - topic diff=0.784350, rho=1.000000
-2024-10-07 08:49:54,771 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:49:54.771584', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:49:55,684 - Inspection date 2024-02-19 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:49:55,684 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:55,684 - Inspection date 2024-02-19 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:49:55,684 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:55,685 - Inspection date 2024-02-19 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:49:55,685 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:55,685 - Inspection date 2024-02-19 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:49:55,685 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:55,685 - Inspection date 2024-02-19 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:49:55,685 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:49:55,685 - Inspection date 2024-02-19 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:49:55,686 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:07,872 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:50:07,874 - built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)
-2024-10-07 08:50:07,874 - Dictionary lifecycle event {'msg': "built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)", 'datetime': '2024-10-07T08:50:07.874738', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:07,875 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:50:07,875 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:50:07,876 - using serial LDA version on this node
-2024-10-07 08:50:07,876 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:50:07,876 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:50:07,880 - -8.004 per-word bound, 256.7 perplexity estimate based on a held-out corpus of 1 documents with 2339 words
-2024-10-07 08:50:07,880 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:50:07,881 - topic #0 (0.333): 0.020*"’" + 0.006*"Cambridgeshire" + 0.006*"effective" + 0.006*"practice" + 0.006*"good" + 0.005*"leaders" + 0.005*"15" + 0.005*"needs" + 0.005*"well" + 0.005*"response"
-2024-10-07 08:50:07,882 - topic #1 (0.333): 0.014*"’" + 0.006*"needs" + 0.006*"However" + 0.006*"leaders" + 0.005*"4" + 0.005*"Cambridgeshire" + 0.005*"leadership" + 0.004*"quality" + 0.004*"effective" + 0.004*"15"
-2024-10-07 08:50:07,882 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.008*"leaders" + 0.007*"Cambridgeshire" + 0.006*"good" + 0.005*"well" + 0.005*"2024" + 0.005*"strong" + 0.004*"quality" + 0.004*"experiences"
-2024-10-07 08:50:07,882 - topic diff=0.785544, rho=1.000000
-2024-10-07 08:50:07,882 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1082, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:50:07.882532', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:08,938 - Inspection date 2024-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:50:08,939 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:08,939 - Inspection date 2024-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:50:08,939 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:08,939 - Inspection date 2024-03-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:50:08,939 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:08,940 - Inspection date 2024-03-04 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:50:08,940 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:08,940 - Inspection date 2024-03-04 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:50:08,940 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:08,940 - Inspection date 2024-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:50:08,940 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:19,194 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:50:19,197 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
-2024-10-07 08:50:19,198 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-10-07T08:50:19.198148', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:19,199 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:50:19,199 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:50:19,200 - using serial LDA version on this node
-2024-10-07 08:50:19,200 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:50:19,200 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:50:19,207 - -7.965 per-word bound, 249.9 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
-2024-10-07 08:50:19,207 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:50:19,209 - topic #0 (0.333): 0.010*"’" + 0.007*"well" + 0.007*"needs" + 0.007*"carers" + 0.005*"good" + 0.005*"need" + 0.004*"effective" + 0.004*"Bedfordshire" + 0.004*"number" + 0.004*"21"
-2024-10-07 08:50:19,209 - topic #1 (0.333): 0.022*"’" + 0.011*"well" + 0.007*"needs" + 0.007*"plans" + 0.006*"need" + 0.006*"carers" + 0.006*"Central" + 0.006*"good" + 0.006*"Bedfordshire" + 0.006*"progress"
-2024-10-07 08:50:19,209 - topic #2 (0.333): 0.013*"’" + 0.008*"well" + 0.007*"need" + 0.007*"needs" + 0.006*"good" + 0.006*"progress" + 0.005*"carers" + 0.005*"plans" + 0.005*"protection" + 0.005*"Leaders"
-2024-10-07 08:50:19,209 - topic diff=0.791028, rho=1.000000
-2024-10-07 08:50:19,209 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1030, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:50:19.209862', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:20,149 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:50:20,149 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:20,149 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:50:20,149 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:20,149 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:50:20,150 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:20,150 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:50:20,150 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:20,150 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:50:20,150 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:20,150 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:50:20,150 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:31,769 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:50:31,771 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)
-2024-10-07 08:50:31,771 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-10-07T08:50:31.771333', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:31,772 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:50:31,772 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:50:31,772 - using serial LDA version on this node
-2024-10-07 08:50:31,773 - 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
-2024-10-07 08:50:31,773 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:50:31,776 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 2272 words
-2024-10-07 08:50:31,776 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:50:31,778 - topic #0 (0.333): 0.013*"’" + 0.008*"2024" + 0.008*"needs" + 0.008*"practice" + 0.007*"plans" + 0.007*"quality" + 0.006*"well" + 0.006*"East" + 0.006*"Cheshire" + 0.006*"leaders"
-2024-10-07 08:50:31,778 - topic #1 (0.333): 0.009*"’" + 0.006*"practice" + 0.006*"2024" + 0.005*"plans" + 0.004*"East" + 0.004*"leaders" + 0.004*"Cheshire" + 0.004*"needs" + 0.004*"well" + 0.004*"always"
-2024-10-07 08:50:31,778 - topic #2 (0.333): 0.014*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"2024" + 0.007*"plans" + 0.006*"quality" + 0.005*"effective" + 0.005*"Cheshire" + 0.005*"need" + 0.005*"East"
-2024-10-07 08:50:31,778 - topic diff=0.790338, rho=1.000000
-2024-10-07 08:50:31,778 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:50:31.778932', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:32,768 - Inspection date 2024-02-26 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:50:32,769 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:32,769 - Inspection date 2024-02-26 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:50:32,769 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:32,769 - Inspection date 2024-02-26 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:50:32,769 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:32,769 - Inspection date 2024-02-26 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:50:32,769 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:32,770 - Inspection date 2024-02-26 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:50:32,770 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:32,770 - Inspection date 2024-02-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:50:32,770 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:43,861 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:50:43,863 - built Dictionary<1010 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2203 corpus positions)
-2024-10-07 08:50:43,863 - Dictionary lifecycle event {'msg': "built Dictionary<1010 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2203 corpus positions)", 'datetime': '2024-10-07T08:50:43.863224', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:43,864 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:50:43,864 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:50:43,864 - using serial LDA version on this node
-2024-10-07 08:50:43,864 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:50:43,865 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:50:43,868 - -7.930 per-word bound, 243.9 perplexity estimate based on a held-out corpus of 1 documents with 2203 words
-2024-10-07 08:50:43,868 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:50:43,869 - topic #0 (0.333): 0.016*"’" + 0.007*"good" + 0.006*"needs" + 0.006*"well" + 0.005*"progress" + 0.005*"Cheshire" + 0.005*"Chester" + 0.005*"impact" + 0.005*"timely" + 0.005*"plans"
-2024-10-07 08:50:43,869 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"progress" + 0.005*"plans" + 0.005*"leaders" + 0.005*"information" + 0.004*"impact" + 0.004*"2024" + 0.004*"means"
-2024-10-07 08:50:43,870 - topic #2 (0.333): 0.017*"’" + 0.006*"plans" + 0.005*"well" + 0.005*"progress" + 0.005*"needs" + 0.005*"access" + 0.005*"impact" + 0.004*"Cheshire" + 0.004*"effective" + 0.004*"Chester"
-2024-10-07 08:50:43,870 - topic diff=0.787317, rho=1.000000
-2024-10-07 08:50:43,870 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1010, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:50:43.870362', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:44,841 - Inspection date 2024-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:50:44,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:44,842 - Inspection date 2024-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:50:44,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:44,842 - Inspection date 2024-07-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:50:44,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:44,842 - Inspection date 2024-07-15 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:50:44,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:44,843 - Inspection date 2024-07-15 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:50:44,843 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:44,843 - Inspection date 2024-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:50:44,843 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:56,257 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:50:56,259 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)
-2024-10-07 08:50:56,259 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-10-07T08:50:56.259864', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:56,261 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:50:56,261 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:50:56,261 - using serial LDA version on this node
-2024-10-07 08:50:56,261 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:50:56,261 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:50:56,265 - -8.050 per-word bound, 265.1 perplexity estimate based on a held-out corpus of 1 documents with 2639 words
-2024-10-07 08:50:56,265 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:50:56,267 - topic #0 (0.333): 0.025*"’" + 0.007*"plans" + 0.006*"2" + 0.006*"Bradford" + 0.005*"risk" + 0.005*"City" + 0.005*"practice" + 0.005*"21" + 0.004*"impact" + 0.004*"◼"
-2024-10-07 08:50:56,267 - topic #1 (0.333): 0.019*"’" + 0.007*"plans" + 0.006*"needs" + 0.005*"need" + 0.005*"quality" + 0.005*"changes" + 0.005*"◼" + 0.005*"Borough" + 0.005*"Council" + 0.004*"2022"
-2024-10-07 08:50:56,267 - topic #2 (0.333): 0.016*"’" + 0.005*"plans" + 0.005*"impact" + 0.005*"Bradford" + 0.004*"2" + 0.004*"needs" + 0.004*"many" + 0.004*"need" + 0.004*"worker" + 0.004*"Metropolitan"
-2024-10-07 08:50:56,267 - topic diff=0.811010, rho=1.000000
-2024-10-07 08:50:56,267 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1164, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:50:56.267831', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:50:57,239 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:50:57,239 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:57,240 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:50:57,240 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:57,240 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:50:57,240 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:57,240 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:50:57,240 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:57,241 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:50:57,241 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:50:57,241 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:50:57,241 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:05,971 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:51:05,972 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)
-2024-10-07 08:51:05,972 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-10-07T08:51:05.972822', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:05,973 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:51:05,973 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:51:05,973 - using serial LDA version on this node
-2024-10-07 08:51:05,974 - 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
-2024-10-07 08:51:05,974 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:51:05,977 - -7.839 per-word bound, 228.9 perplexity estimate based on a held-out corpus of 1 documents with 1767 words
-2024-10-07 08:51:05,977 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:51:05,978 - topic #0 (0.333): 0.011*"well" + 0.008*"’" + 0.008*"ensure" + 0.007*"needs" + 0.006*"clear" + 0.005*"effective" + 0.005*"good" + 0.005*"progress" + 0.004*"experiences" + 0.004*"individual"
-2024-10-07 08:51:05,978 - topic #1 (0.333): 0.012*"needs" + 0.011*"well" + 0.008*"ensure" + 0.007*"’" + 0.006*"effective" + 0.006*"progress" + 0.006*"clear" + 0.005*"good" + 0.005*"individual" + 0.005*"plans"
-2024-10-07 08:51:05,979 - topic #2 (0.333): 0.017*"’" + 0.014*"needs" + 0.009*"ensure" + 0.008*"well" + 0.007*"effective" + 0.007*"plans" + 0.006*"clear" + 0.006*"progress" + 0.006*"practice" + 0.006*"good"
-2024-10-07 08:51:05,979 - topic diff=0.752588, rho=1.000000
-2024-10-07 08:51:05,979 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=876, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:51:05.979340', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:07,085 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:51:07,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:07,086 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:51:07,086 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:07,086 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:51:07,086 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:07,086 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:51:07,087 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:07,087 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:51:07,087 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:07,087 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:51:07,087 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:17,401 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:51:17,403 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)
-2024-10-07 08:51:17,403 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-10-07T08:51:17.403264', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:17,404 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:51:17,404 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:51:17,404 - using serial LDA version on this node
-2024-10-07 08:51:17,405 - 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
-2024-10-07 08:51:17,405 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:51:17,408 - -7.907 per-word bound, 240.0 perplexity estimate based on a held-out corpus of 1 documents with 2281 words
-2024-10-07 08:51:17,408 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:51:17,409 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"Wakefield" + 0.008*"quality" + 0.007*"effective" + 0.007*"good" + 0.006*"November" + 0.006*"plans" + 0.005*"practice" + 0.005*"progress"
-2024-10-07 08:51:17,410 - topic #1 (0.333): 0.016*"’" + 0.010*"leaders" + 0.008*"Wakefield" + 0.008*"November" + 0.007*"effective" + 0.007*"well" + 0.007*"quality" + 0.007*"plans" + 0.006*"good" + 0.006*"19"
-2024-10-07 08:51:17,410 - topic #2 (0.333): 0.016*"’" + 0.008*"quality" + 0.007*"November" + 0.007*"good" + 0.007*"well" + 0.006*"Wakefield" + 0.006*"leaders" + 0.005*"19" + 0.005*"plans" + 0.005*"progress"
-2024-10-07 08:51:17,410 - topic diff=0.801231, rho=1.000000
-2024-10-07 08:51:17,410 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1007, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:51:17.410578', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:18,286 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:51:18,287 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:18,287 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:51:18,287 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:18,288 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:51:18,288 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:18,288 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:51:18,288 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:18,288 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:51:18,288 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:18,288 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:51:18,288 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:27,696 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:51:27,698 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)
-2024-10-07 08:51:27,698 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-10-07T08:51:27.698727', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:27,699 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:51:27,699 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:51:27,700 - using serial LDA version on this node
-2024-10-07 08:51:27,700 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:51:27,700 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:51:27,703 - -7.866 per-word bound, 233.4 perplexity estimate based on a held-out corpus of 1 documents with 1855 words
-2024-10-07 08:51:27,703 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:51:27,705 - topic #0 (0.333): 0.019*"’" + 0.010*"March" + 0.008*"needs" + 0.007*"quality" + 0.006*"effective" + 0.006*"ensure" + 0.006*"However" + 0.006*"well" + 0.005*"York" + 0.005*"training"
-2024-10-07 08:51:27,705 - topic #1 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"effective" + 0.005*"quality" + 0.005*"need" + 0.005*"good" + 0.005*"supported" + 0.005*"York" + 0.005*"experiences" + 0.005*"However"
-2024-10-07 08:51:27,705 - topic #2 (0.333): 0.012*"’" + 0.006*"quality" + 0.006*"needs" + 0.005*"ensure" + 0.005*"plans" + 0.005*"York" + 0.004*"effective" + 0.004*"March" + 0.004*"However" + 0.004*"education"
-2024-10-07 08:51:27,705 - topic diff=0.783969, rho=1.000000
-2024-10-07 08:51:27,705 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=909, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:51:27.705711', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:28,590 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:51:28,590 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:28,590 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:51:28,590 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:28,591 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:51:28,591 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:28,591 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:51:28,591 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:28,591 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:51:28,591 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:28,591 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:51:28,591 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:38,675 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:51:38,678 - built Dictionary<1053 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2351 corpus positions)
-2024-10-07 08:51:38,678 - Dictionary lifecycle event {'msg': "built Dictionary<1053 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2351 corpus positions)", 'datetime': '2024-10-07T08:51:38.678198', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:38,679 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:51:38,679 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:51:38,679 - using serial LDA version on this node
-2024-10-07 08:51:38,680 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:51:38,680 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:51:38,683 - -7.958 per-word bound, 248.6 perplexity estimate based on a held-out corpus of 1 documents with 2351 words
-2024-10-07 08:51:38,683 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:51:38,685 - topic #0 (0.333): 0.013*"’" + 0.007*"need" + 0.007*"needs" + 0.006*"Cornwall" + 0.005*"July" + 0.004*"well" + 0.004*"receive" + 0.004*"oversight" + 0.004*"effective" + 0.003*"1"
-2024-10-07 08:51:38,685 - topic #1 (0.333): 0.022*"’" + 0.012*"needs" + 0.008*"Cornwall" + 0.007*"well" + 0.007*"need" + 0.006*"receive" + 0.006*"effective" + 0.005*"progress" + 0.005*"5" + 0.005*"risk"
-2024-10-07 08:51:38,685 - topic #2 (0.333): 0.018*"’" + 0.008*"Cornwall" + 0.007*"needs" + 0.006*"well" + 0.006*"need" + 0.005*"5" + 0.005*"leaders" + 0.005*"1" + 0.005*"receive" + 0.005*"oversight"
-2024-10-07 08:51:38,685 - topic diff=0.800151, rho=1.000000
-2024-10-07 08:51:38,685 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1053, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:51:38.685840', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:39,639 - Inspection date 2024-07-01 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:51:39,639 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:39,640 - Inspection date 2024-07-01 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:51:39,640 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:39,640 - Inspection date 2024-07-01 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:51:39,640 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:39,640 - Inspection date 2024-07-01 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:51:39,640 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:39,640 - Inspection date 2024-07-01 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:51:39,641 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:39,641 - Inspection date 2024-07-01 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:51:39,641 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:47,279 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:51:47,280 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)
-2024-10-07 08:51:47,280 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-10-07T08:51:47.280812', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:47,281 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:51:47,281 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:51:47,281 - using serial LDA version on this node
-2024-10-07 08:51:47,282 - 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
-2024-10-07 08:51:47,282 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:51:47,285 - -7.686 per-word bound, 205.9 perplexity estimate based on a held-out corpus of 1 documents with 1521 words
-2024-10-07 08:51:47,285 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:51:47,286 - topic #0 (0.333): 0.024*"’" + 0.011*"Isles" + 0.008*"practice" + 0.008*"Scilly" + 0.007*"need" + 0.006*"information" + 0.006*"needs" + 0.005*"protection" + 0.005*"13" + 0.004*"risks"
-2024-10-07 08:51:47,286 - topic #1 (0.333): 0.020*"’" + 0.016*"Scilly" + 0.013*"Isles" + 0.010*"information" + 0.009*"need" + 0.008*"practice" + 0.008*"needs" + 0.006*"quality" + 0.006*"place" + 0.006*"risks"
-2024-10-07 08:51:47,286 - topic #2 (0.333): 0.019*"’" + 0.012*"Isles" + 0.010*"Scilly" + 0.010*"information" + 0.008*"practice" + 0.008*"protection" + 0.007*"need" + 0.006*"quality" + 0.006*"place" + 0.006*"needs"
-2024-10-07 08:51:47,286 - topic diff=0.757559, rho=1.000000
-2024-10-07 08:51:47,287 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=754, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-07T08:51:47.287030', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:48,181 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:51:48,181 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:48,181 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:51:48,181 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:48,182 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:51:48,182 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:48,182 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:51:48,182 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:48,182 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:51:48,182 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:48,183 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:51:48,183 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:51:59,310 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:51:59,311 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)
-2024-10-07 08:51:59,312 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-10-07T08:51:59.312008', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:51:59,312 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:51:59,313 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:51:59,313 - using serial LDA version on this node
-2024-10-07 08:51:59,313 - 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
-2024-10-07 08:51:59,313 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:51:59,317 - -7.849 per-word bound, 230.5 perplexity estimate based on a held-out corpus of 1 documents with 2074 words
-2024-10-07 08:51:59,317 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:51:59,318 - topic #0 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"Coventry" + 0.006*"plans" + 0.006*"well" + 0.005*"strong" + 0.005*"supported" + 0.005*"family" + 0.004*"education" + 0.004*"need"
-2024-10-07 08:51:59,318 - topic #1 (0.333): 0.021*"’" + 0.008*"Coventry" + 0.007*"needs" + 0.007*"well" + 0.007*"supported" + 0.005*"plans" + 0.005*"strong" + 0.005*"family" + 0.004*"range" + 0.004*"July"
-2024-10-07 08:51:59,318 - topic #2 (0.333): 0.021*"’" + 0.010*"well" + 0.009*"Coventry" + 0.008*"supported" + 0.007*"family" + 0.007*"needs" + 0.006*"need" + 0.006*"plans" + 0.006*"strong" + 0.005*"20"
-2024-10-07 08:51:59,319 - topic diff=0.804938, rho=1.000000
-2024-10-07 08:51:59,319 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=938, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:51:59.319210', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:00,313 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:52:00,313 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:00,313 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:52:00,313 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:00,314 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:52:00,314 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:00,314 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:52:00,314 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:00,314 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:52:00,314 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:00,315 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:52:00,315 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:12,951 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:52:12,953 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)
-2024-10-07 08:52:12,954 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-10-07T08:52:12.954046', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:12,955 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:52:12,955 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:52:12,955 - using serial LDA version on this node
-2024-10-07 08:52:12,956 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:52:12,956 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:52:12,960 - -8.090 per-word bound, 272.4 perplexity estimate based on a held-out corpus of 1 documents with 2653 words
-2024-10-07 08:52:12,960 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:52:12,961 - topic #0 (0.333): 0.022*"’" + 0.008*"well" + 0.008*"October" + 0.007*"leaders" + 0.007*"needs" + 0.006*"practice" + 0.005*"Darlington" + 0.005*"quality" + 0.005*"supported" + 0.005*"effective"
-2024-10-07 08:52:12,961 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"leaders" + 0.006*"needs" + 0.006*"practice" + 0.005*"October" + 0.005*"Darlington" + 0.004*"quality" + 0.004*"education" + 0.004*"effective"
-2024-10-07 08:52:12,961 - topic #2 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"Darlington" + 0.006*"needs" + 0.006*"October" + 0.006*"leaders" + 0.006*"practice" + 0.005*"effective" + 0.005*"10" + 0.005*"21"
-2024-10-07 08:52:12,962 - topic diff=0.797656, rho=1.000000
-2024-10-07 08:52:12,962 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1195, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:52:12.962207', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:13,890 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:52:13,891 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:13,891 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:52:13,891 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:13,891 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:52:13,892 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:13,892 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:52:13,892 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:13,892 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:52:13,892 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:13,893 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:52:13,893 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:25,476 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:52:25,478 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)
-2024-10-07 08:52:25,479 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-10-07T08:52:25.479128', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:25,480 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:52:25,480 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:52:25,480 - using serial LDA version on this node
-2024-10-07 08:52:25,480 - 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
-2024-10-07 08:52:25,481 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:52:25,484 - -8.042 per-word bound, 263.5 perplexity estimate based on a held-out corpus of 1 documents with 2396 words
-2024-10-07 08:52:25,484 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:52:25,486 - topic #0 (0.333): 0.020*"’" + 0.010*"needs" + 0.007*"quality" + 0.007*"Derby" + 0.006*"receive" + 0.006*"progress" + 0.006*"leaders" + 0.006*"good" + 0.005*"plans" + 0.005*"well"
-2024-10-07 08:52:25,486 - topic #1 (0.333): 0.021*"’" + 0.010*"needs" + 0.008*"Derby" + 0.006*"receive" + 0.006*"appropriate" + 0.006*"plans" + 0.006*"quality" + 0.006*"need" + 0.005*"oversight" + 0.005*"leaders"
-2024-10-07 08:52:25,486 - topic #2 (0.333): 0.022*"’" + 0.008*"needs" + 0.007*"Derby" + 0.006*"quality" + 0.005*"receive" + 0.005*"well" + 0.005*"need" + 0.005*"plans" + 0.005*"good" + 0.004*"progress"
-2024-10-07 08:52:25,486 - topic diff=0.772026, rho=1.000000
-2024-10-07 08:52:25,487 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1121, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:52:25.487120', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:26,429 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:52:26,429 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:26,429 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:52:26,429 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:26,430 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:52:26,430 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:26,430 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:52:26,430 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:26,430 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:52:26,430 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:26,431 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:52:26,431 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:35,660 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:52:35,662 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)
-2024-10-07 08:52:35,662 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-10-07T08:52:35.662860', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:35,663 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:52:35,663 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:52:35,664 - using serial LDA version on this node
-2024-10-07 08:52:35,664 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:52:35,664 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:52:35,668 - -8.038 per-word bound, 262.7 perplexity estimate based on a held-out corpus of 1 documents with 2035 words
-2024-10-07 08:52:35,668 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:52:35,669 - topic #0 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"Derbyshire" + 0.006*"need" + 0.005*"plans" + 0.005*"education" + 0.005*"leaders" + 0.004*"positive" + 0.004*"effective" + 0.004*"health"
-2024-10-07 08:52:35,669 - topic #1 (0.333): 0.015*"’" + 0.009*"well" + 0.007*"Derbyshire" + 0.005*"needs" + 0.005*"positive" + 0.005*"health" + 0.005*"good" + 0.005*"number" + 0.005*"leaders" + 0.005*"effective"
-2024-10-07 08:52:35,670 - topic #2 (0.333): 0.010*"’" + 0.006*"Derbyshire" + 0.006*"well" + 0.005*"plans" + 0.005*"needs" + 0.004*"10" + 0.004*"practice" + 0.004*"30" + 0.004*"need" + 0.004*"positive"
-2024-10-07 08:52:35,670 - topic diff=0.741010, rho=1.000000
-2024-10-07 08:52:35,670 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:52:35.670347', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:36,701 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:52:36,701 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:36,702 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:52:36,702 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:36,702 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:52:36,702 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:36,702 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:52:36,702 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:36,702 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:52:36,703 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:36,703 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:52:36,703 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:48,036 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:52:48,039 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)
-2024-10-07 08:52:48,039 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-10-07T08:52:48.039229', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:48,040 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:52:48,040 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:52:48,040 - using serial LDA version on this node
-2024-10-07 08:52:48,041 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:52:48,041 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:52:48,045 - -8.147 per-word bound, 283.4 perplexity estimate based on a held-out corpus of 1 documents with 2313 words
-2024-10-07 08:52:48,045 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:52:48,046 - topic #0 (0.333): 0.009*"’" + 0.005*"well" + 0.005*"leaders" + 0.004*"health" + 0.004*"risk" + 0.004*"Devon" + 0.004*"practice" + 0.004*"need" + 0.004*"living" + 0.004*"needs"
-2024-10-07 08:52:48,046 - topic #1 (0.333): 0.009*"’" + 0.005*"well" + 0.005*"leaders" + 0.005*"risk" + 0.005*"health" + 0.004*"protection" + 0.004*"living" + 0.004*"plans" + 0.004*"progress" + 0.003*"risks"
-2024-10-07 08:52:48,047 - topic #2 (0.333): 0.009*"’" + 0.006*"well" + 0.006*"progress" + 0.005*"health" + 0.005*"risk" + 0.005*"case" + 0.004*"leaders" + 0.004*"quality" + 0.004*"Devon" + 0.004*"time"
-2024-10-07 08:52:48,047 - topic diff=0.733848, rho=1.000000
-2024-10-07 08:52:48,047 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:52:48.047409', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:52:49,056 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:52:49,056 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:49,056 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:52:49,056 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:49,057 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:52:49,057 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:49,057 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:52:49,057 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:49,057 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:52:49,057 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:52:49,057 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:52:49,058 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:00,181 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:53:00,183 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)
-2024-10-07 08:53:00,183 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-10-07T08:53:00.183828', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:00,184 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:53:00,185 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:53:00,185 - using serial LDA version on this node
-2024-10-07 08:53:00,185 - 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
-2024-10-07 08:53:00,185 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:53:00,189 - -8.110 per-word bound, 276.3 perplexity estimate based on a held-out corpus of 1 documents with 2429 words
-2024-10-07 08:53:00,189 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:53:00,191 - topic #0 (0.333): 0.027*"’" + 0.007*"well" + 0.007*"Doncaster" + 0.006*"records" + 0.006*"many" + 0.005*"leaders" + 0.005*"plans" + 0.005*"information" + 0.005*"arrangements" + 0.005*"14"
-2024-10-07 08:53:00,191 - topic #1 (0.333): 0.012*"’" + 0.006*"well" + 0.005*"progress" + 0.004*"leaders" + 0.004*"Doncaster" + 0.004*"25" + 0.004*"arrangements" + 0.004*"made" + 0.003*"plans" + 0.003*"oversight"
-2024-10-07 08:53:00,191 - topic #2 (0.333): 0.015*"’" + 0.006*"Doncaster" + 0.006*"well" + 0.005*"progress" + 0.005*"quality" + 0.005*"February" + 0.005*"many" + 0.004*"leaders" + 0.004*"plans" + 0.004*"oversight"
-2024-10-07 08:53:00,191 - topic diff=0.786725, rho=1.000000
-2024-10-07 08:53:00,191 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:53:00.191901', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:02,113 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:53:02,113 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:02,113 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:53:02,114 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:02,114 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:53:02,114 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:02,114 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:53:02,115 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:02,115 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:53:02,115 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:02,115 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:53:02,115 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:10,545 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:53:10,547 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)
-2024-10-07 08:53:10,547 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-10-07T08:53:10.547684', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:10,548 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:53:10,548 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:53:10,549 - using serial LDA version on this node
-2024-10-07 08:53:10,549 - 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
-2024-10-07 08:53:10,549 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:53:10,553 - -8.100 per-word bound, 274.5 perplexity estimate based on a held-out corpus of 1 documents with 1942 words
-2024-10-07 08:53:10,553 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:53:10,554 - topic #0 (0.333): 0.011*"’" + 0.008*"Dorset" + 0.005*"good" + 0.005*"well" + 0.004*"leaders" + 0.004*"27" + 0.004*"needs" + 0.004*"including" + 0.004*"Senior" + 0.004*"arrangements"
-2024-10-07 08:53:10,554 - topic #1 (0.333): 0.015*"’" + 0.007*"good" + 0.007*"Dorset" + 0.007*"well" + 0.005*"change" + 0.004*"arrangements" + 0.004*"needs" + 0.004*"impact" + 0.004*"quality" + 0.004*"pandemic"
-2024-10-07 08:53:10,554 - topic #2 (0.333): 0.014*"’" + 0.008*"Dorset" + 0.005*"good" + 0.005*"well" + 0.005*"needs" + 0.005*"arrangements" + 0.004*"8" + 0.004*"receive" + 0.004*"October" + 0.004*"leaders"
-2024-10-07 08:53:10,555 - topic diff=0.711821, rho=1.000000
-2024-10-07 08:53:10,555 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1067, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:53:10.555208', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:11,461 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:53:11,461 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:11,461 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:53:11,461 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:11,462 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:53:11,462 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:11,462 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:53:11,462 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:11,462 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:53:11,462 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:11,463 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:53:11,463 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:21,856 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:53:21,858 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)
-2024-10-07 08:53:21,858 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-10-07T08:53:21.858202', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:21,859 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:53:21,859 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:53:21,859 - using serial LDA version on this node
-2024-10-07 08:53:21,860 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:53:21,860 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:53:21,863 - -8.012 per-word bound, 258.2 perplexity estimate based on a held-out corpus of 1 documents with 2138 words
-2024-10-07 08:53:21,863 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:53:21,865 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.008*"Dudley" + 0.005*"plans" + 0.005*"arrangements" + 0.005*"always" + 0.004*"quality" + 0.004*"well" + 0.004*"management" + 0.004*"ensure"
-2024-10-07 08:53:21,865 - topic #1 (0.333): 0.015*"’" + 0.013*"needs" + 0.009*"Dudley" + 0.006*"arrangements" + 0.006*"well" + 0.005*"oversight" + 0.005*"11" + 0.005*"quality" + 0.004*"ensure" + 0.004*"always"
-2024-10-07 08:53:21,865 - topic #2 (0.333): 0.016*"’" + 0.010*"needs" + 0.007*"Dudley" + 0.006*"always" + 0.006*"plans" + 0.006*"well" + 0.005*"ensure" + 0.005*"oversight" + 0.004*"However" + 0.004*"November"
-2024-10-07 08:53:21,865 - topic diff=0.760780, rho=1.000000
-2024-10-07 08:53:21,865 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1050, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:53:21.865724', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:22,850 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:53:22,851 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:22,851 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:53:22,851 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:22,851 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:53:22,851 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:22,851 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:53:22,852 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:22,852 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:53:22,852 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:22,852 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:53:22,852 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:34,330 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:53:34,332 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)
-2024-10-07 08:53:34,333 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-10-07T08:53:34.333103', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:34,334 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:53:34,334 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:53:34,334 - using serial LDA version on this node
-2024-10-07 08:53:34,334 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:53:34,334 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:53:34,338 - -7.977 per-word bound, 252.0 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
-2024-10-07 08:53:34,338 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:53:34,339 - topic #0 (0.333): 0.014*"’" + 0.011*"needs" + 0.008*"Durham" + 0.007*"plans" + 0.006*"well" + 0.006*"May" + 0.006*"ensure" + 0.005*"risks" + 0.005*"practice" + 0.005*"identified"
-2024-10-07 08:53:34,340 - topic #1 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"May" + 0.007*"well" + 0.006*"plans" + 0.006*"Durham" + 0.005*"leaders" + 0.005*"ensure" + 0.005*"practice" + 0.004*"progress"
-2024-10-07 08:53:34,340 - topic #2 (0.333): 0.016*"’" + 0.012*"needs" + 0.007*"Durham" + 0.007*"May" + 0.007*"well" + 0.006*"ensure" + 0.006*"plans" + 0.005*"practice" + 0.005*"family" + 0.004*"20"
-2024-10-07 08:53:34,340 - topic diff=0.768121, rho=1.000000
-2024-10-07 08:53:34,340 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:53:34.340561', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:35,248 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:53:35,248 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:35,249 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:53:35,249 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:35,249 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:53:35,249 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:35,249 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:53:35,249 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:35,250 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:53:35,250 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:35,250 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:53:35,250 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:45,785 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:53:45,787 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)
-2024-10-07 08:53:45,787 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-10-07T08:53:45.787956', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:45,788 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:53:45,789 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:53:45,789 - using serial LDA version on this node
-2024-10-07 08:53:45,789 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:53:45,789 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:53:45,793 - -7.926 per-word bound, 243.2 perplexity estimate based on a held-out corpus of 1 documents with 2014 words
-2024-10-07 08:53:45,793 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:53:45,794 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.008*"plans" + 0.007*"East" + 0.007*"needs" + 0.006*"progress" + 0.006*"Riding" + 0.005*"10" + 0.005*"30" + 0.005*"partners"
-2024-10-07 08:53:45,794 - topic #1 (0.333): 0.018*"’" + 0.012*"needs" + 0.009*"plans" + 0.008*"well" + 0.007*"progress" + 0.006*"Riding" + 0.006*"East" + 0.005*"education" + 0.005*"good" + 0.005*"10"
-2024-10-07 08:53:45,794 - topic #2 (0.333): 0.010*"’" + 0.009*"plans" + 0.008*"needs" + 0.007*"well" + 0.007*"progress" + 0.005*"Riding" + 0.005*"February" + 0.004*"30" + 0.004*"East" + 0.004*"quality"
-2024-10-07 08:53:45,794 - topic diff=0.776274, rho=1.000000
-2024-10-07 08:53:45,794 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:53:45.794917', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:46,653 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:53:46,653 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:46,654 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:53:46,654 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:46,654 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:53:46,654 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:46,654 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:53:46,654 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:46,655 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:53:46,655 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:46,655 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:53:46,655 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:56,963 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:53:56,967 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)
-2024-10-07 08:53:56,967 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-10-07T08:53:56.967476', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:56,969 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:53:56,969 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:53:56,969 - using serial LDA version on this node
-2024-10-07 08:53:56,970 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:53:56,970 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:53:56,977 - -8.078 per-word bound, 270.2 perplexity estimate based on a held-out corpus of 1 documents with 2220 words
-2024-10-07 08:53:56,977 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:53:56,979 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.009*"plans" + 0.007*"needs" + 0.006*"East" + 0.006*"Sussex" + 0.006*"progress" + 0.006*"impact" + 0.005*"provide" + 0.005*"11"
-2024-10-07 08:53:56,979 - topic #1 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"plans" + 0.006*"East" + 0.006*"progress" + 0.006*"including" + 0.006*"Sussex" + 0.005*"provide" + 0.005*"impact"
-2024-10-07 08:53:56,980 - topic #2 (0.333): 0.015*"’" + 0.010*"well" + 0.007*"needs" + 0.007*"plans" + 0.006*"East" + 0.006*"Sussex" + 0.006*"progress" + 0.006*"experiences" + 0.005*"including" + 0.005*"2023"
-2024-10-07 08:53:56,980 - topic diff=0.754175, rho=1.000000
-2024-10-07 08:53:56,980 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1111, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:53:56.980440', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:53:57,973 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:53:57,973 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:57,973 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:53:57,973 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:57,974 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:53:57,974 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:57,974 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:53:57,974 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:57,974 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:53:57,974 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:53:57,975 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:53:57,975 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:09,715 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:54:09,719 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)
-2024-10-07 08:54:09,719 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-10-07T08:54:09.719446', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:09,721 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:54:09,722 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:54:09,722 - using serial LDA version on this node
-2024-10-07 08:54:09,723 - 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
-2024-10-07 08:54:09,723 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:54:09,731 - -8.011 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2686 words
-2024-10-07 08:54:09,731 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:54:09,733 - topic #0 (0.333): 0.016*"’" + 0.007*"plans" + 0.006*"progress" + 0.005*"family" + 0.005*"supported" + 0.005*"leaders" + 0.005*"experiences" + 0.005*"well" + 0.005*"quality" + 0.005*"new"
-2024-10-07 08:54:09,733 - topic #1 (0.333): 0.020*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"progress" + 0.006*"plans" + 0.005*"understand" + 0.005*"family" + 0.005*"‘" + 0.005*"health" + 0.005*"helped"
-2024-10-07 08:54:09,733 - topic #2 (0.333): 0.016*"’" + 0.007*"progress" + 0.006*"needs" + 0.006*"well" + 0.006*"Essex" + 0.005*"plans" + 0.005*"risk" + 0.005*"experiences" + 0.005*"advisers" + 0.005*"leaders"
-2024-10-07 08:54:09,733 - topic diff=0.810544, rho=1.000000
-2024-10-07 08:54:09,734 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:54:09.734057', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:10,668 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:54:10,668 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:10,668 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:54:10,669 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:10,669 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:54:10,669 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:10,669 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:54:10,669 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:10,670 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:54:10,670 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:10,670 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:54:10,670 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:21,339 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:54:21,341 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)
-2024-10-07 08:54:21,341 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-10-07T08:54:21.341402', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:21,342 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:54:21,342 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:54:21,342 - using serial LDA version on this node
-2024-10-07 08:54:21,343 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:54:21,343 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:54:21,347 - -8.041 per-word bound, 263.4 perplexity estimate based on a held-out corpus of 1 documents with 2356 words
-2024-10-07 08:54:21,347 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:54:21,348 - topic #0 (0.333): 0.011*"’" + 0.006*"effective" + 0.005*"timely" + 0.005*"well" + 0.005*"practice" + 0.005*"quality" + 0.005*"good" + 0.005*"team" + 0.004*"plans" + 0.004*"needs"
-2024-10-07 08:54:21,348 - topic #1 (0.333): 0.009*"’" + 0.006*"effective" + 0.005*"practice" + 0.005*"good" + 0.005*"quality" + 0.005*"well" + 0.004*"timely" + 0.004*"needs" + 0.004*"home" + 0.004*"need"
-2024-10-07 08:54:21,348 - topic #2 (0.333): 0.017*"’" + 0.011*"effective" + 0.009*"good" + 0.008*"practice" + 0.007*"quality" + 0.007*"needs" + 0.006*"well" + 0.006*"early" + 0.006*"timely" + 0.005*"need"
-2024-10-07 08:54:21,349 - topic diff=0.787636, rho=1.000000
-2024-10-07 08:54:21,349 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:54:21.349180', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:22,257 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:54:22,257 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:22,257 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:54:22,257 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:22,257 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:54:22,257 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:22,258 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:54:22,258 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:22,258 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:54:22,258 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:22,258 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:54:22,258 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:33,602 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:54:33,604 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)
-2024-10-07 08:54:33,605 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-10-07T08:54:33.605165', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:33,606 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:54:33,606 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:54:33,606 - using serial LDA version on this node
-2024-10-07 08:54:33,607 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:54:33,607 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:54:33,611 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2579 words
-2024-10-07 08:54:33,611 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:54:33,612 - topic #0 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"2022" + 0.007*"February" + 0.006*"plans" + 0.005*"protection" + 0.005*"progress" + 0.005*"experienced" + 0.005*"Gloucestershire" + 0.005*"family"
-2024-10-07 08:54:33,612 - topic #1 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"2022" + 0.007*"February" + 0.007*"plans" + 0.006*"progress" + 0.005*"well" + 0.005*"timely" + 0.005*"experienced" + 0.004*"good"
-2024-10-07 08:54:33,613 - topic #2 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"plans" + 0.006*"February" + 0.006*"2022" + 0.005*"Gloucestershire" + 0.005*"7" + 0.005*"need" + 0.005*"appropriate"
-2024-10-07 08:54:33,613 - topic diff=0.823067, rho=1.000000
-2024-10-07 08:54:33,613 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:54:33.613303', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:34,730 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:54:34,731 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:34,731 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:54:34,731 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:34,731 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:54:34,731 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:34,731 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:54:34,732 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:34,732 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:54:34,732 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:34,732 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:54:34,732 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:47,701 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:54:47,705 - built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)
-2024-10-07 08:54:47,705 - Dictionary lifecycle event {'msg': "built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)", 'datetime': '2024-10-07T08:54:47.705219', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:47,707 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:54:47,707 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:54:47,707 - using serial LDA version on this node
-2024-10-07 08:54:47,708 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:54:47,708 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:54:47,715 - -8.059 per-word bound, 266.6 perplexity estimate based on a held-out corpus of 1 documents with 2652 words
-2024-10-07 08:54:47,716 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:54:47,718 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"Halton" + 0.006*"many" + 0.006*"quality" + 0.006*"including" + 0.006*"plans" + 0.005*"need" + 0.005*"Leaders" + 0.005*"lack"
-2024-10-07 08:54:47,718 - topic #1 (0.333): 0.015*"’" + 0.007*"Halton" + 0.007*"quality" + 0.006*"needs" + 0.006*"many" + 0.006*"including" + 0.005*"need" + 0.005*"plans" + 0.004*"Leaders" + 0.004*"lack"
-2024-10-07 08:54:47,718 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.005*"protection" + 0.005*"many" + 0.005*"need" + 0.005*"Halton" + 0.005*"quality" + 0.004*"recently" + 0.004*"including" + 0.004*"experiences"
-2024-10-07 08:54:47,718 - topic diff=0.800364, rho=1.000000
-2024-10-07 08:54:47,719 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1172, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:54:47.719095', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:54:48,692 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:54:48,692 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:48,692 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:54:48,692 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:48,692 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:54:48,693 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:48,693 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:54:48,693 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:48,693 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:54:48,693 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:54:48,693 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:54:48,693 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:00,096 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:55:00,098 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)
-2024-10-07 08:55:00,099 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)", 'datetime': '2024-10-07T08:55:00.099092', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:00,100 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:55:00,100 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:55:00,100 - using serial LDA version on this node
-2024-10-07 08:55:00,100 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:55:00,101 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:55:00,104 - -7.973 per-word bound, 251.2 perplexity estimate based on a held-out corpus of 1 documents with 2524 words
-2024-10-07 08:55:00,104 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:55:00,106 - topic #0 (0.333): 0.010*"’" + 0.007*"family" + 0.007*"plans" + 0.006*"well" + 0.006*"progress" + 0.005*"new" + 0.005*"quality" + 0.004*"needs" + 0.004*"carers" + 0.004*"practice"
-2024-10-07 08:55:00,106 - topic #1 (0.333): 0.018*"’" + 0.008*"well" + 0.007*"family" + 0.006*"new" + 0.006*"plans" + 0.006*"achieve" + 0.006*"progress" + 0.006*"quality" + 0.005*"receive" + 0.005*"understand"
-2024-10-07 08:55:00,106 - topic #2 (0.333): 0.019*"’" + 0.008*"new" + 0.007*"progress" + 0.006*"family" + 0.006*"well" + 0.006*"plans" + 0.005*"needs" + 0.005*"quality" + 0.005*"Hampshire" + 0.005*"practice"
-2024-10-07 08:55:00,106 - topic diff=0.814952, rho=1.000000
-2024-10-07 08:55:00,106 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:55:00.106815', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:01,080 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:55:01,080 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:01,080 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:55:01,080 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:01,081 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:55:01,081 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:01,081 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:55:01,081 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:01,081 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:55:01,081 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:01,081 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:55:01,082 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:13,811 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:55:13,814 - built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)
-2024-10-07 08:55:13,814 - Dictionary lifecycle event {'msg': "built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)", 'datetime': '2024-10-07T08:55:13.814893', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:13,816 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:55:13,816 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:55:13,817 - using serial LDA version on this node
-2024-10-07 08:55:13,817 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:55:13,817 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:55:13,822 - -8.072 per-word bound, 269.1 perplexity estimate based on a held-out corpus of 1 documents with 2584 words
-2024-10-07 08:55:13,822 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:55:13,824 - topic #0 (0.333): 0.018*"’" + 0.007*"needs" + 0.007*"Hartlepool" + 0.006*"March" + 0.006*"well" + 0.005*"strong" + 0.005*"leaders" + 0.005*"supported" + 0.005*"practice" + 0.004*"clear"
-2024-10-07 08:55:13,824 - topic #1 (0.333): 0.015*"’" + 0.009*"March" + 0.007*"Hartlepool" + 0.006*"needs" + 0.006*"18" + 0.005*"well" + 0.005*"leaders" + 0.005*"plans" + 0.005*"clear" + 0.004*"strong"
-2024-10-07 08:55:13,824 - topic #2 (0.333): 0.026*"’" + 0.007*"March" + 0.006*"well" + 0.006*"Hartlepool" + 0.006*"needs" + 0.006*"leaders" + 0.005*"effective" + 0.005*"plans" + 0.004*"ensure" + 0.004*"good"
-2024-10-07 08:55:13,824 - topic diff=0.789380, rho=1.000000
-2024-10-07 08:55:13,824 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1171, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:55:13.824975', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:14,830 - Inspection date 2024-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:55:14,830 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:14,830 - Inspection date 2024-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:55:14,831 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:14,831 - Inspection date 2024-03-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:55:14,831 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:14,831 - Inspection date 2024-03-18 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:55:14,831 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:14,831 - Inspection date 2024-03-18 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:55:14,831 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:14,832 - Inspection date 2024-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:55:14,832 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:26,793 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:55:26,795 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
-2024-10-07 08:55:26,795 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-10-07T08:55:26.795480', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:26,796 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:55:26,796 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:55:26,796 - using serial LDA version on this node
-2024-10-07 08:55:26,797 - 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
-2024-10-07 08:55:26,797 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:55:26,801 - -8.043 per-word bound, 263.8 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
-2024-10-07 08:55:26,801 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:55:26,802 - topic #0 (0.333): 0.019*"’" + 0.006*"practice" + 0.006*"needs" + 0.005*"lack" + 0.005*"many" + 0.004*"18" + 0.004*"impact" + 0.004*"carers" + 0.004*"plans" + 0.004*"quality"
-2024-10-07 08:55:26,802 - topic #1 (0.333): 0.018*"’" + 0.005*"Herefordshire" + 0.005*"impact" + 0.005*"practice" + 0.005*"lack" + 0.004*"29" + 0.004*"needs" + 0.004*"many" + 0.004*"ensure" + 0.004*"progress"
-2024-10-07 08:55:26,802 - topic #2 (0.333): 0.015*"’" + 0.006*"Herefordshire" + 0.005*"lack" + 0.005*"practice" + 0.005*"agency" + 0.005*"plans" + 0.004*"many" + 0.004*"harm" + 0.004*"impact" + 0.004*"needs"
-2024-10-07 08:55:26,803 - topic diff=0.788639, rho=1.000000
-2024-10-07 08:55:26,803 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:55:26.803169', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:27,636 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:55:27,636 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:27,637 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:55:27,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:27,637 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:55:27,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:27,637 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:55:27,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:27,638 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:55:27,638 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:27,638 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:55:27,638 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:39,670 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:55:39,672 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)
-2024-10-07 08:55:39,672 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-10-07T08:55:39.672862', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:39,673 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:55:39,674 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:55:39,674 - using serial LDA version on this node
-2024-10-07 08:55:39,674 - 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
-2024-10-07 08:55:39,674 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:55:39,678 - -8.131 per-word bound, 280.4 perplexity estimate based on a held-out corpus of 1 documents with 2456 words
-2024-10-07 08:55:39,678 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:55:39,680 - topic #0 (0.333): 0.020*"’" + 0.006*"Hertfordshire" + 0.006*"well" + 0.004*"receive" + 0.004*"needs" + 0.004*"27" + 0.004*"23" + 0.004*"effective" + 0.004*"leaders" + 0.004*"plans"
-2024-10-07 08:55:39,680 - topic #1 (0.333): 0.019*"’" + 0.008*"Hertfordshire" + 0.007*"well" + 0.007*"needs" + 0.005*"plans" + 0.004*"family" + 0.004*"risk" + 0.004*"effective" + 0.004*"receive" + 0.004*"January"
-2024-10-07 08:55:39,680 - topic #2 (0.333): 0.027*"’" + 0.006*"needs" + 0.006*"well" + 0.006*"receive" + 0.005*"Hertfordshire" + 0.005*"plans" + 0.005*"2023" + 0.005*"need" + 0.004*"positive" + 0.004*"23"
-2024-10-07 08:55:39,680 - topic diff=0.792795, rho=1.000000
-2024-10-07 08:55:39,680 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:55:39.680951', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:41,329 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:55:41,329 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:41,330 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:55:41,330 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:41,330 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:55:41,330 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:41,330 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:55:41,330 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:41,330 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:55:41,331 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:41,331 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:55:41,331 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:50,742 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:55:50,744 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)
-2024-10-07 08:55:50,744 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-10-07T08:55:50.744676', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:50,745 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:55:50,745 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:55:50,745 - using serial LDA version on this node
-2024-10-07 08:55:50,746 - 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
-2024-10-07 08:55:50,746 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:55:50,749 - -7.955 per-word bound, 248.2 perplexity estimate based on a held-out corpus of 1 documents with 1934 words
-2024-10-07 08:55:50,749 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:55:50,751 - topic #0 (0.333): 0.019*"’" + 0.008*"leaders" + 0.007*"well" + 0.006*"practice" + 0.006*"Senior" + 0.005*"plans" + 0.005*"good" + 0.005*"needs" + 0.005*"progress" + 0.005*"3"
-2024-10-07 08:55:50,751 - topic #1 (0.333): 0.011*"’" + 0.009*"leaders" + 0.006*"supported" + 0.005*"needs" + 0.005*"progress" + 0.005*"improve" + 0.005*"plans" + 0.004*"Isle" + 0.004*"well" + 0.004*"PAs"
-2024-10-07 08:55:50,751 - topic #2 (0.333): 0.021*"’" + 0.008*"leaders" + 0.006*"needs" + 0.006*"Wight" + 0.005*"Isle" + 0.005*"3" + 0.005*"improve" + 0.005*"PAs" + 0.005*"information" + 0.005*"Senior"
-2024-10-07 08:55:50,751 - topic diff=0.771167, rho=1.000000
-2024-10-07 08:55:50,751 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:55:50.751700', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:55:51,735 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:55:51,735 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:51,736 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:55:51,736 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:51,736 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:55:51,736 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:51,736 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:55:51,736 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:51,737 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:55:51,737 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:55:51,737 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:55:51,737 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:04,122 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:56:04,125 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)
-2024-10-07 08:56:04,125 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-10-07T08:56:04.125455', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:04,126 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:56:04,126 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:56:04,127 - using serial LDA version on this node
-2024-10-07 08:56:04,127 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:56:04,127 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:56:04,131 - -8.167 per-word bound, 287.4 perplexity estimate based on a held-out corpus of 1 documents with 2888 words
-2024-10-07 08:56:04,131 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:56:04,133 - topic #0 (0.333): 0.023*"’" + 0.010*"Kent" + 0.006*"needs" + 0.006*"Council" + 0.006*"supported" + 0.005*"County" + 0.005*"well" + 0.005*"practice" + 0.005*"progress" + 0.004*"leaders"
-2024-10-07 08:56:04,133 - topic #1 (0.333): 0.013*"’" + 0.008*"Kent" + 0.007*"well" + 0.006*"needs" + 0.005*"Council" + 0.005*"County" + 0.004*"9" + 0.004*"supported" + 0.004*"including" + 0.004*"progress"
-2024-10-07 08:56:04,133 - topic #2 (0.333): 0.016*"’" + 0.010*"Kent" + 0.009*"needs" + 0.007*"well" + 0.006*"supported" + 0.006*"Council" + 0.005*"progress" + 0.005*"County" + 0.004*"leaders" + 0.004*"practice"
-2024-10-07 08:56:04,133 - topic diff=0.800288, rho=1.000000
-2024-10-07 08:56:04,134 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1298, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:56:04.133982', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:05,085 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:56:05,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:05,085 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:56:05,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:05,085 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:56:05,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:05,086 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:56:05,086 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:05,086 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:56:05,086 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:05,086 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:56:05,086 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:15,003 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:56:15,005 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)
-2024-10-07 08:56:15,005 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-10-07T08:56:15.005961', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:15,006 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:56:15,007 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:56:15,007 - using serial LDA version on this node
-2024-10-07 08:56:15,007 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:56:15,007 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:56:15,011 - -7.948 per-word bound, 246.9 perplexity estimate based on a held-out corpus of 1 documents with 1970 words
-2024-10-07 08:56:15,011 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:56:15,012 - topic #0 (0.333): 0.015*"’" + 0.008*"practice" + 0.007*"number" + 0.007*"planning" + 0.006*"well" + 0.006*"protection" + 0.006*"management" + 0.006*"need" + 0.006*"impact" + 0.006*"Hull"
-2024-10-07 08:56:15,012 - topic #1 (0.333): 0.015*"’" + 0.007*"number" + 0.007*"planning" + 0.006*"need" + 0.006*"well" + 0.006*"Hull" + 0.006*"risks" + 0.006*"management" + 0.005*"protection" + 0.005*"oversight"
-2024-10-07 08:56:15,012 - topic #2 (0.333): 0.018*"’" + 0.006*"protection" + 0.006*"planning" + 0.006*"number" + 0.005*"well" + 0.005*"agency" + 0.004*"Hull" + 0.004*"small" + 0.004*"risks" + 0.004*"team"
-2024-10-07 08:56:15,012 - topic diff=0.759500, rho=1.000000
-2024-10-07 08:56:15,013 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:56:15.013044', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:15,938 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:56:15,938 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:15,938 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:56:15,939 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:15,939 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:56:15,939 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:15,939 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:56:15,939 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:15,940 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:56:15,940 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:15,940 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:56:15,940 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:28,024 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:56:28,026 - built Dictionary<963 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2139 corpus positions)
-2024-10-07 08:56:28,026 - Dictionary lifecycle event {'msg': "built Dictionary<963 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2139 corpus positions)", 'datetime': '2024-10-07T08:56:28.026347', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:28,027 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:56:28,027 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:56:28,027 - using serial LDA version on this node
-2024-10-07 08:56:28,028 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:56:28,028 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:56:28,031 - -7.874 per-word bound, 234.6 perplexity estimate based on a held-out corpus of 1 documents with 2139 words
-2024-10-07 08:56:28,031 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:56:28,032 - topic #0 (0.333): 0.025*"’" + 0.009*"needs" + 0.008*"Kirklees" + 0.008*"plans" + 0.006*"impact" + 0.006*"effective" + 0.006*"leaders" + 0.005*"need" + 0.005*"well" + 0.005*"timely"
-2024-10-07 08:56:28,033 - topic #1 (0.333): 0.017*"’" + 0.008*"effective" + 0.007*"well" + 0.007*"Kirklees" + 0.006*"plans" + 0.006*"needs" + 0.006*"ensure" + 0.006*"impact" + 0.005*"need" + 0.005*"quality"
-2024-10-07 08:56:28,033 - topic #2 (0.333): 0.018*"’" + 0.007*"plans" + 0.006*"Kirklees" + 0.006*"effective" + 0.006*"needs" + 0.005*"quality" + 0.005*"need" + 0.005*"well" + 0.004*"accommodation" + 0.004*"impact"
-2024-10-07 08:56:28,033 - topic diff=0.794831, rho=1.000000
-2024-10-07 08:56:28,033 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=963, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:56:28.033605', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:29,002 - Inspection date 2024-07-08 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:56:29,002 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:29,002 - Inspection date 2024-07-08 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:56:29,002 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:29,003 - Inspection date 2024-07-08 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:56:29,003 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:29,003 - Inspection date 2024-07-08 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:56:29,003 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:29,003 - Inspection date 2024-07-08 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:56:29,003 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:29,004 - Inspection date 2024-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:56:29,004 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:38,060 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:56:38,062 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)
-2024-10-07 08:56:38,063 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-10-07T08:56:38.063121', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:38,064 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:56:38,064 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:56:38,064 - using serial LDA version on this node
-2024-10-07 08:56:38,065 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:56:38,065 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:56:38,070 - -7.831 per-word bound, 227.7 perplexity estimate based on a held-out corpus of 1 documents with 1837 words
-2024-10-07 08:56:38,070 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:56:38,072 - topic #0 (0.333): 0.016*"’" + 0.009*"progress" + 0.007*"quality" + 0.007*"needs" + 0.007*"Knowsley" + 0.006*"plans" + 0.006*"2021" + 0.006*"abuse" + 0.005*"experiences" + 0.005*"impact"
-2024-10-07 08:56:38,072 - topic #1 (0.333): 0.015*"’" + 0.008*"progress" + 0.008*"plans" + 0.007*"needs" + 0.006*"quality" + 0.006*"Knowsley" + 0.006*"need" + 0.006*"good" + 0.005*"2021" + 0.005*"11"
-2024-10-07 08:56:38,073 - topic #2 (0.333): 0.012*"’" + 0.007*"needs" + 0.007*"progress" + 0.007*"plans" + 0.007*"quality" + 0.006*"2021" + 0.005*"22" + 0.005*"Knowsley" + 0.005*"need" + 0.005*"impact"
-2024-10-07 08:56:38,073 - topic diff=0.744480, rho=1.000000
-2024-10-07 08:56:38,073 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=886, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:56:38.073602', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:38,946 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:56:38,946 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:38,946 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:56:38,946 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:38,946 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:56:38,947 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:38,947 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:56:38,947 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:38,947 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:56:38,947 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:38,947 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:56:38,948 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:49,640 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:56:49,642 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)
-2024-10-07 08:56:49,643 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-10-07T08:56:49.643127', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:49,644 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:56:49,644 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:56:49,644 - using serial LDA version on this node
-2024-10-07 08:56:49,644 - 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
-2024-10-07 08:56:49,644 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:56:49,648 - -7.973 per-word bound, 251.3 perplexity estimate based on a held-out corpus of 1 documents with 2263 words
-2024-10-07 08:56:49,648 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:56:49,650 - topic #0 (0.333): 0.015*"’" + 0.007*"need" + 0.005*"needs" + 0.005*"well" + 0.005*"Lancashire" + 0.005*"plans" + 0.005*"supported" + 0.005*"parents" + 0.004*"practice" + 0.004*"health"
-2024-10-07 08:56:49,650 - topic #1 (0.333): 0.018*"’" + 0.011*"well" + 0.008*"needs" + 0.008*"need" + 0.006*"Lancashire" + 0.006*"positive" + 0.006*"supported" + 0.005*"homes" + 0.005*"health" + 0.005*"plans"
-2024-10-07 08:56:49,650 - topic #2 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"Lancashire" + 0.006*"need" + 0.006*"plans" + 0.005*"practice" + 0.005*"progress" + 0.005*"information" + 0.005*"live"
-2024-10-07 08:56:49,651 - topic diff=0.780913, rho=1.000000
-2024-10-07 08:56:49,651 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:56:49.651201', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:56:50,638 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:56:50,638 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:50,638 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:56:50,638 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:50,638 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:56:50,639 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:50,639 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:56:50,639 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:50,639 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:56:50,639 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:56:50,639 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:56:50,639 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:01,543 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:57:01,545 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)
-2024-10-07 08:57:01,545 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-10-07T08:57:01.545734', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:01,546 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:57:01,546 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:57:01,547 - using serial LDA version on this node
-2024-10-07 08:57:01,547 - 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
-2024-10-07 08:57:01,547 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:57:01,551 - -8.011 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2261 words
-2024-10-07 08:57:01,551 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:57:01,552 - topic #0 (0.333): 0.018*"’" + 0.008*"Leeds" + 0.008*"needs" + 0.005*"well" + 0.005*"risk" + 0.005*"making" + 0.005*"4" + 0.004*"ensure" + 0.004*"21" + 0.004*"protection"
-2024-10-07 08:57:01,552 - topic #1 (0.333): 0.012*"’" + 0.006*"Leeds" + 0.006*"well" + 0.005*"needs" + 0.005*"risk" + 0.004*"benefit" + 0.004*"practice" + 0.004*"2022" + 0.004*"plans" + 0.004*"leaders"
-2024-10-07 08:57:01,553 - topic #2 (0.333): 0.016*"’" + 0.007*"needs" + 0.007*"Leeds" + 0.006*"well" + 0.006*"practice" + 0.006*"risk" + 0.005*"ensure" + 0.005*"4" + 0.005*"plans" + 0.005*"protection"
-2024-10-07 08:57:01,553 - topic diff=0.782002, rho=1.000000
-2024-10-07 08:57:01,553 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1071, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:57:01.553444', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:02,460 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:57:02,460 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:02,460 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:57:02,460 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:02,461 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:57:02,461 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:02,461 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:57:02,461 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:02,461 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:57:02,461 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:02,461 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:57:02,462 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:11,790 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:57:11,792 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)
-2024-10-07 08:57:11,792 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-10-07T08:57:11.792956', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:11,793 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:57:11,794 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:57:11,794 - using serial LDA version on this node
-2024-10-07 08:57:11,794 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:57:11,794 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:57:11,798 - -7.871 per-word bound, 234.2 perplexity estimate based on a held-out corpus of 1 documents with 1950 words
-2024-10-07 08:57:11,798 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:57:11,799 - topic #0 (0.333): 0.023*"’" + 0.010*"2021" + 0.009*"Leicester" + 0.009*"well" + 0.008*"needs" + 0.006*"ensure" + 0.006*"number" + 0.006*"improve" + 0.005*"20" + 0.005*"1"
-2024-10-07 08:57:11,800 - topic #1 (0.333): 0.016*"’" + 0.008*"2021" + 0.008*"well" + 0.006*"Leicester" + 0.005*"ensure" + 0.005*"good" + 0.005*"needs" + 0.005*"1" + 0.005*"number" + 0.004*"high"
-2024-10-07 08:57:11,800 - topic #2 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"good" + 0.006*"needs" + 0.006*"Leicester" + 0.006*"2021" + 0.005*"20" + 0.005*"including" + 0.005*"number" + 0.005*"1"
-2024-10-07 08:57:11,800 - topic diff=0.784027, rho=1.000000
-2024-10-07 08:57:11,800 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=932, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:57:11.800516', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:12,779 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:57:12,780 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:12,780 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:57:12,780 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:12,781 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:57:12,781 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:12,781 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:57:12,781 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:12,781 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:57:12,781 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:12,782 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:57:12,782 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:27,002 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:57:27,005 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)
-2024-10-07 08:57:27,005 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)", 'datetime': '2024-10-07T08:57:27.005389', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:27,006 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:57:27,006 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:57:27,006 - using serial LDA version on this node
-2024-10-07 08:57:27,007 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:57:27,007 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:57:27,011 - -8.102 per-word bound, 274.8 perplexity estimate based on a held-out corpus of 1 documents with 2745 words
-2024-10-07 08:57:27,011 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:57:27,013 - topic #0 (0.333): 0.011*"’" + 0.008*"well" + 0.005*"Leicestershire" + 0.005*"ensure" + 0.005*"understand" + 0.005*"family" + 0.004*"experiences" + 0.004*"need" + 0.004*"quality" + 0.004*"progress"
-2024-10-07 08:57:27,013 - topic #1 (0.333): 0.025*"’" + 0.010*"well" + 0.007*"needs" + 0.007*"Leicestershire" + 0.006*"need" + 0.006*"family" + 0.006*"PAs" + 0.006*"experiences" + 0.005*"understand" + 0.005*"plans"
-2024-10-07 08:57:27,013 - topic #2 (0.333): 0.013*"’" + 0.007*"Leicestershire" + 0.007*"well" + 0.006*"family" + 0.005*"progress" + 0.005*"plans" + 0.005*"experiences" + 0.004*"risk" + 0.004*"needs" + 0.004*"need"
-2024-10-07 08:57:27,013 - topic diff=0.822323, rho=1.000000
-2024-10-07 08:57:27,013 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:57:27.013641', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:27,984 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:57:27,984 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:27,985 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:57:27,985 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:27,985 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:57:27,985 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:27,985 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:57:27,985 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:27,986 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:57:27,986 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:27,986 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:57:27,986 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:41,584 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:57:41,587 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)
-2024-10-07 08:57:41,587 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-10-07T08:57:41.587795', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:41,589 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:57:41,590 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:57:41,590 - using serial LDA version on this node
-2024-10-07 08:57:41,590 - 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
-2024-10-07 08:57:41,591 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:57:41,598 - -8.191 per-word bound, 292.2 perplexity estimate based on a held-out corpus of 1 documents with 2927 words
-2024-10-07 08:57:41,599 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:57:41,601 - topic #0 (0.333): 0.018*"’" + 0.008*"Lincolnshire" + 0.007*"needs" + 0.006*"plans" + 0.005*"well" + 0.005*"24" + 0.004*"progress" + 0.004*"education" + 0.004*"need" + 0.004*"effective"
-2024-10-07 08:57:41,601 - topic #1 (0.333): 0.019*"’" + 0.007*"Lincolnshire" + 0.006*"well" + 0.004*"needs" + 0.004*"progress" + 0.004*"family" + 0.004*"April" + 0.004*"28" + 0.003*"offer" + 0.003*"education"
-2024-10-07 08:57:41,602 - topic #2 (0.333): 0.026*"’" + 0.008*"needs" + 0.007*"Lincolnshire" + 0.006*"well" + 0.005*"plans" + 0.005*"family" + 0.005*"progress" + 0.004*"2023" + 0.004*"24" + 0.004*"28"
-2024-10-07 08:57:41,602 - topic diff=0.791934, rho=1.000000
-2024-10-07 08:57:41,602 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1323, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:57:41.602432', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:42,640 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:57:42,641 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:42,641 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:57:42,641 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:42,641 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:57:42,641 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:42,641 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:57:42,642 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:42,642 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:57:42,642 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:42,642 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:57:42,642 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:55,721 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:57:55,724 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
-2024-10-07 08:57:55,724 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-10-07T08:57:55.724365', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:55,725 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:57:55,725 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:57:55,725 - using serial LDA version on this node
-2024-10-07 08:57:55,726 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:57:55,726 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:57:55,730 - -7.992 per-word bound, 254.6 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
-2024-10-07 08:57:55,730 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:57:55,731 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.008*"need" + 0.006*"always" + 0.006*"practice" + 0.006*"Liverpool" + 0.005*"protection" + 0.005*"met" + 0.005*"quality" + 0.004*"24"
-2024-10-07 08:57:55,731 - topic #1 (0.333): 0.023*"’" + 0.007*"practice" + 0.007*"needs" + 0.006*"always" + 0.006*"need" + 0.006*"quality" + 0.005*"timely" + 0.005*"13" + 0.005*"protection" + 0.005*"Liverpool"
-2024-10-07 08:57:55,732 - topic #2 (0.333): 0.019*"’" + 0.007*"Liverpool" + 0.006*"quality" + 0.006*"always" + 0.006*"practice" + 0.006*"needs" + 0.005*"PAs" + 0.005*"including" + 0.004*"need" + 0.004*"receive"
-2024-10-07 08:57:55,732 - topic diff=0.838463, rho=1.000000
-2024-10-07 08:57:55,732 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1134, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:57:55.732307', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:57:56,635 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:57:56,635 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:56,635 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:57:56,636 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:56,636 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:57:56,636 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:56,636 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:57:56,636 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:56,636 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:57:56,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:57:56,637 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:57:56,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:09,028 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:58:09,030 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)
-2024-10-07 08:58:09,030 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-10-07T08:58:09.030641', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:09,031 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:58:09,031 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:58:09,032 - using serial LDA version on this node
-2024-10-07 08:58:09,032 - 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
-2024-10-07 08:58:09,032 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:58:09,036 - -8.095 per-word bound, 273.5 perplexity estimate based on a held-out corpus of 1 documents with 2610 words
-2024-10-07 08:58:09,036 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:58:09,038 - topic #0 (0.333): 0.022*"’" + 0.008*"needs" + 0.006*"plans" + 0.005*"progress" + 0.005*"practice" + 0.005*"planning" + 0.005*"well" + 0.005*"carers" + 0.005*"good" + 0.004*"Dagenham"
-2024-10-07 08:58:09,038 - topic #1 (0.333): 0.026*"’" + 0.008*"needs" + 0.007*"good" + 0.006*"plans" + 0.006*"well" + 0.005*"information" + 0.005*"carers" + 0.004*"ensure" + 0.004*"London" + 0.004*"e"
-2024-10-07 08:58:09,038 - topic #2 (0.333): 0.018*"’" + 0.007*"needs" + 0.005*"good" + 0.005*"10" + 0.005*"carers" + 0.005*"practice" + 0.005*"well" + 0.004*"Barking" + 0.004*"information" + 0.004*"e"
-2024-10-07 08:58:09,038 - topic diff=0.796903, rho=1.000000
-2024-10-07 08:58:09,038 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1193, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:58:09.038852', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:09,953 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:58:09,953 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:09,953 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:58:09,953 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:09,954 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:58:09,954 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:09,954 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:58:09,954 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:09,954 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:58:09,954 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:09,955 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:58:09,955 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:21,837 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:58:21,839 - built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)
-2024-10-07 08:58:21,839 - Dictionary lifecycle event {'msg': "built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)", 'datetime': '2024-10-07T08:58:21.839897', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:21,840 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:58:21,841 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:58:21,841 - using serial LDA version on this node
-2024-10-07 08:58:21,841 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:58:21,841 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:58:21,845 - -8.048 per-word bound, 264.7 perplexity estimate based on a held-out corpus of 1 documents with 2445 words
-2024-10-07 08:58:21,845 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:58:21,847 - topic #0 (0.333): 0.029*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"plans" + 0.007*"Barnet" + 0.005*"experiences" + 0.005*"effective" + 0.005*"14" + 0.005*"risk" + 0.005*"10"
-2024-10-07 08:58:21,847 - topic #1 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"plans" + 0.007*"well" + 0.006*"Barnet" + 0.005*"2024" + 0.004*"understand" + 0.004*"carers" + 0.004*"10" + 0.004*"risk"
-2024-10-07 08:58:21,847 - topic #2 (0.333): 0.014*"’" + 0.008*"Barnet" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.004*"experiences" + 0.004*"strong" + 0.004*"progress" + 0.004*"carers" + 0.004*"10"
-2024-10-07 08:58:21,847 - topic diff=0.793983, rho=1.000000
-2024-10-07 08:58:21,847 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1132, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:58:21.847785', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:22,853 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:58:22,853 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:22,854 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:58:22,854 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:22,854 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:58:22,854 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:22,854 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:58:22,854 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:22,855 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:58:22,855 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:22,855 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:58:22,855 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:35,144 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:58:35,147 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)
-2024-10-07 08:58:35,147 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-10-07T08:58:35.147230', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:35,148 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:58:35,148 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:58:35,148 - using serial LDA version on this node
-2024-10-07 08:58:35,149 - 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
-2024-10-07 08:58:35,149 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:58:35,153 - -8.099 per-word bound, 274.3 perplexity estimate based on a held-out corpus of 1 documents with 2563 words
-2024-10-07 08:58:35,153 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:58:35,154 - topic #0 (0.333): 0.014*"’" + 0.006*"need" + 0.005*"10" + 0.005*"Bexley" + 0.005*"effective" + 0.004*"including" + 0.004*"needs" + 0.004*"practice" + 0.004*"plans" + 0.004*"clear"
-2024-10-07 08:58:35,154 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"plans" + 0.005*"effective" + 0.005*"10" + 0.005*"need" + 0.005*"Bexley" + 0.005*"practice" + 0.004*"6"
-2024-10-07 08:58:35,155 - topic #2 (0.333): 0.022*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"effective" + 0.006*"Bexley" + 0.005*"need" + 0.005*"plans" + 0.005*"make" + 0.005*"progress" + 0.004*"6"
-2024-10-07 08:58:35,155 - topic diff=0.782137, rho=1.000000
-2024-10-07 08:58:35,155 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1190, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:58:35.155471', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:36,207 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:58:36,208 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:36,208 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:58:36,208 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:36,209 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:58:36,210 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:36,211 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:58:36,211 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:36,211 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:58:36,213 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:36,213 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:58:36,213 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:47,162 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:58:47,164 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)
-2024-10-07 08:58:47,164 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-10-07T08:58:47.164552', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:47,165 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:58:47,165 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:58:47,165 - using serial LDA version on this node
-2024-10-07 08:58:47,166 - 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
-2024-10-07 08:58:47,166 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:58:47,169 - -7.927 per-word bound, 243.4 perplexity estimate based on a held-out corpus of 1 documents with 2371 words
-2024-10-07 08:58:47,170 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:58:47,171 - topic #0 (0.333): 0.014*"’" + 0.009*"well" + 0.005*"leaders" + 0.005*"progress" + 0.005*"senior" + 0.005*"plans" + 0.005*"practice" + 0.004*"information" + 0.004*"Brent" + 0.004*"good"
-2024-10-07 08:58:47,171 - topic #1 (0.333): 0.022*"’" + 0.008*"well" + 0.007*"plans" + 0.007*"leaders" + 0.007*"number" + 0.007*"progress" + 0.007*"good" + 0.006*"Brent" + 0.006*"practice" + 0.005*"senior"
-2024-10-07 08:58:47,171 - topic #2 (0.333): 0.013*"’" + 0.009*"well" + 0.008*"leaders" + 0.007*"quality" + 0.006*"plans" + 0.006*"progress" + 0.005*"good" + 0.005*"Brent" + 0.005*"needs" + 0.004*"practice"
-2024-10-07 08:58:47,171 - topic diff=0.826619, rho=1.000000
-2024-10-07 08:58:47,172 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:58:47.172144', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:58:48,199 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:58:48,199 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:48,199 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:58:48,199 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:48,199 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:58:48,200 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:48,200 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:58:48,200 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:48,200 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:58:48,200 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:58:48,201 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:58:48,201 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:01,326 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:59:01,328 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)
-2024-10-07 08:59:01,328 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-10-07T08:59:01.328691', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:01,329 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:59:01,329 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:59:01,330 - using serial LDA version on this node
-2024-10-07 08:59:01,330 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:59:01,330 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:59:01,335 - -8.182 per-word bound, 290.4 perplexity estimate based on a held-out corpus of 1 documents with 2640 words
-2024-10-07 08:59:01,335 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:59:01,336 - topic #0 (0.333): 0.023*"’" + 0.011*"Bromley" + 0.007*"needs" + 0.007*"well" + 0.006*"leaders" + 0.005*"plans" + 0.005*"helping" + 0.005*"YPAs" + 0.005*"practice" + 0.004*"November"
-2024-10-07 08:59:01,337 - topic #1 (0.333): 0.018*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"Bromley" + 0.005*"plans" + 0.005*"health" + 0.005*"practice" + 0.004*"leaders" + 0.004*"progress" + 0.004*"2023"
-2024-10-07 08:59:01,337 - topic #2 (0.333): 0.017*"’" + 0.010*"Bromley" + 0.007*"well" + 0.006*"plans" + 0.006*"needs" + 0.005*"leaders" + 0.005*"practice" + 0.005*"education" + 0.005*"relationships" + 0.004*"health"
-2024-10-07 08:59:01,337 - topic diff=0.769265, rho=1.000000
-2024-10-07 08:59:01,337 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1266, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:59:01.337522', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:02,379 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:59:02,379 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:02,380 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:59:02,380 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:02,380 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:59:02,380 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:02,380 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:59:02,380 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:02,381 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:59:02,381 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:02,381 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:59:02,381 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:11,045 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:59:11,047 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)
-2024-10-07 08:59:11,047 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-10-07T08:59:11.047171', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:11,048 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:59:11,048 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:59:11,048 - using serial LDA version on this node
-2024-10-07 08:59:11,048 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 08:59:11,048 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:59:11,052 - -8.061 per-word bound, 267.0 perplexity estimate based on a held-out corpus of 1 documents with 1735 words
-2024-10-07 08:59:11,052 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:59:11,053 - topic #0 (0.333): 0.013*"’" + 0.008*"leaders" + 0.007*"practice" + 0.006*"response" + 0.005*"well" + 0.005*"25" + 0.005*"protection" + 0.005*"needs" + 0.005*"Camden" + 0.005*"appropriate"
-2024-10-07 08:59:11,053 - topic #1 (0.333): 0.010*"Camden" + 0.010*"’" + 0.006*"practice" + 0.005*"protection" + 0.005*"29" + 0.005*"leaders" + 0.005*"needs" + 0.004*"well" + 0.004*"2022" + 0.004*"April"
-2024-10-07 08:59:11,054 - topic #2 (0.333): 0.008*"’" + 0.006*"Camden" + 0.006*"leaders" + 0.006*"well" + 0.005*"practice" + 0.005*"needs" + 0.004*"appropriate" + 0.004*"response" + 0.004*"protection" + 0.003*"2022"
-2024-10-07 08:59:11,054 - topic diff=0.700036, rho=1.000000
-2024-10-07 08:59:11,054 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=993, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:59:11.054350', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:11,962 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:59:11,962 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:11,963 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:59:11,963 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:11,963 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:59:11,963 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:11,963 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:59:11,963 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:11,964 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:59:11,964 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:11,964 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:59:11,964 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:23,287 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:59:23,289 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)
-2024-10-07 08:59:23,289 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-10-07T08:59:23.289753', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:23,290 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:59:23,290 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:59:23,291 - using serial LDA version on this node
-2024-10-07 08:59:23,291 - 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
-2024-10-07 08:59:23,291 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:59:23,295 - -7.985 per-word bound, 253.3 perplexity estimate based on a held-out corpus of 1 documents with 2209 words
-2024-10-07 08:59:23,295 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:59:23,296 - topic #0 (0.333): 0.011*"’" + 0.008*"needs" + 0.008*"well" + 0.006*"effective" + 0.006*"Croydon" + 0.006*"improved" + 0.005*"quality" + 0.005*"good" + 0.005*"health" + 0.005*"plans"
-2024-10-07 08:59:23,296 - topic #1 (0.333): 0.009*"’" + 0.006*"well" + 0.006*"needs" + 0.006*"Senior" + 0.005*"good" + 0.005*"quality" + 0.005*"ensure" + 0.005*"risk" + 0.005*"Croydon" + 0.005*"health"
-2024-10-07 08:59:23,296 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"need" + 0.007*"needs" + 0.006*"Croydon" + 0.005*"However" + 0.005*"Senior" + 0.005*"quality" + 0.005*"ensure" + 0.005*"arrangements"
-2024-10-07 08:59:23,297 - topic diff=0.772138, rho=1.000000
-2024-10-07 08:59:23,297 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:59:23.297186', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:24,425 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:59:24,425 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:24,426 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:59:24,426 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:24,426 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:59:24,426 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:24,426 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:59:24,427 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:24,427 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:59:24,427 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:24,427 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:59:24,427 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:36,277 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:59:36,279 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)
-2024-10-07 08:59:36,280 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)", 'datetime': '2024-10-07T08:59:36.280082', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:36,281 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:59:36,281 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:59:36,281 - using serial LDA version on this node
-2024-10-07 08:59:36,282 - 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
-2024-10-07 08:59:36,282 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:59:36,285 - -8.052 per-word bound, 265.4 perplexity estimate based on a held-out corpus of 1 documents with 2365 words
-2024-10-07 08:59:36,285 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:59:36,287 - topic #0 (0.333): 0.022*"’" + 0.009*"Ealing" + 0.008*"needs" + 0.008*"well" + 0.007*"plans" + 0.006*"progress" + 0.006*"need" + 0.005*"London" + 0.005*"effective" + 0.005*"3"
-2024-10-07 08:59:36,287 - topic #1 (0.333): 0.011*"’" + 0.008*"well" + 0.006*"Ealing" + 0.005*"needs" + 0.005*"plans" + 0.004*"progress" + 0.004*"need" + 0.004*"quality" + 0.004*"effective" + 0.003*"good"
-2024-10-07 08:59:36,287 - topic #2 (0.333): 0.015*"’" + 0.008*"Ealing" + 0.006*"well" + 0.006*"progress" + 0.005*"effective" + 0.005*"including" + 0.005*"3" + 0.004*"Borough" + 0.004*"April" + 0.004*"good"
-2024-10-07 08:59:36,287 - topic diff=0.802784, rho=1.000000
-2024-10-07 08:59:36,288 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:59:36.287992', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:37,396 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:59:37,396 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:37,397 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:59:37,397 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:37,397 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:59:37,397 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:37,397 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:59:37,397 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:37,398 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:59:37,398 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:37,398 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:59:37,398 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:49,511 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 08:59:49,513 - built Dictionary<1108 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
-2024-10-07 08:59:49,514 - Dictionary lifecycle event {'msg': "built Dictionary<1108 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-10-07T08:59:49.514007', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:49,515 - using symmetric alpha at 0.3333333333333333
-2024-10-07 08:59:49,515 - using symmetric eta at 0.3333333333333333
-2024-10-07 08:59:49,515 - using serial LDA version on this node
-2024-10-07 08:59:49,515 - 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
-2024-10-07 08:59:49,516 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 08:59:49,519 - -8.000 per-word bound, 256.0 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
-2024-10-07 08:59:49,519 - PROGRESS: pass 0, at document #1/1
-2024-10-07 08:59:49,521 - topic #0 (0.333): 0.012*"’" + 0.011*"needs" + 0.009*"well" + 0.007*"plans" + 0.006*"Enfield" + 0.005*"receive" + 0.005*"practice" + 0.005*"good" + 0.005*"timely" + 0.005*"ensure"
-2024-10-07 08:59:49,521 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"plans" + 0.007*"Enfield" + 0.007*"well" + 0.006*"need" + 0.005*"receive" + 0.004*"protection" + 0.004*"timely" + 0.004*"practice"
-2024-10-07 08:59:49,521 - topic #2 (0.333): 0.021*"’" + 0.011*"needs" + 0.010*"well" + 0.008*"Enfield" + 0.006*"plans" + 0.006*"need" + 0.005*"timely" + 0.005*"receive" + 0.005*"practice" + 0.005*"education"
-2024-10-07 08:59:49,521 - topic diff=0.800080, rho=1.000000
-2024-10-07 08:59:49,521 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1108, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T08:59:49.521865', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 08:59:50,467 - Inspection date 2024-07-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 08:59:50,468 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:50,468 - Inspection date 2024-07-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 08:59:50,468 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:50,468 - Inspection date 2024-07-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 08:59:50,468 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:50,469 - Inspection date 2024-07-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 08:59:50,469 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:50,469 - Inspection date 2024-07-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 08:59:50,469 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 08:59:50,469 - Inspection date 2024-07-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 08:59:50,469 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:01,605 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:00:01,607 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)
-2024-10-07 09:00:01,607 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)", 'datetime': '2024-10-07T09:00:01.607407', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:01,608 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:00:01,608 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:00:01,608 - using serial LDA version on this node
-2024-10-07 09:00:01,609 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:00:01,609 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:00:01,612 - -7.988 per-word bound, 253.9 perplexity estimate based on a held-out corpus of 1 documents with 2078 words
-2024-10-07 09:00:01,612 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:00:01,614 - topic #0 (0.333): 0.017*"’" + 0.012*"Greenwich" + 0.009*"well" + 0.008*"needs" + 0.005*"carers" + 0.005*"7" + 0.005*"3" + 0.005*"progress" + 0.004*"Borough" + 0.004*"plans"
-2024-10-07 09:00:01,614 - topic #1 (0.333): 0.016*"’" + 0.010*"Greenwich" + 0.007*"plans" + 0.006*"well" + 0.005*"needs" + 0.004*"3" + 0.004*"provide" + 0.004*"Borough" + 0.004*"Royal" + 0.004*"progress"
-2024-10-07 09:00:01,614 - topic #2 (0.333): 0.019*"’" + 0.010*"Greenwich" + 0.007*"needs" + 0.007*"plans" + 0.006*"provide" + 0.006*"well" + 0.005*"2024" + 0.005*"progress" + 0.005*"7" + 0.004*"3"
-2024-10-07 09:00:01,614 - topic diff=0.757385, rho=1.000000
-2024-10-07 09:00:01,614 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:00:01.614916', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:02,610 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:00:02,610 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:02,610 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:00:02,610 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:02,611 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:00:02,611 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:02,611 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:00:02,611 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:02,611 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:00:02,611 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:02,612 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:00:02,612 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:16,689 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:00:16,691 - built Dictionary<1222 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2748 corpus positions)
-2024-10-07 09:00:16,692 - Dictionary lifecycle event {'msg': 'built Dictionary<1222 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2748 corpus positions)', 'datetime': '2024-10-07T09:00:16.692130', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:16,693 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:00:16,693 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:00:16,693 - using serial LDA version on this node
-2024-10-07 09:00:16,694 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:00:16,694 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:00:16,698 - -8.103 per-word bound, 274.9 perplexity estimate based on a held-out corpus of 1 documents with 2748 words
-2024-10-07 09:00:16,698 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:00:16,699 - topic #0 (0.333): 0.014*"’" + 0.006*"Hackney" + 0.006*"needs" + 0.005*"July" + 0.005*"well" + 0.004*"need" + 0.004*"12" + 0.004*"carers" + 0.004*"progress" + 0.004*"1"
-2024-10-07 09:00:16,699 - topic #1 (0.333): 0.013*"’" + 0.009*"Hackney" + 0.006*"needs" + 0.005*"practice" + 0.005*"need" + 0.005*"effective" + 0.004*"carers" + 0.004*"12" + 0.004*"well" + 0.004*"understand"
-2024-10-07 09:00:16,700 - topic #2 (0.333): 0.022*"’" + 0.011*"Hackney" + 0.010*"needs" + 0.006*"carers" + 0.006*"well" + 0.005*"12" + 0.005*"oversight" + 0.004*"timely" + 0.004*"need" + 0.004*"education"
-2024-10-07 09:00:16,700 - topic diff=0.815237, rho=1.000000
-2024-10-07 09:00:16,700 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1222, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:00:16.700405', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:17,786 - Inspection date 2024-07-01 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:00:17,786 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:17,787 - Inspection date 2024-07-01 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:00:17,787 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:17,787 - Inspection date 2024-07-01 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:00:17,787 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:17,787 - Inspection date 2024-07-01 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:00:17,787 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:17,787 - Inspection date 2024-07-01 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:00:17,788 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:17,788 - Inspection date 2024-07-01 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:00:17,788 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:32,538 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:00:32,541 - built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
-2024-10-07 09:00:32,542 - Dictionary lifecycle event {'msg': "built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-10-07T09:00:32.542017', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:32,543 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:00:32,543 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:00:32,543 - using serial LDA version on this node
-2024-10-07 09:00:32,544 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:00:32,544 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:00:32,548 - -8.208 per-word bound, 295.6 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
-2024-10-07 09:00:32,548 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:00:32,550 - topic #0 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"receive" + 0.005*"Hammersmith" + 0.004*"Leaders" + 0.004*"leaders" + 0.004*"plans" + 0.004*"Fulham" + 0.004*"timely"
-2024-10-07 09:00:32,550 - topic #1 (0.333): 0.017*"’" + 0.008*"well" + 0.006*"receive" + 0.005*"Fulham" + 0.005*"plans" + 0.005*"Hammersmith" + 0.004*"leaders" + 0.004*"protection" + 0.004*"11" + 0.004*"effective"
-2024-10-07 09:00:32,550 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"receive" + 0.005*"2024" + 0.004*"effective" + 0.004*"Leaders" + 0.004*"supported" + 0.004*"11" + 0.004*"plans"
-2024-10-07 09:00:32,550 - topic diff=0.797748, rho=1.000000
-2024-10-07 09:00:32,550 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1330, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:00:32.550969', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:33,491 - Inspection date 2024-03-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:00:33,491 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:33,491 - Inspection date 2024-03-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:00:33,491 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:33,491 - Inspection date 2024-03-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:00:33,492 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:33,492 - Inspection date 2024-03-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:00:33,492 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:33,492 - Inspection date 2024-03-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:00:33,492 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:33,492 - Inspection date 2024-03-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:00:33,493 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:46,869 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:00:46,872 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)
-2024-10-07 09:00:46,872 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-10-07T09:00:46.872604', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:46,873 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:00:46,873 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:00:46,874 - using serial LDA version on this node
-2024-10-07 09:00:46,874 - 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
-2024-10-07 09:00:46,874 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:00:46,878 - -8.169 per-word bound, 287.8 perplexity estimate based on a held-out corpus of 1 documents with 2620 words
-2024-10-07 09:00:46,878 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:00:46,880 - topic #0 (0.333): 0.011*"’" + 0.007*"Haringey" + 0.006*"needs" + 0.006*"plans" + 0.006*"progress" + 0.006*"well" + 0.005*"good" + 0.004*"education" + 0.004*"need" + 0.004*"carers"
-2024-10-07 09:00:46,880 - topic #1 (0.333): 0.016*"’" + 0.009*"Haringey" + 0.008*"needs" + 0.007*"plans" + 0.006*"well" + 0.006*"need" + 0.005*"good" + 0.005*"risk" + 0.005*"education" + 0.004*"progress"
-2024-10-07 09:00:46,880 - topic #2 (0.333): 0.019*"’" + 0.008*"Haringey" + 0.007*"needs" + 0.007*"plans" + 0.005*"well" + 0.005*"good" + 0.005*"need" + 0.005*"24" + 0.004*"risk" + 0.004*"progress"
-2024-10-07 09:00:46,880 - topic diff=0.770820, rho=1.000000
-2024-10-07 09:00:46,880 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1252, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:00:46.880866', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:47,788 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:00:47,789 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:47,789 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:00:47,789 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:47,789 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:00:47,789 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:47,790 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:00:47,790 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:47,790 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:00:47,790 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:47,790 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:00:47,790 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:56,634 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:00:56,636 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)
-2024-10-07 09:00:56,636 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-10-07T09:00:56.636738', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:56,637 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:00:56,637 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:00:56,637 - using serial LDA version on this node
-2024-10-07 09:00:56,638 - 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
-2024-10-07 09:00:56,638 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:00:56,641 - -7.971 per-word bound, 250.8 perplexity estimate based on a held-out corpus of 1 documents with 1732 words
-2024-10-07 09:00:56,641 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:00:56,643 - topic #0 (0.333): 0.012*"’" + 0.011*"good" + 0.009*"needs" + 0.009*"well" + 0.006*"protection" + 0.006*"impact" + 0.006*"plans" + 0.005*"need" + 0.005*"school" + 0.005*"practice"
-2024-10-07 09:00:56,643 - topic #1 (0.333): 0.011*"’" + 0.011*"good" + 0.008*"well" + 0.008*"needs" + 0.006*"practice" + 0.005*"impact" + 0.005*"plans" + 0.005*"need" + 0.005*"experiences" + 0.005*"early"
-2024-10-07 09:00:56,643 - topic #2 (0.333): 0.011*"’" + 0.009*"good" + 0.008*"well" + 0.006*"needs" + 0.005*"protection" + 0.005*"plans" + 0.005*"impact" + 0.004*"experiences" + 0.004*"early" + 0.004*"need"
-2024-10-07 09:00:56,643 - topic diff=0.691362, rho=1.000000
-2024-10-07 09:00:56,643 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=942, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:00:56.643583', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:00:58,456 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:00:58,457 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:58,457 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:00:58,457 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:58,457 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:00:58,457 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:58,458 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:00:58,458 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:58,458 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:00:58,458 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:00:58,458 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:00:58,458 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:09,931 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:01:09,933 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)
-2024-10-07 09:01:09,934 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-10-07T09:01:09.934089', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:09,935 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:01:09,935 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:01:09,935 - using serial LDA version on this node
-2024-10-07 09:01:09,935 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:01:09,935 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:01:09,939 - -8.013 per-word bound, 258.3 perplexity estimate based on a held-out corpus of 1 documents with 2243 words
-2024-10-07 09:01:09,939 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:01:09,941 - topic #0 (0.333): 0.019*"’" + 0.012*"Havering" + 0.010*"quality" + 0.007*"plans" + 0.007*"oversight" + 0.006*"effective" + 0.006*"needs" + 0.005*"December" + 0.004*"2023" + 0.004*"11"
-2024-10-07 09:01:09,941 - topic #1 (0.333): 0.018*"’" + 0.010*"Havering" + 0.007*"plans" + 0.006*"quality" + 0.004*"oversight" + 0.004*"practice" + 0.004*"effective" + 0.003*"11" + 0.003*"22" + 0.003*"experiences"
-2024-10-07 09:01:09,941 - topic #2 (0.333): 0.015*"’" + 0.011*"Havering" + 0.008*"quality" + 0.007*"plans" + 0.005*"effective" + 0.005*"11" + 0.004*"well" + 0.004*"22" + 0.004*"practice" + 0.004*"needs"
-2024-10-07 09:01:09,941 - topic diff=0.777945, rho=1.000000
-2024-10-07 09:01:09,941 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:01:09.941764', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:11,083 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:01:11,084 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:11,084 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:01:11,084 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:11,084 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:01:11,084 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:11,085 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:01:11,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:11,085 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:01:11,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:11,085 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:01:11,085 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:22,547 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:01:22,549 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)
-2024-10-07 09:01:22,550 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-10-07T09:01:22.549993', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:22,551 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:01:22,551 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:01:22,551 - using serial LDA version on this node
-2024-10-07 09:01:22,551 - 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
-2024-10-07 09:01:22,552 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:01:22,555 - -8.074 per-word bound, 269.5 perplexity estimate based on a held-out corpus of 1 documents with 2511 words
-2024-10-07 09:01:22,555 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:01:22,557 - topic #0 (0.333): 0.012*"’" + 0.007*"Hillingdon" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.005*"team" + 0.005*"2" + 0.004*"leaders" + 0.004*"need" + 0.004*"health"
-2024-10-07 09:01:22,557 - topic #1 (0.333): 0.020*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"Hillingdon" + 0.007*"well" + 0.005*"6" + 0.005*"need" + 0.004*"PAs" + 0.004*"receive" + 0.004*"good"
-2024-10-07 09:01:22,557 - topic #2 (0.333): 0.020*"’" + 0.011*"needs" + 0.009*"plans" + 0.008*"Hillingdon" + 0.008*"well" + 0.005*"team" + 0.005*"2" + 0.004*"need" + 0.004*"leaders" + 0.004*"2023"
-2024-10-07 09:01:22,557 - topic diff=0.790635, rho=1.000000
-2024-10-07 09:01:22,558 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:01:22.558085', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:23,541 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:01:23,541 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:23,542 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:01:23,542 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:23,542 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:01:23,542 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:23,542 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:01:23,542 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:23,542 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:01:23,543 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:23,543 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:01:23,543 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:35,653 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:01:35,655 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)
-2024-10-07 09:01:35,655 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-10-07T09:01:35.655395', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:35,656 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:01:35,656 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:01:35,656 - using serial LDA version on this node
-2024-10-07 09:01:35,657 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:01:35,657 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:01:35,660 - -8.003 per-word bound, 256.5 perplexity estimate based on a held-out corpus of 1 documents with 2271 words
-2024-10-07 09:01:35,660 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:01:35,662 - topic #0 (0.333): 0.022*"’" + 0.011*"needs" + 0.010*"well" + 0.008*"effective" + 0.008*"timely" + 0.007*"Hounslow" + 0.006*"plans" + 0.005*"training" + 0.005*"experiences" + 0.005*"oversight"
-2024-10-07 09:01:35,662 - topic #1 (0.333): 0.017*"’" + 0.012*"needs" + 0.010*"well" + 0.009*"effective" + 0.008*"Hounslow" + 0.005*"timely" + 0.005*"16" + 0.004*"progress" + 0.004*"education" + 0.004*"oversight"
-2024-10-07 09:01:35,662 - topic #2 (0.333): 0.020*"’" + 0.010*"needs" + 0.009*"well" + 0.006*"plans" + 0.005*"Hounslow" + 0.005*"timely" + 0.005*"effective" + 0.005*"20" + 0.005*"strong" + 0.004*"ensure"
-2024-10-07 09:01:35,662 - topic diff=0.780990, rho=1.000000
-2024-10-07 09:01:35,662 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1070, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:01:35.662773', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:36,683 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:01:36,684 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:36,684 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:01:36,684 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:36,684 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:01:36,685 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:36,685 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:01:36,685 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:36,685 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:01:36,685 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:36,686 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:01:36,686 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:45,605 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:01:45,607 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)
-2024-10-07 09:01:45,607 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-10-07T09:01:45.607363', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:45,608 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:01:45,608 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:01:45,608 - using serial LDA version on this node
-2024-10-07 09:01:45,609 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:01:45,609 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:01:45,612 - -7.929 per-word bound, 243.7 perplexity estimate based on a held-out corpus of 1 documents with 1982 words
-2024-10-07 09:01:45,612 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:01:45,613 - topic #0 (0.333): 0.012*"’" + 0.011*"needs" + 0.009*"well" + 0.007*"plans" + 0.005*"highly" + 0.005*"risk" + 0.005*"leaders" + 0.004*"Islington" + 0.004*"practice" + 0.004*"good"
-2024-10-07 09:01:45,614 - topic #1 (0.333): 0.013*"’" + 0.013*"well" + 0.012*"needs" + 0.007*"plans" + 0.007*"good" + 0.007*"highly" + 0.007*"quality" + 0.006*"leaders" + 0.005*"effective" + 0.005*"Islington"
-2024-10-07 09:01:45,614 - topic #2 (0.333): 0.012*"’" + 0.010*"needs" + 0.008*"well" + 0.006*"good" + 0.006*"effective" + 0.006*"plans" + 0.005*"quality" + 0.005*"highly" + 0.005*"Islington" + 0.005*"leaders"
-2024-10-07 09:01:45,614 - topic diff=0.741402, rho=1.000000
-2024-10-07 09:01:45,614 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:01:45.614472', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:47,740 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:01:47,740 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:47,740 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:01:47,740 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:47,741 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:01:47,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:47,741 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:01:47,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:47,741 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:01:47,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:47,741 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:01:47,742 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:01:59,165 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:01:59,167 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)
-2024-10-07 09:01:59,167 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-10-07T09:01:59.167675', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:01:59,168 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:01:59,168 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:01:59,168 - using serial LDA version on this node
-2024-10-07 09:01:59,169 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:01:59,169 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:01:59,172 - -7.904 per-word bound, 239.4 perplexity estimate based on a held-out corpus of 1 documents with 2090 words
-2024-10-07 09:01:59,172 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:01:59,174 - topic #0 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"plans" + 0.007*"need" + 0.007*"Lambeth" + 0.007*"leaders" + 0.006*"progress" + 0.006*"good" + 0.006*"impact"
-2024-10-07 09:01:59,174 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"plans" + 0.007*"needs" + 0.007*"good" + 0.006*"progress" + 0.006*"Lambeth" + 0.005*"impact" + 0.005*"need" + 0.005*"leaders"
-2024-10-07 09:01:59,174 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.009*"well" + 0.007*"good" + 0.006*"plans" + 0.006*"Lambeth" + 0.005*"arrangements" + 0.005*"4" + 0.005*"2022" + 0.005*"impact"
-2024-10-07 09:01:59,174 - topic diff=0.797040, rho=1.000000
-2024-10-07 09:01:59,174 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:01:59.174784', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:00,188 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:02:00,189 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:00,189 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:02:00,189 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:00,189 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:02:00,189 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:00,189 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:02:00,190 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:00,190 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:02:00,190 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:00,190 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:02:00,190 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:12,189 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:02:12,192 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)
-2024-10-07 09:02:12,192 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-10-07T09:02:12.192221', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:12,193 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:02:12,193 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:02:12,193 - using serial LDA version on this node
-2024-10-07 09:02:12,194 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:02:12,194 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:02:12,197 - -8.046 per-word bound, 264.2 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
-2024-10-07 09:02:12,197 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:02:12,199 - topic #0 (0.333): 0.018*"’" + 0.009*"well" + 0.007*"needs" + 0.007*"plans" + 0.005*"effective" + 0.005*"Lewisham" + 0.005*"good" + 0.005*"progress" + 0.005*"4" + 0.005*"need"
-2024-10-07 09:02:12,199 - topic #1 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"effective" + 0.007*"plans" + 0.006*"needs" + 0.005*"Lewisham" + 0.004*"progress" + 0.004*"benefit" + 0.004*"good" + 0.004*"4"
-2024-10-07 09:02:12,199 - topic #2 (0.333): 0.019*"’" + 0.008*"needs" + 0.008*"well" + 0.007*"plans" + 0.007*"Lewisham" + 0.006*"effective" + 0.005*"progress" + 0.005*"4" + 0.005*"good" + 0.005*"leaders"
-2024-10-07 09:02:12,199 - topic diff=0.768726, rho=1.000000
-2024-10-07 09:02:12,199 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:02:12.199833', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:13,100 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:02:13,100 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:13,100 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:02:13,100 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:13,101 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:02:13,101 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:13,101 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:02:13,101 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:13,101 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:02:13,101 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:13,101 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:02:13,102 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:22,884 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:02:22,886 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)
-2024-10-07 09:02:22,886 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-10-07T09:02:22.886202', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:22,887 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:02:22,887 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:02:22,887 - using serial LDA version on this node
-2024-10-07 09:02:22,887 - 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
-2024-10-07 09:02:22,887 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:02:22,891 - -7.991 per-word bound, 254.3 perplexity estimate based on a held-out corpus of 1 documents with 2032 words
-2024-10-07 09:02:22,891 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:02:22,892 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.006*"Merton" + 0.006*"needs" + 0.005*"4" + 0.005*"good" + 0.005*"progress" + 0.004*"information" + 0.004*"plans" + 0.004*"family"
-2024-10-07 09:02:22,892 - topic #1 (0.333): 0.015*"’" + 0.009*"well" + 0.006*"Merton" + 0.005*"plans" + 0.005*"family" + 0.005*"needs" + 0.004*"2022" + 0.004*"early" + 0.004*"progress" + 0.004*"ensure"
-2024-10-07 09:02:22,893 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"Merton" + 0.006*"needs" + 0.005*"plans" + 0.004*"leaders" + 0.004*"ensure" + 0.004*"progress" + 0.004*"good" + 0.004*"health"
-2024-10-07 09:02:22,893 - topic diff=0.754536, rho=1.000000
-2024-10-07 09:02:22,893 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1015, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:02:22.893257', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:23,715 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:02:23,715 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:23,715 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:02:23,716 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:23,716 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:02:23,716 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:23,716 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:02:23,716 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:23,716 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:02:23,716 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:23,717 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:02:23,717 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:35,530 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:02:35,532 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)
-2024-10-07 09:02:35,532 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-10-07T09:02:35.532692', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:35,533 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:02:35,533 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:02:35,534 - using serial LDA version on this node
-2024-10-07 09:02:35,534 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:02:35,534 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:02:35,538 - -8.057 per-word bound, 266.3 perplexity estimate based on a held-out corpus of 1 documents with 2540 words
-2024-10-07 09:02:35,538 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:02:35,539 - topic #0 (0.333): 0.014*"’" + 0.006*"needs" + 0.006*"effective" + 0.006*"Newham" + 0.005*"practice" + 0.005*"progress" + 0.004*"need" + 0.004*"plans" + 0.004*"good" + 0.004*"18"
-2024-10-07 09:02:35,539 - topic #1 (0.333): 0.021*"’" + 0.009*"Newham" + 0.008*"needs" + 0.006*"progress" + 0.006*"practice" + 0.006*"plans" + 0.006*"need" + 0.005*"good" + 0.005*"effective" + 0.005*"Leaders"
-2024-10-07 09:02:35,540 - topic #2 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"plans" + 0.007*"need" + 0.007*"progress" + 0.006*"practice" + 0.006*"effective" + 0.005*"Newham" + 0.005*"good" + 0.005*"receive"
-2024-10-07 09:02:35,540 - topic diff=0.783692, rho=1.000000
-2024-10-07 09:02:35,540 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1153, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:02:35.540316', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:36,421 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:02:36,422 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:36,422 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:02:36,422 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:36,422 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:02:36,422 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:36,423 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:02:36,423 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:36,423 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:02:36,423 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:36,423 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:02:36,423 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:47,446 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:02:47,450 - built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)
-2024-10-07 09:02:47,450 - Dictionary lifecycle event {'msg': "built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-10-07T09:02:47.450347', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:47,452 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:02:47,452 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:02:47,452 - using serial LDA version on this node
-2024-10-07 09:02:47,453 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:02:47,453 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:02:47,460 - -8.164 per-word bound, 286.8 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
-2024-10-07 09:02:47,460 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:02:47,463 - topic #0 (0.333): 0.013*"’" + 0.007*"Redbridge" + 0.006*"supported" + 0.005*"carers" + 0.005*"practice" + 0.005*"needs" + 0.004*"10" + 0.004*"effective" + 0.004*"leaders" + 0.004*"14"
-2024-10-07 09:02:47,463 - topic #1 (0.333): 0.013*"’" + 0.008*"Redbridge" + 0.006*"family" + 0.005*"needs" + 0.005*"early" + 0.005*"leaders" + 0.004*"risk" + 0.004*"practice" + 0.004*"10" + 0.004*"carers"
-2024-10-07 09:02:47,463 - topic #2 (0.333): 0.017*"’" + 0.006*"Redbridge" + 0.005*"practice" + 0.005*"needs" + 0.005*"carers" + 0.004*"supported" + 0.004*"leaders" + 0.004*"family" + 0.004*"14" + 0.004*"early"
-2024-10-07 09:02:47,463 - topic diff=0.748891, rho=1.000000
-2024-10-07 09:02:47,463 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1204, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:02:47.463901', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:48,423 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:02:48,423 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:48,424 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:02:48,424 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:48,424 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:02:48,424 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:48,424 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:02:48,424 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:48,425 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:02:48,425 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:48,425 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:02:48,425 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:57,131 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:02:57,133 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)
-2024-10-07 09:02:57,133 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-10-07T09:02:57.133409', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:57,134 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:02:57,134 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:02:57,134 - using serial LDA version on this node
-2024-10-07 09:02:57,135 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:02:57,135 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:02:57,138 - -7.985 per-word bound, 253.4 perplexity estimate based on a held-out corpus of 1 documents with 1818 words
-2024-10-07 09:02:57,138 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:02:57,139 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.008*"Richmond" + 0.006*"needs" + 0.006*"supported" + 0.005*"need" + 0.005*"team" + 0.005*"good" + 0.005*"strong" + 0.005*"31"
-2024-10-07 09:02:57,140 - topic #1 (0.333): 0.018*"’" + 0.013*"well" + 0.010*"Richmond" + 0.009*"needs" + 0.006*"team" + 0.006*"need" + 0.006*"good" + 0.006*"additional" + 0.006*"supported" + 0.005*"ensure"
-2024-10-07 09:02:57,140 - topic #2 (0.333): 0.013*"’" + 0.010*"well" + 0.006*"needs" + 0.006*"supported" + 0.005*"4" + 0.005*"good" + 0.005*"Richmond" + 0.004*"team" + 0.004*"Thames" + 0.004*"need"
-2024-10-07 09:02:57,140 - topic diff=0.738729, rho=1.000000
-2024-10-07 09:02:57,140 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:02:57.140600', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:02:58,118 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:02:58,118 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:58,119 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:02:58,119 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:58,119 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:02:58,119 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:58,119 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:02:58,119 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:58,120 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:02:58,120 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:02:58,120 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:02:58,120 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:08,004 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:03:08,006 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)
-2024-10-07 09:03:08,006 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-10-07T09:03:08.006657', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:08,007 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:03:08,007 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:03:08,007 - using serial LDA version on this node
-2024-10-07 09:03:08,008 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:03:08,008 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:03:08,011 - -7.923 per-word bound, 242.8 perplexity estimate based on a held-out corpus of 1 documents with 1878 words
-2024-10-07 09:03:08,011 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:03:08,013 - topic #0 (0.333): 0.014*"’" + 0.010*"Southwark" + 0.008*"good" + 0.007*"well" + 0.007*"strong" + 0.006*"needs" + 0.006*"effective" + 0.005*"progress" + 0.005*"leaders" + 0.005*"plans"
-2024-10-07 09:03:08,013 - topic #1 (0.333): 0.016*"’" + 0.008*"good" + 0.007*"Southwark" + 0.006*"well" + 0.006*"needs" + 0.006*"plans" + 0.006*"progress" + 0.005*"need" + 0.005*"strong" + 0.005*"Leaders"
-2024-10-07 09:03:08,013 - topic #2 (0.333): 0.022*"’" + 0.010*"Southwark" + 0.008*"well" + 0.008*"needs" + 0.007*"good" + 0.006*"receive" + 0.006*"need" + 0.006*"progress" + 0.006*"Leaders" + 0.005*"plans"
-2024-10-07 09:03:08,013 - topic diff=0.739257, rho=1.000000
-2024-10-07 09:03:08,013 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=945, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:03:08.013737', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:08,878 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:03:08,879 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:08,879 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:03:08,879 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:08,879 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:03:08,880 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:08,880 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:03:08,880 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:08,880 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:03:08,880 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:08,880 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:03:08,881 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:17,620 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:03:17,622 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)
-2024-10-07 09:03:17,622 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-10-07T09:03:17.622860', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:17,623 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:03:17,623 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:03:17,624 - using serial LDA version on this node
-2024-10-07 09:03:17,624 - 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
-2024-10-07 09:03:17,624 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:03:17,627 - -7.985 per-word bound, 253.4 perplexity estimate based on a held-out corpus of 1 documents with 1847 words
-2024-10-07 09:03:17,627 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:03:17,629 - topic #0 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"Sutton" + 0.005*"effective" + 0.005*"good" + 0.004*"6" + 0.004*"needs" + 0.004*"progress" + 0.004*"December" + 0.004*"protection"
-2024-10-07 09:03:17,629 - topic #1 (0.333): 0.019*"’" + 0.007*"needs" + 0.006*"progress" + 0.006*"well" + 0.006*"Sutton" + 0.005*"effective" + 0.005*"receive" + 0.005*"6" + 0.004*"need" + 0.004*"good"
-2024-10-07 09:03:17,629 - topic #2 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"receive" + 0.005*"Sutton" + 0.005*"good" + 0.005*"supported" + 0.005*"progress" + 0.004*"need" + 0.004*"leaders"
-2024-10-07 09:03:17,629 - topic diff=0.724635, rho=1.000000
-2024-10-07 09:03:17,629 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:03:17.629948', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:19,417 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:03:19,417 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:19,418 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:03:19,418 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:19,418 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:03:19,418 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:19,418 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:03:19,418 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:19,419 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:03:19,419 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:19,419 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:03:19,419 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:30,206 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:03:30,209 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)
-2024-10-07 09:03:30,209 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-10-07T09:03:30.209308', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:30,210 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:03:30,210 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:03:30,210 - using serial LDA version on this node
-2024-10-07 09:03:30,211 - 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
-2024-10-07 09:03:30,211 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:03:30,215 - -8.132 per-word bound, 280.6 perplexity estimate based on a held-out corpus of 1 documents with 2465 words
-2024-10-07 09:03:30,215 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:03:30,216 - topic #0 (0.333): 0.014*"’" + 0.007*"effective" + 0.006*"practice" + 0.006*"good" + 0.006*"progress" + 0.005*"plans" + 0.005*"‘" + 0.005*"well" + 0.004*"need" + 0.004*"carers"
-2024-10-07 09:03:30,216 - topic #1 (0.333): 0.014*"’" + 0.007*"effective" + 0.006*"good" + 0.006*"‘" + 0.005*"plans" + 0.005*"well" + 0.004*"early" + 0.004*"progress" + 0.004*"practice" + 0.004*"needs"
-2024-10-07 09:03:30,217 - topic #2 (0.333): 0.016*"’" + 0.007*"good" + 0.007*"plans" + 0.006*"need" + 0.006*"well" + 0.006*"risk" + 0.005*"early" + 0.005*"‘" + 0.005*"practice" + 0.005*"including"
-2024-10-07 09:03:30,217 - topic diff=0.769348, rho=1.000000
-2024-10-07 09:03:30,217 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1194, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:03:30.217251', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:31,164 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:03:31,164 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:31,165 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:03:31,165 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:31,165 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:03:31,165 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:31,166 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:03:31,166 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:31,166 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:03:31,166 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:31,166 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:03:31,166 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:42,985 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:03:42,987 - built Dictionary<1061 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2398 corpus positions)
-2024-10-07 09:03:42,987 - Dictionary lifecycle event {'msg': "built Dictionary<1061 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2398 corpus positions)", 'datetime': '2024-10-07T09:03:42.987614', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:42,988 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:03:42,988 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:03:42,989 - using serial LDA version on this node
-2024-10-07 09:03:42,989 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:03:42,989 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:03:42,993 - -7.955 per-word bound, 248.2 perplexity estimate based on a held-out corpus of 1 documents with 2398 words
-2024-10-07 09:03:42,993 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:03:42,994 - topic #0 (0.333): 0.020*"’" + 0.012*"needs" + 0.008*"well" + 0.008*"plans" + 0.006*"Forest" + 0.006*"Waltham" + 0.005*"progress" + 0.005*"leaders" + 0.004*"2024" + 0.004*"know"
-2024-10-07 09:03:42,994 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"plans" + 0.006*"progress" + 0.005*"Waltham" + 0.004*"12" + 0.004*"leaders" + 0.004*"Leaders" + 0.004*"Forest"
-2024-10-07 09:03:42,994 - topic #2 (0.333): 0.017*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"Waltham" + 0.006*"Forest" + 0.005*"plans" + 0.005*"Leaders" + 0.005*"leaders" + 0.005*"8" + 0.004*"12"
-2024-10-07 09:03:42,995 - topic diff=0.783410, rho=1.000000
-2024-10-07 09:03:42,995 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1061, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:03:42.995140', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:44,172 - Inspection date 2024-07-08 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:03:44,173 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:44,173 - Inspection date 2024-07-08 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:03:44,173 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:44,173 - Inspection date 2024-07-08 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:03:44,173 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:44,174 - Inspection date 2024-07-08 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:03:44,174 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:44,174 - Inspection date 2024-07-08 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:03:44,174 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:44,175 - Inspection date 2024-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:03:44,175 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:52,695 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:03:52,697 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)
-2024-10-07 09:03:52,697 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-10-07T09:03:52.697364', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:52,698 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:03:52,698 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:03:52,698 - using serial LDA version on this node
-2024-10-07 09:03:52,698 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:03:52,699 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:03:52,702 - -7.852 per-word bound, 231.0 perplexity estimate based on a held-out corpus of 1 documents with 1772 words
-2024-10-07 09:03:52,702 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:03:52,703 - topic #0 (0.333): 0.011*"’" + 0.007*"well" + 0.006*"protection" + 0.005*"practice" + 0.005*"progress" + 0.005*"Wandsworth" + 0.005*"needs" + 0.005*"7" + 0.005*"However" + 0.005*"Senior"
-2024-10-07 09:03:52,703 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"Wandsworth" + 0.005*"protection" + 0.005*"Senior" + 0.005*"team" + 0.005*"supported" + 0.005*"progress" + 0.005*"practice"
-2024-10-07 09:03:52,703 - topic #2 (0.333): 0.011*"’" + 0.006*"progress" + 0.006*"quality" + 0.006*"well" + 0.005*"needs" + 0.005*"effective" + 0.005*"ensure" + 0.005*"Senior" + 0.005*"practice" + 0.004*"timely"
-2024-10-07 09:03:52,703 - topic diff=0.743712, rho=1.000000
-2024-10-07 09:03:52,704 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=884, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:03:52.704036', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:03:53,555 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:03:53,555 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:53,555 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:03:53,555 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:53,555 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:03:53,555 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:53,556 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:03:53,556 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:53,556 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:03:53,556 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:03:53,556 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:03:53,556 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:02,702 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:04:02,705 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)
-2024-10-07 09:04:02,705 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-10-07T09:04:02.705915', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:02,707 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:04:02,707 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:04:02,708 - using serial LDA version on this node
-2024-10-07 09:04:02,708 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:04:02,708 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:04:02,714 - -8.151 per-word bound, 284.3 perplexity estimate based on a held-out corpus of 1 documents with 2101 words
-2024-10-07 09:04:02,715 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:04:02,717 - topic #0 (0.333): 0.012*"’" + 0.006*"practice" + 0.005*"highly" + 0.005*"needs" + 0.005*"across" + 0.004*"well" + 0.004*"family" + 0.003*"many" + 0.003*"Westminster" + 0.003*"quality"
-2024-10-07 09:04:02,717 - topic #1 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"practice" + 0.006*"highly" + 0.005*"well" + 0.004*"direct" + 0.004*"plans" + 0.003*"shared" + 0.003*"many" + 0.003*"experiences"
-2024-10-07 09:04:02,717 - topic #2 (0.333): 0.013*"’" + 0.007*"practice" + 0.006*"highly" + 0.006*"needs" + 0.005*"well" + 0.004*"many" + 0.004*"high" + 0.004*"family" + 0.003*"skilled" + 0.003*"across"
-2024-10-07 09:04:02,717 - topic diff=0.688628, rho=1.000000
-2024-10-07 09:04:02,718 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1136, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:04:02.718121', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:03,875 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:04:03,876 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:03,876 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:04:03,876 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:03,876 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:04:03,876 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:03,877 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:04:03,877 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:03,877 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:04:03,877 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:03,877 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:04:03,877 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:16,138 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:04:16,142 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)
-2024-10-07 09:04:16,142 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-10-07T09:04:16.142211', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:16,143 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:04:16,143 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:04:16,143 - using serial LDA version on this node
-2024-10-07 09:04:16,144 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:04:16,144 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:04:16,148 - -8.107 per-word bound, 275.6 perplexity estimate based on a held-out corpus of 1 documents with 2593 words
-2024-10-07 09:04:16,148 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:04:16,149 - topic #0 (0.333): 0.017*"’" + 0.006*"need" + 0.006*"good" + 0.006*"needs" + 0.005*"ensure" + 0.005*"effective" + 0.005*"plans" + 0.005*"Luton" + 0.005*"impact" + 0.004*"progress"
-2024-10-07 09:04:16,149 - topic #1 (0.333): 0.011*"’" + 0.006*"Luton" + 0.006*"plans" + 0.005*"need" + 0.004*"needs" + 0.004*"effective" + 0.004*"ensure" + 0.004*"22" + 0.004*"2022" + 0.004*"good"
-2024-10-07 09:04:16,150 - topic #2 (0.333): 0.021*"’" + 0.008*"needs" + 0.007*"need" + 0.006*"plans" + 0.006*"effective" + 0.006*"progress" + 0.006*"impact" + 0.005*"Luton" + 0.005*"quality" + 0.005*"good"
-2024-10-07 09:04:16,150 - topic diff=0.794024, rho=1.000000
-2024-10-07 09:04:16,150 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1199, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:04:16.150332', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:17,178 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:04:17,178 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:17,179 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:04:17,179 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:17,179 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:04:17,179 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:17,179 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:04:17,179 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:17,179 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:04:17,180 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:17,180 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:04:17,180 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:26,097 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:04:26,098 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)
-2024-10-07 09:04:26,099 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-10-07T09:04:26.098998', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:26,099 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:04:26,099 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:04:26,100 - using serial LDA version on this node
-2024-10-07 09:04:26,100 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:04:26,100 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:04:26,103 - -7.769 per-word bound, 218.1 perplexity estimate based on a held-out corpus of 1 documents with 1938 words
-2024-10-07 09:04:26,103 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:04:26,104 - topic #0 (0.333): 0.018*"’" + 0.011*"needs" + 0.010*"Manchester" + 0.006*"always" + 0.006*"supported" + 0.006*"well" + 0.005*"disabled" + 0.005*"progress" + 0.005*"effective" + 0.005*"1"
-2024-10-07 09:04:26,105 - topic #1 (0.333): 0.026*"’" + 0.012*"Manchester" + 0.010*"needs" + 0.008*"well" + 0.008*"supported" + 0.007*"always" + 0.006*"quality" + 0.005*"plans" + 0.005*"protection" + 0.005*"family"
-2024-10-07 09:04:26,105 - topic #2 (0.333): 0.017*"’" + 0.009*"Manchester" + 0.007*"well" + 0.006*"needs" + 0.006*"always" + 0.006*"effective" + 0.006*"plans" + 0.005*"protection" + 0.005*"education" + 0.005*"supported"
-2024-10-07 09:04:26,105 - topic diff=0.811393, rho=1.000000
-2024-10-07 09:04:26,105 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=871, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-07T09:04:26.105435', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:27,035 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:04:27,035 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:27,035 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:04:27,036 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:27,036 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:04:27,036 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:27,036 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:04:27,036 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:27,037 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:04:27,037 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:27,037 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:04:27,037 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:36,806 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:04:36,808 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)
-2024-10-07 09:04:36,808 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-10-07T09:04:36.808896', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:36,809 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:04:36,810 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:04:36,810 - using serial LDA version on this node
-2024-10-07 09:04:36,810 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:04:36,810 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:04:36,814 - -7.889 per-word bound, 237.0 perplexity estimate based on a held-out corpus of 1 documents with 1857 words
-2024-10-07 09:04:36,814 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:04:36,815 - topic #0 (0.333): 0.016*"’" + 0.009*"Medway" + 0.008*"quality" + 0.008*"practice" + 0.007*"leaders" + 0.007*"well" + 0.006*"needs" + 0.005*"progress" + 0.005*"oversight" + 0.005*"impact"
-2024-10-07 09:04:36,815 - topic #1 (0.333): 0.015*"’" + 0.010*"well" + 0.009*"Medway" + 0.008*"quality" + 0.007*"practice" + 0.007*"experiences" + 0.006*"oversight" + 0.005*"17" + 0.005*"impact" + 0.005*"needs"
-2024-10-07 09:04:36,815 - topic #2 (0.333): 0.016*"’" + 0.009*"Medway" + 0.009*"practice" + 0.007*"quality" + 0.007*"needs" + 0.006*"leaders" + 0.006*"oversight" + 0.006*"well" + 0.006*"impact" + 0.006*"clear"
-2024-10-07 09:04:36,815 - topic diff=0.759378, rho=1.000000
-2024-10-07 09:04:36,816 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=922, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:04:36.816043', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:37,746 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:04:37,746 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:37,746 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:04:37,746 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:37,746 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:04:37,746 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:37,747 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:04:37,747 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:37,747 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:04:37,747 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:37,747 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:04:37,747 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:49,851 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:04:49,855 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)
-2024-10-07 09:04:49,855 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-10-07T09:04:49.855423', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:49,857 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:04:49,857 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:04:49,857 - using serial LDA version on this node
-2024-10-07 09:04:49,858 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:04:49,858 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:04:49,865 - -8.000 per-word bound, 256.0 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
-2024-10-07 09:04:49,865 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:04:49,867 - topic #0 (0.333): 0.016*"’" + 0.008*"plans" + 0.008*"effective" + 0.007*"Middlesbrough" + 0.007*"needs" + 0.006*"well" + 0.006*"24" + 0.006*"practice" + 0.006*"progress" + 0.005*"13"
-2024-10-07 09:04:49,867 - topic #1 (0.333): 0.012*"’" + 0.007*"Middlesbrough" + 0.006*"plans" + 0.006*"well" + 0.006*"effective" + 0.006*"practice" + 0.006*"needs" + 0.005*"place" + 0.005*"progress" + 0.005*"2023"
-2024-10-07 09:04:49,868 - topic #2 (0.333): 0.012*"’" + 0.006*"effective" + 0.006*"well" + 0.006*"Middlesbrough" + 0.005*"plans" + 0.005*"needs" + 0.004*"practice" + 0.004*"24" + 0.004*"progress" + 0.004*"planning"
-2024-10-07 09:04:49,868 - topic diff=0.780353, rho=1.000000
-2024-10-07 09:04:49,868 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1068, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:04:49.868588', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:04:50,841 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:04:50,841 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:50,841 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:04:50,841 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:50,841 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:04:50,841 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:50,842 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:04:50,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:50,842 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:04:50,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:04:50,842 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:04:50,842 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:01,554 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:05:01,556 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)
-2024-10-07 09:05:01,556 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-10-07T09:05:01.556880', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:01,557 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:05:01,558 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:05:01,558 - using serial LDA version on this node
-2024-10-07 09:05:01,558 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:05:01,558 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:05:01,562 - -8.036 per-word bound, 262.4 perplexity estimate based on a held-out corpus of 1 documents with 2328 words
-2024-10-07 09:05:01,562 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:05:01,563 - topic #0 (0.333): 0.012*"’" + 0.007*"Milton" + 0.006*"Keynes" + 0.005*"well" + 0.005*"good" + 0.005*"leaders" + 0.005*"practice" + 0.005*"need" + 0.005*"plans" + 0.004*"25"
-2024-10-07 09:05:01,564 - topic #1 (0.333): 0.013*"’" + 0.005*"Keynes" + 0.005*"Milton" + 0.004*"well" + 0.004*"need" + 0.004*"2021" + 0.004*"plans" + 0.004*"education" + 0.004*"October" + 0.003*"needs"
-2024-10-07 09:05:01,564 - topic #2 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"need" + 0.006*"Keynes" + 0.005*"practice" + 0.005*"25" + 0.005*"Milton" + 0.005*"education" + 0.005*"5" + 0.005*"plans"
-2024-10-07 09:05:01,564 - topic diff=0.789233, rho=1.000000
-2024-10-07 09:05:01,564 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1101, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:05:01.564464', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:02,463 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:05:02,464 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:02,464 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:05:02,464 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:02,464 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:05:02,464 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:02,465 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:05:02,465 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:02,465 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:05:02,465 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:02,465 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:05:02,466 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:12,462 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:05:12,463 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)
-2024-10-07 09:05:12,464 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-10-07T09:05:12.464100', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:12,465 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:05:12,465 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:05:12,465 - using serial LDA version on this node
-2024-10-07 09:05:12,465 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:05:12,465 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:05:12,469 - -7.878 per-word bound, 235.2 perplexity estimate based on a held-out corpus of 1 documents with 2076 words
-2024-10-07 09:05:12,469 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:05:12,470 - topic #0 (0.333): 0.014*"’" + 0.009*"plans" + 0.007*"needs" + 0.007*"good" + 0.006*"well" + 0.006*"Newcastle" + 0.006*"protection" + 0.006*"progress" + 0.005*"10" + 0.005*"ensure"
-2024-10-07 09:05:12,470 - topic #1 (0.333): 0.017*"’" + 0.011*"plans" + 0.008*"needs" + 0.007*"protection" + 0.007*"making" + 0.006*"well" + 0.006*"good" + 0.006*"Newcastle" + 0.006*"need" + 0.005*"response"
-2024-10-07 09:05:12,470 - topic #2 (0.333): 0.016*"’" + 0.011*"plans" + 0.008*"Newcastle" + 0.007*"needs" + 0.007*"good" + 0.007*"protection" + 0.006*"ensure" + 0.006*"well" + 0.006*"progress" + 0.006*"management"
-2024-10-07 09:05:12,470 - topic diff=0.782500, rho=1.000000
-2024-10-07 09:05:12,471 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=956, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:05:12.471113', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:13,358 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:05:13,358 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:13,358 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:05:13,358 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:13,358 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:05:13,359 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:13,359 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:05:13,359 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:13,359 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:05:13,359 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:13,359 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:05:13,359 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:25,180 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:05:25,182 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)
-2024-10-07 09:05:25,182 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-10-07T09:05:25.182517', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:25,183 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:05:25,183 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:05:25,184 - using serial LDA version on this node
-2024-10-07 09:05:25,184 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:05:25,184 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:05:25,188 - -8.128 per-word bound, 279.8 perplexity estimate based on a held-out corpus of 1 documents with 2655 words
-2024-10-07 09:05:25,188 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:05:25,190 - topic #0 (0.333): 0.009*"’" + 0.008*"well" + 0.006*"carers" + 0.006*"Norfolk" + 0.005*"supported" + 0.005*"7" + 0.004*"practice" + 0.004*"18" + 0.004*"including" + 0.004*"plans"
-2024-10-07 09:05:25,190 - topic #1 (0.333): 0.019*"’" + 0.008*"Norfolk" + 0.007*"well" + 0.005*"practice" + 0.005*"range" + 0.005*"leaders" + 0.005*"needs" + 0.004*"carers" + 0.004*"including" + 0.004*"plans"
-2024-10-07 09:05:25,190 - topic #2 (0.333): 0.020*"’" + 0.009*"Norfolk" + 0.009*"well" + 0.008*"needs" + 0.007*"carers" + 0.007*"supported" + 0.006*"practice" + 0.005*"plans" + 0.005*"progress" + 0.004*"leaders"
-2024-10-07 09:05:25,190 - topic diff=0.786128, rho=1.000000
-2024-10-07 09:05:25,190 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1221, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:05:25.190674', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:26,110 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:05:26,110 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:26,111 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:05:26,111 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:26,111 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:05:26,111 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:26,111 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:05:26,111 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:26,112 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:05:26,112 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:26,112 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:05:26,112 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:36,400 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:05:36,403 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)
-2024-10-07 09:05:36,403 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-10-07T09:05:36.403348', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:36,404 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:05:36,405 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:05:36,405 - using serial LDA version on this node
-2024-10-07 09:05:36,405 - 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
-2024-10-07 09:05:36,405 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:05:36,411 - -7.894 per-word bound, 237.9 perplexity estimate based on a held-out corpus of 1 documents with 2045 words
-2024-10-07 09:05:36,411 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:05:36,413 - topic #0 (0.333): 0.013*"’" + 0.008*"practice" + 0.007*"risk" + 0.006*"needs" + 0.005*"need" + 0.005*"leaders" + 0.005*"many" + 0.005*"planning" + 0.005*"senior" + 0.004*"quality"
-2024-10-07 09:05:36,414 - topic #1 (0.333): 0.017*"’" + 0.007*"practice" + 0.007*"risk" + 0.007*"leaders" + 0.006*"needs" + 0.006*"planning" + 0.005*"October" + 0.005*"Lincolnshire" + 0.005*"North" + 0.005*"plans"
-2024-10-07 09:05:36,414 - topic #2 (0.333): 0.011*"’" + 0.009*"practice" + 0.007*"planning" + 0.007*"leaders" + 0.007*"risk" + 0.006*"many" + 0.006*"needs" + 0.005*"quality" + 0.005*"need" + 0.005*"2021"
-2024-10-07 09:05:36,414 - topic diff=0.771727, rho=1.000000
-2024-10-07 09:05:36,414 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=958, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:05:36.414723', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:37,630 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:05:37,630 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:37,630 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:05:37,630 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:37,630 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:05:37,630 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:37,631 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:05:37,631 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:37,631 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:05:37,631 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:37,631 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:05:37,631 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:47,308 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:05:47,310 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)
-2024-10-07 09:05:47,310 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-10-07T09:05:47.310963', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:47,311 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:05:47,312 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:05:47,312 - using serial LDA version on this node
-2024-10-07 09:05:47,312 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:05:47,312 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:05:47,316 - -8.066 per-word bound, 267.9 perplexity estimate based on a held-out corpus of 1 documents with 2174 words
-2024-10-07 09:05:47,316 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:05:47,318 - topic #0 (0.333): 0.017*"’" + 0.007*"‘" + 0.006*"well" + 0.006*"North" + 0.006*"family" + 0.005*"team" + 0.005*"need" + 0.005*"approach" + 0.004*"leaders" + 0.004*"10"
-2024-10-07 09:05:47,318 - topic #1 (0.333): 0.024*"’" + 0.007*"family" + 0.006*"Lincolnshire" + 0.006*"North" + 0.006*"leaders" + 0.006*"‘" + 0.005*"well" + 0.005*"approach" + 0.005*"10" + 0.004*"14"
-2024-10-07 09:05:47,318 - topic #2 (0.333): 0.020*"’" + 0.009*"‘" + 0.005*"approach" + 0.005*"council" + 0.005*"Lincolnshire" + 0.005*"10" + 0.005*"leaders" + 0.005*"need" + 0.005*"family" + 0.004*"practice"
-2024-10-07 09:05:47,318 - topic diff=0.748620, rho=1.000000
-2024-10-07 09:05:47,318 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:05:47.318663', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:48,417 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:05:48,418 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:48,418 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:05:48,418 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:48,418 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:05:48,418 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:48,419 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:05:48,419 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:48,419 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:05:48,419 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:48,419 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:05:48,419 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:58,313 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:05:58,316 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)
-2024-10-07 09:05:58,316 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-10-07T09:05:58.316470', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:58,318 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:05:58,318 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:05:58,318 - using serial LDA version on this node
-2024-10-07 09:05:58,319 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:05:58,319 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:05:58,325 - -8.034 per-word bound, 262.1 perplexity estimate based on a held-out corpus of 1 documents with 2204 words
-2024-10-07 09:05:58,325 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:05:58,327 - topic #0 (0.333): 0.018*"’" + 0.009*"Northamptonshire" + 0.008*"North" + 0.007*"well" + 0.006*"quality" + 0.005*"needs" + 0.005*"14" + 0.005*"experiences" + 0.005*"plans" + 0.005*"impact"
-2024-10-07 09:05:58,327 - topic #1 (0.333): 0.017*"’" + 0.009*"Northamptonshire" + 0.006*"quality" + 0.006*"North" + 0.006*"practice" + 0.006*"Leaders" + 0.005*"well" + 0.005*"NCT" + 0.005*"need" + 0.005*"3"
-2024-10-07 09:05:58,327 - topic #2 (0.333): 0.015*"’" + 0.006*"well" + 0.005*"Northamptonshire" + 0.005*"North" + 0.005*"practice" + 0.005*"Leaders" + 0.005*"quality" + 0.004*"impact" + 0.004*"need" + 0.004*"needs"
-2024-10-07 09:05:58,327 - topic diff=0.751124, rho=1.000000
-2024-10-07 09:05:58,327 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:05:58.327934', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:05:59,286 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:05:59,286 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:59,287 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:05:59,287 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:59,287 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:05:59,287 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:59,287 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:05:59,287 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:59,288 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:05:59,288 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:05:59,288 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:05:59,288 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:11,546 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:06:11,549 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)
-2024-10-07 09:06:11,549 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-10-07T09:06:11.549218', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:11,550 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:06:11,550 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:06:11,550 - using serial LDA version on this node
-2024-10-07 09:06:11,551 - 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
-2024-10-07 09:06:11,551 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:06:11,555 - -8.071 per-word bound, 268.9 perplexity estimate based on a held-out corpus of 1 documents with 2902 words
-2024-10-07 09:06:11,555 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:06:11,556 - topic #0 (0.333): 0.017*"’" + 0.006*"quality" + 0.006*"needs" + 0.005*"practice" + 0.005*"well" + 0.005*"risk" + 0.005*"North" + 0.005*"always" + 0.005*"experienced" + 0.005*"Somerset"
-2024-10-07 09:06:11,556 - topic #1 (0.333): 0.016*"’" + 0.007*"quality" + 0.006*"needs" + 0.006*"number" + 0.005*"always" + 0.005*"plans" + 0.005*"Somerset" + 0.005*"North" + 0.005*"need" + 0.005*"practice"
-2024-10-07 09:06:11,557 - topic #2 (0.333): 0.017*"’" + 0.008*"quality" + 0.008*"needs" + 0.007*"always" + 0.007*"Somerset" + 0.006*"North" + 0.006*"progress" + 0.006*"number" + 0.006*"practice" + 0.006*"risk"
-2024-10-07 09:06:11,557 - topic diff=0.833813, rho=1.000000
-2024-10-07 09:06:11,557 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1219, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:06:11.557434', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:13,317 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:06:13,317 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:13,317 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:06:13,318 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:13,318 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:06:13,318 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:13,318 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:06:13,318 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:13,318 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:06:13,318 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:13,319 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:06:13,319 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:24,849 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:06:24,852 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)
-2024-10-07 09:06:24,852 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-10-07T09:06:24.852498', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:24,853 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:06:24,853 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:06:24,854 - using serial LDA version on this node
-2024-10-07 09:06:24,854 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:06:24,854 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:06:24,858 - -8.224 per-word bound, 298.9 perplexity estimate based on a held-out corpus of 1 documents with 2518 words
-2024-10-07 09:06:24,858 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:06:24,860 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.005*"leaders" + 0.005*"need" + 0.004*"impact" + 0.004*"quality" + 0.004*"make" + 0.004*"needs" + 0.004*"early" + 0.004*"protection"
-2024-10-07 09:06:24,860 - topic #1 (0.333): 0.019*"’" + 0.006*"well" + 0.005*"quality" + 0.005*"need" + 0.005*"make" + 0.004*"leaders" + 0.004*"needs" + 0.004*"understand" + 0.004*"progress" + 0.003*"impact"
-2024-10-07 09:06:24,860 - topic #2 (0.333): 0.014*"’" + 0.006*"leaders" + 0.006*"well" + 0.005*"need" + 0.005*"make" + 0.005*"needs" + 0.004*"early" + 0.004*"clear" + 0.004*"protection" + 0.004*"impact"
-2024-10-07 09:06:24,860 - topic diff=0.730326, rho=1.000000
-2024-10-07 09:06:24,860 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1273, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:06:24.860975', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:25,866 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:06:25,866 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:25,866 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:06:25,866 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:25,866 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:06:25,867 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:25,867 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:06:25,867 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:25,867 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:06:25,867 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:25,867 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:06:25,867 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:38,008 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:06:38,011 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)
-2024-10-07 09:06:38,011 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-10-07T09:06:38.011293', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:38,012 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:06:38,012 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:06:38,012 - using serial LDA version on this node
-2024-10-07 09:06:38,013 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:06:38,013 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:06:38,019 - -8.145 per-word bound, 283.2 perplexity estimate based on a held-out corpus of 1 documents with 2759 words
-2024-10-07 09:06:38,019 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:06:38,021 - topic #0 (0.333): 0.023*"’" + 0.009*"well" + 0.007*"needs" + 0.007*"practice" + 0.006*"family" + 0.006*"Yorkshire" + 0.005*"North" + 0.005*"‘" + 0.005*"need" + 0.004*"7"
-2024-10-07 09:06:38,021 - topic #1 (0.333): 0.018*"’" + 0.007*"well" + 0.005*"North" + 0.005*"Yorkshire" + 0.004*"practice" + 0.004*"3" + 0.004*"needs" + 0.004*"carers" + 0.004*"‘" + 0.004*"supported"
-2024-10-07 09:06:38,021 - topic #2 (0.333): 0.019*"’" + 0.008*"well" + 0.008*"North" + 0.007*"Yorkshire" + 0.006*"practice" + 0.006*"family" + 0.005*"3" + 0.005*"‘" + 0.005*"needs" + 0.004*"7"
-2024-10-07 09:06:38,021 - topic diff=0.804902, rho=1.000000
-2024-10-07 09:06:38,021 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1259, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:06:38.021743', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:39,200 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:06:39,200 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:39,200 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:06:39,200 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:39,201 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:06:39,201 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:39,201 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:06:39,201 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:39,201 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:06:39,201 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:39,202 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:06:39,202 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:52,344 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:06:52,346 - built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)
-2024-10-07 09:06:52,347 - Dictionary lifecycle event {'msg': "built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)", 'datetime': '2024-10-07T09:06:52.347052', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:52,348 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:06:52,348 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:06:52,348 - using serial LDA version on this node
-2024-10-07 09:06:52,349 - 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
-2024-10-07 09:06:52,349 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:06:52,353 - -8.068 per-word bound, 268.4 perplexity estimate based on a held-out corpus of 1 documents with 2884 words
-2024-10-07 09:06:52,353 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:06:52,354 - topic #0 (0.333): 0.016*"’" + 0.008*"family" + 0.007*"well" + 0.007*"needs" + 0.006*"experiences" + 0.006*"leaders" + 0.006*"strong" + 0.005*"provide" + 0.005*"practice" + 0.005*"within"
-2024-10-07 09:06:52,354 - topic #1 (0.333): 0.022*"’" + 0.008*"family" + 0.007*"leaders" + 0.007*"strong" + 0.007*"needs" + 0.006*"well" + 0.005*"Northumberland" + 0.005*"plans" + 0.005*"effective" + 0.005*"experiences"
-2024-10-07 09:06:52,355 - topic #2 (0.333): 0.016*"’" + 0.007*"experiences" + 0.007*"family" + 0.006*"Northumberland" + 0.006*"progress" + 0.006*"leaders" + 0.006*"strong" + 0.005*"needs" + 0.005*"provide" + 0.004*"well"
-2024-10-07 09:06:52,355 - topic diff=0.833599, rho=1.000000
-2024-10-07 09:06:52,355 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1218, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:06:52.355254', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:06:53,395 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:06:53,395 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:53,395 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:06:53,396 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:53,396 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:06:53,396 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:53,396 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:06:53,396 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:53,396 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:06:53,397 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:06:53,397 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:06:53,397 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:05,151 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:07:05,154 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
-2024-10-07 09:07:05,154 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-10-07T09:07:05.154241', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:05,155 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:07:05,155 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:07:05,155 - using serial LDA version on this node
-2024-10-07 09:07:05,156 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:07:05,156 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:07:05,162 - -8.027 per-word bound, 260.9 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
-2024-10-07 09:07:05,162 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:07:05,165 - topic #0 (0.333): 0.010*"’" + 0.009*"needs" + 0.005*"effective" + 0.005*"11" + 0.005*"Nottingham" + 0.005*"plans" + 0.005*"However" + 0.005*"impact" + 0.004*"July" + 0.004*"oversight"
-2024-10-07 09:07:05,165 - topic #1 (0.333): 0.014*"’" + 0.010*"needs" + 0.007*"Nottingham" + 0.006*"plans" + 0.005*"effective" + 0.005*"practice" + 0.004*"protection" + 0.004*"impact" + 0.004*"11" + 0.004*"However"
-2024-10-07 09:07:05,165 - topic #2 (0.333): 0.016*"’" + 0.006*"needs" + 0.005*"oversight" + 0.005*"effective" + 0.005*"City" + 0.005*"plans" + 0.005*"impact" + 0.005*"2022" + 0.005*"Nottingham" + 0.005*"risk"
-2024-10-07 09:07:05,165 - topic diff=0.766504, rho=1.000000
-2024-10-07 09:07:05,166 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:07:05.166060', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:06,168 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:07:06,168 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:06,168 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:07:06,168 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:06,169 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:07:06,169 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:06,169 - Inspection date None / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:07:06,169 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:06,169 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:07:06,169 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:06,170 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:07:06,170 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:17,341 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:07:17,343 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)
-2024-10-07 09:07:17,343 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)", 'datetime': '2024-10-07T09:07:17.343399', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:17,344 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:07:17,344 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:07:17,344 - using serial LDA version on this node
-2024-10-07 09:07:17,345 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:07:17,345 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:07:17,348 - -8.006 per-word bound, 257.1 perplexity estimate based on a held-out corpus of 1 documents with 2129 words
-2024-10-07 09:07:17,348 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:07:17,350 - topic #0 (0.333): 0.021*"’" + 0.011*"needs" + 0.009*"well" + 0.007*"Nottinghamshire" + 0.007*"plans" + 0.005*"Leaders" + 0.005*"practice" + 0.005*"ensure" + 0.005*"20" + 0.005*"effective"
-2024-10-07 09:07:17,350 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"Nottinghamshire" + 0.005*"Leaders" + 0.004*"plans" + 0.004*"progress" + 0.004*"effective" + 0.004*"benefit" + 0.004*"ensure"
-2024-10-07 09:07:17,350 - topic #2 (0.333): 0.016*"’" + 0.009*"well" + 0.005*"effective" + 0.005*"plans" + 0.005*"needs" + 0.005*"24" + 0.004*"leaders" + 0.004*"benefit" + 0.004*"2024" + 0.004*"need"
-2024-10-07 09:07:17,350 - topic diff=0.782390, rho=1.000000
-2024-10-07 09:07:17,350 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:07:17.350771', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:18,267 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:07:18,267 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:18,267 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:07:18,268 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:18,268 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:07:18,269 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:18,269 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:07:18,269 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:18,269 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:07:18,270 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:18,270 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:07:18,270 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:30,512 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:07:30,514 - built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)
-2024-10-07 09:07:30,514 - Dictionary lifecycle event {'msg': "built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)", 'datetime': '2024-10-07T09:07:30.514490', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:30,515 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:07:30,515 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:07:30,515 - using serial LDA version on this node
-2024-10-07 09:07:30,516 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:07:30,516 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:07:30,520 - -8.078 per-word bound, 270.1 perplexity estimate based on a held-out corpus of 1 documents with 2441 words
-2024-10-07 09:07:30,520 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:07:30,522 - topic #0 (0.333): 0.011*"’" + 0.009*"plans" + 0.005*"Oldham" + 0.005*"needs" + 0.005*"leaders" + 0.005*"well" + 0.005*"practice" + 0.004*"receive" + 0.004*"24" + 0.004*"appropriate"
-2024-10-07 09:07:30,522 - topic #1 (0.333): 0.015*"’" + 0.010*"well" + 0.007*"plans" + 0.007*"needs" + 0.007*"Oldham" + 0.007*"practice" + 0.006*"PAs" + 0.006*"leaders" + 0.005*"effective" + 0.005*"risk"
-2024-10-07 09:07:30,522 - topic #2 (0.333): 0.012*"’" + 0.008*"plans" + 0.008*"well" + 0.007*"PAs" + 0.006*"needs" + 0.005*"progress" + 0.005*"Oldham" + 0.005*"practice" + 0.005*"appropriate" + 0.004*"leaders"
-2024-10-07 09:07:30,522 - topic diff=0.783423, rho=1.000000
-2024-10-07 09:07:30,522 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1152, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:07:30.522586', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:31,378 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:07:31,378 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:31,378 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:07:31,378 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:31,378 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:07:31,379 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:31,379 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:07:31,379 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:31,379 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:07:31,379 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:31,379 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:07:31,379 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:42,685 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:07:42,687 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)
-2024-10-07 09:07:42,687 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-10-07T09:07:42.687707', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:42,688 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:07:42,688 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:07:42,689 - using serial LDA version on this node
-2024-10-07 09:07:42,689 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:07:42,689 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:07:42,693 - -7.999 per-word bound, 255.8 perplexity estimate based on a held-out corpus of 1 documents with 2294 words
-2024-10-07 09:07:42,693 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:07:42,695 - topic #0 (0.333): 0.019*"’" + 0.011*"needs" + 0.009*"Oxfordshire" + 0.007*"good" + 0.006*"well" + 0.006*"risk" + 0.006*"progress" + 0.006*"quality" + 0.005*"supported" + 0.005*"23"
-2024-10-07 09:07:42,695 - topic #1 (0.333): 0.019*"’" + 0.010*"needs" + 0.007*"well" + 0.007*"risk" + 0.006*"Oxfordshire" + 0.005*"supported" + 0.005*"arrangements" + 0.005*"receive" + 0.005*"access" + 0.005*"good"
-2024-10-07 09:07:42,695 - topic #2 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"well" + 0.006*"Oxfordshire" + 0.005*"supported" + 0.005*"good" + 0.005*"leaders" + 0.005*"12" + 0.004*"practice" + 0.004*"receive"
-2024-10-07 09:07:42,695 - topic diff=0.777842, rho=1.000000
-2024-10-07 09:07:42,695 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1066, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:07:42.695678', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:43,909 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:07:43,909 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:43,910 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:07:43,910 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:43,910 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:07:43,910 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:43,910 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:07:43,910 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:43,911 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:07:43,911 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:43,911 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:07:43,911 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:52,919 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:07:52,920 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)
-2024-10-07 09:07:52,921 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-10-07T09:07:52.921108', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:52,921 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:07:52,922 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:07:52,922 - using serial LDA version on this node
-2024-10-07 09:07:52,922 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:07:52,922 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:07:52,925 - -7.877 per-word bound, 235.0 perplexity estimate based on a held-out corpus of 1 documents with 1737 words
-2024-10-07 09:07:52,925 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:07:52,927 - topic #0 (0.333): 0.017*"needs" + 0.017*"’" + 0.008*"need" + 0.007*"well" + 0.007*"progress" + 0.007*"Peterborough" + 0.006*"2023" + 0.005*"supported" + 0.005*"27" + 0.005*"8"
-2024-10-07 09:07:52,927 - topic #1 (0.333): 0.014*"’" + 0.012*"needs" + 0.007*"need" + 0.007*"Peterborough" + 0.006*"2023" + 0.006*"plans" + 0.006*"supported" + 0.006*"8" + 0.005*"receive" + 0.005*"progress"
-2024-10-07 09:07:52,927 - topic #2 (0.333): 0.011*"’" + 0.009*"needs" + 0.007*"Peterborough" + 0.006*"2023" + 0.006*"well" + 0.005*"good" + 0.005*"need" + 0.004*"plans" + 0.004*"receive" + 0.004*"27"
-2024-10-07 09:07:52,927 - topic diff=0.737929, rho=1.000000
-2024-10-07 09:07:52,927 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=893, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:07:52.927775', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:07:54,069 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:07:54,069 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:54,069 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:07:54,069 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:54,070 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:07:54,070 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:54,070 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:07:54,070 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:54,070 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:07:54,070 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:07:54,070 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:07:54,071 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:07,945 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:08:07,947 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
-2024-10-07 09:08:07,947 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-10-07T09:08:07.947913', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:07,949 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:08:07,949 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:08:07,949 - using serial LDA version on this node
-2024-10-07 09:08:07,949 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:08:07,950 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:08:07,954 - -8.085 per-word bound, 271.5 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
-2024-10-07 09:08:07,954 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:08:07,955 - topic #0 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"Plymouth" + 0.007*"well" + 0.005*"22" + 0.005*"2" + 0.005*"education" + 0.005*"practice" + 0.005*"plans" + 0.005*"benefit"
-2024-10-07 09:08:07,955 - topic #1 (0.333): 0.011*"’" + 0.008*"needs" + 0.006*"well" + 0.006*"Plymouth" + 0.006*"practice" + 0.005*"appropriate" + 0.005*"risks" + 0.005*"Council" + 0.004*"February" + 0.004*"timely"
-2024-10-07 09:08:07,955 - topic #2 (0.333): 0.012*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"Plymouth" + 0.004*"appropriate" + 0.004*"plans" + 0.004*"practice" + 0.004*"2024" + 0.004*"education" + 0.004*"good"
-2024-10-07 09:08:07,956 - topic diff=0.841621, rho=1.000000
-2024-10-07 09:08:07,956 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1232, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:08:07.956149', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:08,924 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:08:08,924 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:08,924 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:08:08,924 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:08,925 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:08:08,925 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:08,925 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:08:08,925 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:08,925 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:08:08,925 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:08,926 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:08:08,926 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:21,815 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:08:21,817 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)
-2024-10-07 09:08:21,818 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-10-07T09:08:21.818041', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:21,819 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:08:21,819 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:08:21,819 - using serial LDA version on this node
-2024-10-07 09:08:21,819 - 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
-2024-10-07 09:08:21,820 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:08:21,824 - -8.106 per-word bound, 275.5 perplexity estimate based on a held-out corpus of 1 documents with 2738 words
-2024-10-07 09:08:21,824 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:08:21,825 - topic #0 (0.333): 0.013*"’" + 0.007*"care-experienced" + 0.007*"well" + 0.006*"needs" + 0.006*"family" + 0.006*"health" + 0.005*"plans" + 0.004*"15" + 0.004*"Portsmouth" + 0.004*"leaders"
-2024-10-07 09:08:21,825 - topic #1 (0.333): 0.015*"’" + 0.009*"care-experienced" + 0.008*"well" + 0.008*"Portsmouth" + 0.007*"needs" + 0.006*"family" + 0.005*"plans" + 0.005*"leaders" + 0.005*"risk" + 0.005*"19"
-2024-10-07 09:08:21,825 - topic #2 (0.333): 0.022*"’" + 0.008*"Portsmouth" + 0.007*"care-experienced" + 0.006*"needs" + 0.006*"well" + 0.006*"health" + 0.005*"plans" + 0.005*"practice" + 0.004*"progress" + 0.004*"19"
-2024-10-07 09:08:21,826 - topic diff=0.791685, rho=1.000000
-2024-10-07 09:08:21,826 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:08:21.826195', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:22,803 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:08:22,803 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:22,804 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:08:22,804 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:22,804 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:08:22,804 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:22,804 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:08:22,804 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:22,805 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:08:22,805 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:22,805 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:08:22,805 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:34,385 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:08:34,387 - built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)
-2024-10-07 09:08:34,387 - Dictionary lifecycle event {'msg': "built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)", 'datetime': '2024-10-07T09:08:34.387537', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:34,388 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:08:34,388 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:08:34,389 - using serial LDA version on this node
-2024-10-07 09:08:34,389 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:08:34,389 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:08:34,393 - -8.157 per-word bound, 285.5 perplexity estimate based on a held-out corpus of 1 documents with 2562 words
-2024-10-07 09:08:34,393 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:08:34,395 - topic #0 (0.333): 0.013*"’" + 0.006*"needs" + 0.005*"PAs" + 0.005*"plans" + 0.004*"progress" + 0.004*"well" + 0.004*"3" + 0.004*"arrangements" + 0.004*"22" + 0.004*"family"
-2024-10-07 09:08:34,395 - topic #1 (0.333): 0.012*"’" + 0.005*"needs" + 0.005*"Reading" + 0.005*"clear" + 0.005*"progress" + 0.005*"plans" + 0.004*"PAs" + 0.004*"timely" + 0.004*"3" + 0.004*"2024"
-2024-10-07 09:08:34,395 - topic #2 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"PAs" + 0.006*"well" + 0.005*"progress" + 0.005*"plans" + 0.005*"Reading" + 0.005*"May" + 0.004*"22" + 0.004*"effective"
-2024-10-07 09:08:34,395 - topic diff=0.767321, rho=1.000000
-2024-10-07 09:08:34,395 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1231, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:08:34.395574', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:35,382 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:08:35,382 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:35,382 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:08:35,383 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:35,383 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:08:35,383 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:35,383 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:08:35,383 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:35,383 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:08:35,384 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:35,384 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:08:35,384 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:46,571 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:08:46,574 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)
-2024-10-07 09:08:46,574 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-10-07T09:08:46.574311', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:46,575 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:08:46,575 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:08:46,575 - using serial LDA version on this node
-2024-10-07 09:08:46,576 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:08:46,576 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:08:46,579 - -8.005 per-word bound, 256.8 perplexity estimate based on a held-out corpus of 1 documents with 2515 words
-2024-10-07 09:08:46,580 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:08:46,581 - topic #0 (0.333): 0.017*"’" + 0.006*"However" + 0.006*"Redcar" + 0.006*"consistently" + 0.005*"leaders" + 0.005*"plans" + 0.005*"practice" + 0.005*"2022" + 0.005*"Cleveland" + 0.005*"needs"
-2024-10-07 09:08:46,581 - topic #1 (0.333): 0.016*"’" + 0.005*"However" + 0.005*"consistently" + 0.005*"plans" + 0.005*"risk" + 0.004*"Cleveland" + 0.004*"practice" + 0.004*"response" + 0.004*"June" + 0.004*"appropriate"
-2024-10-07 09:08:46,581 - topic #2 (0.333): 0.019*"’" + 0.008*"leaders" + 0.007*"needs" + 0.006*"plans" + 0.006*"20" + 0.005*"carers" + 0.005*"2022" + 0.005*"However" + 0.005*"consistently" + 0.005*"practice"
-2024-10-07 09:08:46,581 - topic diff=0.803247, rho=1.000000
-2024-10-07 09:08:46,581 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:08:46.581953', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:08:47,505 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:08:47,506 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:47,506 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:08:47,506 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:47,506 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:08:47,506 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:47,506 - Inspection date None / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:08:47,506 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:47,507 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:08:47,507 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:08:47,507 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:08:47,507 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:00,159 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:09:00,161 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)
-2024-10-07 09:09:00,161 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-10-07T09:09:00.161592', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:00,162 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:09:00,162 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:09:00,163 - using serial LDA version on this node
-2024-10-07 09:09:00,163 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:09:00,163 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:09:00,167 - -8.028 per-word bound, 261.0 perplexity estimate based on a held-out corpus of 1 documents with 2656 words
-2024-10-07 09:09:00,167 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:09:00,168 - topic #0 (0.333): 0.019*"’" + 0.009*"experienced" + 0.009*"needs" + 0.007*"practice" + 0.006*"plans" + 0.006*"Rochdale" + 0.005*"quality" + 0.005*"PAs" + 0.005*"response" + 0.005*"well"
-2024-10-07 09:09:00,169 - topic #1 (0.333): 0.023*"’" + 0.009*"experienced" + 0.009*"practice" + 0.007*"response" + 0.007*"needs" + 0.006*"good" + 0.006*"plans" + 0.005*"consistently" + 0.005*"3" + 0.005*"quality"
-2024-10-07 09:09:00,169 - topic #2 (0.333): 0.017*"’" + 0.010*"experienced" + 0.008*"practice" + 0.007*"needs" + 0.006*"plans" + 0.006*"consistently" + 0.005*"response" + 0.005*"3" + 0.005*"quality" + 0.004*"well"
-2024-10-07 09:09:00,169 - topic diff=0.819981, rho=1.000000
-2024-10-07 09:09:00,169 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1150, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:09:00.169400', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:01,225 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:09:01,225 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:01,225 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:09:01,225 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:01,226 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:09:01,226 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:01,226 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:09:01,226 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:01,226 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:09:01,226 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:01,226 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:09:01,227 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:12,970 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:09:12,972 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)
-2024-10-07 09:09:12,972 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-10-07T09:09:12.972641', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:12,973 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:09:12,973 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:09:12,974 - using serial LDA version on this node
-2024-10-07 09:09:12,974 - 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
-2024-10-07 09:09:12,974 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:09:12,978 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2366 words
-2024-10-07 09:09:12,978 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:09:12,979 - topic #0 (0.333): 0.013*"’" + 0.005*"needs" + 0.005*"Rotherham" + 0.004*"good" + 0.004*"well" + 0.004*"However" + 0.004*"clear" + 0.003*"July" + 0.003*"ensure" + 0.003*"plans"
-2024-10-07 09:09:12,979 - topic #1 (0.333): 0.015*"’" + 0.009*"Rotherham" + 0.006*"needs" + 0.006*"well" + 0.005*"ensure" + 0.005*"Council" + 0.004*"Metropolitan" + 0.004*"27" + 0.004*"protection" + 0.004*"improve"
-2024-10-07 09:09:12,980 - topic #2 (0.333): 0.016*"’" + 0.011*"Rotherham" + 0.007*"needs" + 0.006*"good" + 0.005*"Council" + 0.005*"plans" + 0.005*"well" + 0.005*"However" + 0.005*"ensure" + 0.004*"clear"
-2024-10-07 09:09:12,980 - topic diff=0.786865, rho=1.000000
-2024-10-07 09:09:12,980 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1127, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:09:12.980459', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:13,862 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:09:13,862 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:13,863 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:09:13,863 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:13,863 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:09:13,863 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:13,863 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:09:13,863 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:13,863 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:09:13,864 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:13,864 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:09:13,864 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:24,341 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:09:24,344 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)
-2024-10-07 09:09:24,344 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-10-07T09:09:24.344221', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:24,345 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:09:24,345 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:09:24,345 - using serial LDA version on this node
-2024-10-07 09:09:24,346 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:09:24,346 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:09:24,349 - -8.047 per-word bound, 264.5 perplexity estimate based on a held-out corpus of 1 documents with 2380 words
-2024-10-07 09:09:24,349 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:09:24,351 - topic #0 (0.333): 0.010*"well" + 0.010*"’" + 0.009*"practice" + 0.008*"highly" + 0.006*"strong" + 0.006*"leaders" + 0.006*"needs" + 0.005*"effective" + 0.004*"professionals" + 0.004*"need"
-2024-10-07 09:09:24,351 - topic #1 (0.333): 0.014*"’" + 0.013*"well" + 0.011*"practice" + 0.008*"highly" + 0.005*"needs" + 0.005*"strong" + 0.005*"effective" + 0.005*"high" + 0.004*"range" + 0.004*"leaders"
-2024-10-07 09:09:24,351 - topic #2 (0.333): 0.016*"well" + 0.011*"practice" + 0.011*"’" + 0.007*"strong" + 0.006*"effective" + 0.005*"needs" + 0.005*"highly" + 0.005*"leaders" + 0.005*"professionals" + 0.004*"high"
-2024-10-07 09:09:24,351 - topic diff=0.769015, rho=1.000000
-2024-10-07 09:09:24,352 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:09:24.352040', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:25,389 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:09:25,389 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:25,389 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:09:25,390 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:25,390 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:09:25,390 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:25,390 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:09:25,390 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:25,390 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:09:25,390 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:25,391 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:09:25,391 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:36,056 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:09:36,058 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)
-2024-10-07 09:09:36,058 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-10-07T09:09:36.058564', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:36,059 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:09:36,059 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:09:36,059 - using serial LDA version on this node
-2024-10-07 09:09:36,060 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:09:36,060 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:09:36,064 - -8.070 per-word bound, 268.7 perplexity estimate based on a held-out corpus of 1 documents with 2257 words
-2024-10-07 09:09:36,064 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:09:36,065 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.008*"plans" + 0.006*"needs" + 0.005*"good" + 0.004*"practice" + 0.004*"parents" + 0.004*"effective" + 0.004*"progress" + 0.004*"risk"
-2024-10-07 09:09:36,065 - topic #1 (0.333): 0.010*"’" + 0.008*"plans" + 0.007*"well" + 0.007*"needs" + 0.005*"good" + 0.004*"supported" + 0.004*"effective" + 0.004*"clear" + 0.004*"appropriate" + 0.004*"practice"
-2024-10-07 09:09:36,066 - topic #2 (0.333): 0.015*"’" + 0.011*"well" + 0.009*"needs" + 0.008*"plans" + 0.005*"need" + 0.005*"effective" + 0.005*"good" + 0.004*"clear" + 0.004*"practice" + 0.004*"parents"
-2024-10-07 09:09:36,066 - topic diff=0.754745, rho=1.000000
-2024-10-07 09:09:36,066 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1107, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:09:36.066232', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:37,262 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:09:37,262 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:37,263 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:09:37,263 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:37,263 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:09:37,263 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:37,263 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:09:37,263 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:37,263 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:09:37,263 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:37,264 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:09:37,264 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:48,058 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:09:48,061 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)
-2024-10-07 09:09:48,061 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-10-07T09:09:48.061269', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:48,062 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:09:48,062 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:09:48,062 - using serial LDA version on this node
-2024-10-07 09:09:48,063 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:09:48,063 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:09:48,066 - -8.118 per-word bound, 277.8 perplexity estimate based on a held-out corpus of 1 documents with 2088 words
-2024-10-07 09:09:48,067 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:09:48,068 - topic #0 (0.333): 0.008*"’" + 0.005*"needs" + 0.005*"well" + 0.003*"plans" + 0.003*"risk" + 0.003*"quality" + 0.003*"health" + 0.003*"information" + 0.003*"timely" + 0.003*"use"
-2024-10-07 09:09:48,068 - topic #1 (0.333): 0.014*"’" + 0.006*"well" + 0.005*"quality" + 0.005*"plans" + 0.004*"needs" + 0.004*"benefit" + 0.004*"use" + 0.004*"effective" + 0.004*"always" + 0.004*"changes"
-2024-10-07 09:09:48,068 - topic #2 (0.333): 0.012*"’" + 0.005*"quality" + 0.005*"well" + 0.005*"needs" + 0.005*"information" + 0.005*"plans" + 0.004*"effective" + 0.004*"actions" + 0.004*"use" + 0.004*"However"
-2024-10-07 09:09:48,068 - topic diff=0.728304, rho=1.000000
-2024-10-07 09:09:48,069 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:09:48.069088', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:09:49,320 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:09:49,320 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:49,320 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:09:49,320 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:49,321 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:09:49,321 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:49,321 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:09:49,321 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:49,321 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:09:49,321 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:09:49,322 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:09:49,322 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:00,715 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:10:00,717 - built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)
-2024-10-07 09:10:00,717 - Dictionary lifecycle event {'msg': "built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)", 'datetime': '2024-10-07T09:10:00.717427', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:00,718 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:10:00,718 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:10:00,718 - using serial LDA version on this node
-2024-10-07 09:10:00,719 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:10:00,719 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:10:00,722 - -8.053 per-word bound, 265.6 perplexity estimate based on a held-out corpus of 1 documents with 2211 words
-2024-10-07 09:10:00,723 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:10:00,724 - topic #0 (0.333): 0.023*"’" + 0.011*"Rutland" + 0.008*"needs" + 0.008*"effective" + 0.006*"plans" + 0.006*"positive" + 0.005*"good" + 0.005*"impact" + 0.005*"need" + 0.005*"family"
-2024-10-07 09:10:00,724 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.007*"Rutland" + 0.007*"impact" + 0.006*"effective" + 0.005*"need" + 0.005*"positive" + 0.005*"experiences" + 0.004*"plans" + 0.004*"15"
-2024-10-07 09:10:00,724 - topic #2 (0.333): 0.018*"’" + 0.007*"Rutland" + 0.006*"impact" + 0.006*"needs" + 0.006*"positive" + 0.005*"plans" + 0.005*"practice" + 0.005*"PAs" + 0.005*"need" + 0.004*"well"
-2024-10-07 09:10:00,724 - topic diff=0.778486, rho=1.000000
-2024-10-07 09:10:00,725 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1089, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:10:00.725002', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:01,694 - Inspection date 2024-04-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:10:01,694 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:01,694 - Inspection date 2024-04-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:10:01,694 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:01,695 - Inspection date 2024-04-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:10:01,695 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:01,695 - Inspection date 2024-04-15 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:10:01,695 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:01,695 - Inspection date 2024-04-15 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:10:01,695 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:01,696 - Inspection date 2024-04-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:10:01,696 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:12,921 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:10:12,923 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)
-2024-10-07 09:10:12,923 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-10-07T09:10:12.923717', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:12,924 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:10:12,924 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:10:12,925 - using serial LDA version on this node
-2024-10-07 09:10:12,925 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:10:12,925 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:10:12,929 - -8.010 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2253 words
-2024-10-07 09:10:12,929 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:10:12,930 - topic #0 (0.333): 0.013*"’" + 0.008*"needs" + 0.008*"plans" + 0.007*"well" + 0.007*"effective" + 0.005*"Salford" + 0.005*"leaders" + 0.005*"practice" + 0.004*"November" + 0.004*"6"
-2024-10-07 09:10:12,930 - topic #1 (0.333): 0.012*"’" + 0.008*"plans" + 0.007*"needs" + 0.006*"effective" + 0.006*"well" + 0.005*"progress" + 0.005*"Salford" + 0.005*"practice" + 0.004*"planning" + 0.004*"appropriate"
-2024-10-07 09:10:12,930 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.007*"plans" + 0.007*"needs" + 0.006*"Salford" + 0.006*"planning" + 0.006*"effective" + 0.005*"2023" + 0.005*"Council" + 0.005*"experiences"
-2024-10-07 09:10:12,931 - topic diff=0.786686, rho=1.000000
-2024-10-07 09:10:12,931 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:10:12.931200', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:13,791 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:10:13,792 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:13,792 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:10:13,792 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:13,792 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:10:13,793 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:13,793 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:10:13,793 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:13,793 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:10:13,793 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:13,793 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:10:13,793 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:23,596 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:10:23,598 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)
-2024-10-07 09:10:23,598 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-10-07T09:10:23.598913', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:23,599 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:10:23,599 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:10:23,600 - using serial LDA version on this node
-2024-10-07 09:10:23,600 - 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
-2024-10-07 09:10:23,600 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:10:23,603 - -7.946 per-word bound, 246.5 perplexity estimate based on a held-out corpus of 1 documents with 2066 words
-2024-10-07 09:10:23,604 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:10:23,605 - topic #0 (0.333): 0.016*"’" + 0.008*"Sandwell" + 0.007*"plans" + 0.007*"needs" + 0.006*"well" + 0.006*"quality" + 0.005*"progress" + 0.005*"Trust" + 0.005*"9" + 0.005*"20"
-2024-10-07 09:10:23,605 - topic #1 (0.333): 0.015*"’" + 0.010*"needs" + 0.007*"Sandwell" + 0.007*"well" + 0.007*"plans" + 0.006*"quality" + 0.005*"education" + 0.005*"number" + 0.005*"many" + 0.004*"good"
-2024-10-07 09:10:23,605 - topic #2 (0.333): 0.009*"’" + 0.006*"Sandwell" + 0.006*"plans" + 0.006*"well" + 0.005*"needs" + 0.004*"Trust" + 0.004*"quality" + 0.004*"number" + 0.004*"progress" + 0.004*"training"
-2024-10-07 09:10:23,605 - topic diff=0.774216, rho=1.000000
-2024-10-07 09:10:23,605 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=995, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:10:23.605896', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:24,636 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:10:24,636 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:24,637 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:10:24,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:24,637 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:10:24,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:24,637 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:10:24,637 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:24,638 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:10:24,638 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:24,638 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:10:24,638 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:35,381 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:10:35,383 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)
-2024-10-07 09:10:35,383 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-10-07T09:10:35.383780', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:35,384 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:10:35,384 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:10:35,385 - using serial LDA version on this node
-2024-10-07 09:10:35,385 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:10:35,385 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:10:35,389 - -7.927 per-word bound, 243.3 perplexity estimate based on a held-out corpus of 1 documents with 2300 words
-2024-10-07 09:10:35,389 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:10:35,390 - topic #0 (0.333): 0.020*"’" + 0.010*"needs" + 0.006*"oversight" + 0.006*"lack" + 0.005*"management" + 0.005*"4" + 0.005*"plans" + 0.005*"practice" + 0.005*"◼" + 0.005*"always"
-2024-10-07 09:10:35,390 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.006*"practice" + 0.005*"including" + 0.004*"oversight" + 0.004*"many" + 0.004*"lack" + 0.004*"ocal" + 0.004*"protection" + 0.004*"always"
-2024-10-07 09:10:35,390 - topic #2 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"practice" + 0.006*"protection" + 0.005*"oversight" + 0.005*"including" + 0.005*"March" + 0.005*"◼" + 0.005*"many" + 0.005*"management"
-2024-10-07 09:10:35,391 - topic diff=0.798565, rho=1.000000
-2024-10-07 09:10:35,391 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:10:35.391148', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:36,319 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:10:36,319 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:36,319 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:10:36,319 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:36,319 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:10:36,320 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:36,320 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:10:36,320 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:36,320 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:10:36,320 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:36,320 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:10:36,320 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:47,608 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:10:47,610 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)
-2024-10-07 09:10:47,610 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-10-07T09:10:47.610949', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:47,612 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:10:47,612 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:10:47,612 - using serial LDA version on this node
-2024-10-07 09:10:47,612 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:10:47,612 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:10:47,616 - -8.067 per-word bound, 268.2 perplexity estimate based on a held-out corpus of 1 documents with 2327 words
-2024-10-07 09:10:47,616 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:10:47,618 - topic #0 (0.333): 0.021*"’" + 0.014*"Sheffield" + 0.011*"needs" + 0.008*"well" + 0.006*"health" + 0.006*"practice" + 0.005*"leaders" + 0.005*"good" + 0.005*"quality" + 0.005*"adviser"
-2024-10-07 09:10:47,618 - topic #1 (0.333): 0.013*"’" + 0.007*"Sheffield" + 0.007*"needs" + 0.006*"leaders" + 0.005*"practice" + 0.005*"well" + 0.004*"receive" + 0.004*"11" + 0.004*"health" + 0.004*"experiences"
-2024-10-07 09:10:47,618 - topic #2 (0.333): 0.024*"’" + 0.011*"Sheffield" + 0.007*"needs" + 0.007*"well" + 0.005*"leaders" + 0.005*"practice" + 0.005*"health" + 0.005*"mental" + 0.005*"22" + 0.005*"ensure"
-2024-10-07 09:10:47,618 - topic diff=0.776956, rho=1.000000
-2024-10-07 09:10:47,618 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:10:47.618708', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:48,564 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:10:48,564 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:48,564 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:10:48,564 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:48,564 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:10:48,564 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:48,565 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:10:48,565 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:48,565 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:10:48,565 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:48,565 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:10:48,565 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:56,551 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:10:56,554 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)
-2024-10-07 09:10:56,554 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-10-07T09:10:56.554412', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:56,555 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:10:56,555 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:10:56,556 - using serial LDA version on this node
-2024-10-07 09:10:56,556 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:10:56,556 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:10:56,562 - -7.961 per-word bound, 249.1 perplexity estimate based on a held-out corpus of 1 documents with 1749 words
-2024-10-07 09:10:56,563 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:10:56,565 - topic #0 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"Shropshire" + 0.005*"well" + 0.005*"progress" + 0.005*"plans" + 0.005*"making" + 0.005*"7" + 0.005*"February" + 0.005*"2022"
-2024-10-07 09:10:56,565 - topic #1 (0.333): 0.017*"’" + 0.008*"well" + 0.007*"Shropshire" + 0.007*"needs" + 0.006*"progress" + 0.006*"plans" + 0.005*"making" + 0.005*"training" + 0.005*"2022" + 0.005*"leaders"
-2024-10-07 09:10:56,565 - topic #2 (0.333): 0.018*"’" + 0.009*"needs" + 0.007*"well" + 0.006*"progress" + 0.005*"7" + 0.005*"2022" + 0.005*"Shropshire" + 0.005*"plans" + 0.004*"making" + 0.004*"effectively"
-2024-10-07 09:10:56,565 - topic diff=0.715719, rho=1.000000
-2024-10-07 09:10:56,566 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=939, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:10:56.566168', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:10:57,449 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:10:57,449 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:57,449 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:10:57,449 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:57,450 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:10:57,450 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:57,450 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:10:57,450 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:57,450 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:10:57,450 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:10:57,451 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:10:57,451 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:09,137 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:11:09,140 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)
-2024-10-07 09:11:09,140 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-10-07T09:11:09.140274', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:09,141 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:11:09,141 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:11:09,141 - using serial LDA version on this node
-2024-10-07 09:11:09,142 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:11:09,142 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:11:09,145 - -8.047 per-word bound, 264.4 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
-2024-10-07 09:11:09,146 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:11:09,147 - topic #0 (0.333): 0.013*"’" + 0.008*"Slough" + 0.007*"plans" + 0.005*"practice" + 0.005*"impact" + 0.005*"quality" + 0.005*"needs" + 0.004*"3" + 0.004*"leaders" + 0.004*"However"
-2024-10-07 09:11:09,147 - topic #1 (0.333): 0.019*"’" + 0.009*"Slough" + 0.006*"needs" + 0.006*"quality" + 0.006*"plans" + 0.006*"practice" + 0.005*"leaders" + 0.005*"supported" + 0.005*"senior" + 0.005*"3"
-2024-10-07 09:11:09,147 - topic #2 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"quality" + 0.006*"Slough" + 0.006*"practice" + 0.005*"impact" + 0.005*"plans" + 0.004*"3" + 0.004*"23" + 0.004*"PAs"
-2024-10-07 09:11:09,147 - topic diff=0.786063, rho=1.000000
-2024-10-07 09:11:09,148 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1113, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:11:09.148005', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:10,053 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:11:10,053 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:10,053 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:11:10,053 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:10,053 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:11:10,054 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:10,054 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:11:10,054 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:10,054 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:11:10,054 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:10,054 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:11:10,054 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:20,863 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:11:20,865 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)
-2024-10-07 09:11:20,865 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-10-07T09:11:20.865849', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:20,867 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:11:20,867 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:11:20,867 - using serial LDA version on this node
-2024-10-07 09:11:20,867 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:11:20,867 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:11:20,871 - -7.920 per-word bound, 242.2 perplexity estimate based on a held-out corpus of 1 documents with 2163 words
-2024-10-07 09:11:20,871 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:11:20,872 - topic #0 (0.333): 0.011*"’" + 0.009*"lack" + 0.006*"2022" + 0.005*"means" + 0.005*"risk" + 0.005*"Solihull" + 0.004*"practice" + 0.004*"quality" + 0.004*"effective" + 0.004*"worker"
-2024-10-07 09:11:20,872 - topic #1 (0.333): 0.020*"’" + 0.011*"lack" + 0.010*"2022" + 0.009*"need" + 0.008*"Solihull" + 0.006*"quality" + 0.006*"significant" + 0.005*"practice" + 0.005*"experiences" + 0.005*"effective"
-2024-10-07 09:11:20,873 - topic #2 (0.333): 0.013*"’" + 0.011*"lack" + 0.009*"2022" + 0.008*"risk" + 0.006*"experiences" + 0.005*"practice" + 0.005*"effective" + 0.005*"quality" + 0.005*"Solihull" + 0.005*"progress"
-2024-10-07 09:11:20,873 - topic diff=0.797496, rho=1.000000
-2024-10-07 09:11:20,873 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=996, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:11:20.873300', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:21,797 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:11:21,797 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:21,797 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:11:21,797 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:21,797 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:11:21,798 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:21,798 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:11:21,798 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:21,798 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:11:21,798 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:21,798 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:11:21,798 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:32,106 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:11:32,108 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)
-2024-10-07 09:11:32,109 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-10-07T09:11:32.109001', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:32,109 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:11:32,110 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:11:32,110 - using serial LDA version on this node
-2024-10-07 09:11:32,110 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:11:32,110 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:11:32,114 - -7.921 per-word bound, 242.3 perplexity estimate based on a held-out corpus of 1 documents with 2181 words
-2024-10-07 09:11:32,114 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:11:32,115 - topic #0 (0.333): 0.014*"’" + 0.009*"needs" + 0.009*"Somerset" + 0.007*"well" + 0.007*"plans" + 0.005*"supported" + 0.005*"progress" + 0.005*"need" + 0.005*"number" + 0.005*"including"
-2024-10-07 09:11:32,115 - topic #1 (0.333): 0.019*"’" + 0.009*"well" + 0.009*"needs" + 0.007*"Somerset" + 0.006*"good" + 0.006*"plans" + 0.005*"practice" + 0.005*"leaders" + 0.005*"family" + 0.005*"including"
-2024-10-07 09:11:32,115 - topic #2 (0.333): 0.017*"’" + 0.010*"well" + 0.007*"needs" + 0.006*"good" + 0.005*"supported" + 0.005*"plans" + 0.005*"number" + 0.005*"progress" + 0.005*"leaders" + 0.005*"understand"
-2024-10-07 09:11:32,116 - topic diff=0.802590, rho=1.000000
-2024-10-07 09:11:32,116 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:11:32.116187', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:32,966 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:11:32,966 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:32,967 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:11:32,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:32,967 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:11:32,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:32,967 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:11:32,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:32,968 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:11:32,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:32,968 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:11:32,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:44,783 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:11:44,785 - built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)
-2024-10-07 09:11:44,786 - Dictionary lifecycle event {'msg': "built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)", 'datetime': '2024-10-07T09:11:44.786082', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:44,787 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:11:44,787 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:11:44,787 - using serial LDA version on this node
-2024-10-07 09:11:44,787 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:11:44,788 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:11:44,792 - -8.059 per-word bound, 266.7 perplexity estimate based on a held-out corpus of 1 documents with 2751 words
-2024-10-07 09:11:44,792 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:11:44,793 - topic #0 (0.333): 0.018*"’" + 0.012*"needs" + 0.006*"June" + 0.006*"well" + 0.006*"leaders" + 0.006*"2024" + 0.006*"plans" + 0.005*"South" + 0.005*"understand" + 0.005*"quality"
-2024-10-07 09:11:44,794 - topic #1 (0.333): 0.019*"’" + 0.011*"needs" + 0.007*"leaders" + 0.007*"2024" + 0.006*"June" + 0.006*"ensure" + 0.006*"effective" + 0.006*"Gloucestershire" + 0.005*"strong" + 0.005*"well"
-2024-10-07 09:11:44,794 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"leaders" + 0.006*"2024" + 0.006*"June" + 0.005*"well" + 0.005*"quality" + 0.005*"understand" + 0.005*"progress" + 0.005*"effective"
-2024-10-07 09:11:44,794 - topic diff=0.835526, rho=1.000000
-2024-10-07 09:11:44,794 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1188, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:11:44.794481', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:45,740 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:11:45,740 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:45,741 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:11:45,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:45,741 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:11:45,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:45,741 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:11:45,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:45,741 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:11:45,742 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:45,742 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:11:45,742 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:55,630 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:11:55,632 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions)
-2024-10-07 09:11:55,632 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-10-07T09:11:55.632437', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:55,633 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:11:55,633 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:11:55,633 - using serial LDA version on this node
-2024-10-07 09:11:55,634 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:11:55,634 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:11:55,637 - -7.886 per-word bound, 236.5 perplexity estimate based on a held-out corpus of 1 documents with 2189 words
-2024-10-07 09:11:55,637 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:11:55,638 - topic #0 (0.333): 0.023*"’" + 0.010*"needs" + 0.009*"South" + 0.007*"Tyneside" + 0.005*"oversight" + 0.005*"9" + 0.005*"5" + 0.005*"However" + 0.005*"management" + 0.005*"2022"
-2024-10-07 09:11:55,639 - topic #1 (0.333): 0.028*"’" + 0.008*"needs" + 0.007*"South" + 0.006*"Tyneside" + 0.006*"2023" + 0.005*"risk" + 0.005*"effective" + 0.005*"5" + 0.005*"practice" + 0.005*"management"
-2024-10-07 09:11:55,639 - topic #2 (0.333): 0.021*"’" + 0.009*"Tyneside" + 0.008*"needs" + 0.006*"carers" + 0.006*"South" + 0.005*"However" + 0.005*"oversight" + 0.005*"management" + 0.005*"effective" + 0.004*"14"
-2024-10-07 09:11:55,639 - topic diff=0.795319, rho=1.000000
-2024-10-07 09:11:55,639 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=981, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:11:55.639547', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:11:56,605 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:11:56,605 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:56,605 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:11:56,605 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:56,605 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:11:56,606 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:56,606 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:11:56,606 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:56,606 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:11:56,606 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:11:56,606 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:11:56,606 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:07,595 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:12:07,597 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)
-2024-10-07 09:12:07,597 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-10-07T09:12:07.597431', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:07,598 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:12:07,598 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:12:07,598 - using serial LDA version on this node
-2024-10-07 09:12:07,599 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:12:07,599 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:12:07,603 - -8.152 per-word bound, 284.4 perplexity estimate based on a held-out corpus of 1 documents with 2318 words
-2024-10-07 09:12:07,603 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:12:07,604 - topic #0 (0.333): 0.018*"’" + 0.006*"plans" + 0.005*"Southampton" + 0.005*"improve" + 0.004*"timely" + 0.004*"including" + 0.004*"experiences" + 0.004*"June" + 0.004*"well" + 0.004*"2023"
-2024-10-07 09:12:07,605 - topic #1 (0.333): 0.013*"’" + 0.005*"5" + 0.005*"plans" + 0.005*"good" + 0.005*"Southampton" + 0.005*"needs" + 0.004*"improve" + 0.004*"progress" + 0.004*"including" + 0.004*"experiences"
-2024-10-07 09:12:07,605 - topic #2 (0.333): 0.017*"’" + 0.007*"Southampton" + 0.006*"plans" + 0.006*"progress" + 0.005*"improve" + 0.005*"including" + 0.004*"well" + 0.004*"needs" + 0.004*"16" + 0.004*"provide"
-2024-10-07 09:12:07,605 - topic diff=0.743066, rho=1.000000
-2024-10-07 09:12:07,605 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1178, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:12:07.605463', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:08,749 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:12:08,749 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:08,750 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:12:08,750 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:08,750 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:12:08,750 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:08,750 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:12:08,750 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:08,750 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:12:08,750 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:08,751 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:12:08,751 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:18,881 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:12:18,885 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)
-2024-10-07 09:12:18,885 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-10-07T09:12:18.885416', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:18,886 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:12:18,887 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:12:18,887 - using serial LDA version on this node
-2024-10-07 09:12:18,888 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:12:18,888 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:12:18,893 - -7.951 per-word bound, 247.5 perplexity estimate based on a held-out corpus of 1 documents with 2086 words
-2024-10-07 09:12:18,893 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:12:18,895 - topic #0 (0.333): 0.013*"’" + 0.008*"practice" + 0.007*"quality" + 0.006*"leaders" + 0.005*"planning" + 0.005*"within" + 0.005*"needs" + 0.005*"protection" + 0.005*"number" + 0.005*"risk"
-2024-10-07 09:12:18,896 - topic #1 (0.333): 0.014*"’" + 0.010*"planning" + 0.007*"quality" + 0.006*"effective" + 0.006*"practice" + 0.006*"always" + 0.006*"protection" + 0.006*"leaders" + 0.006*"good" + 0.005*"need"
-2024-10-07 09:12:18,896 - topic #2 (0.333): 0.012*"’" + 0.007*"practice" + 0.007*"planning" + 0.006*"number" + 0.006*"leaders" + 0.005*"quality" + 0.005*"within" + 0.005*"protection" + 0.004*"carers" + 0.004*"always"
-2024-10-07 09:12:18,896 - topic diff=0.777020, rho=1.000000
-2024-10-07 09:12:18,896 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:12:18.896779', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:20,706 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:12:20,706 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:20,706 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:12:20,706 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:20,706 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:12:20,707 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:20,707 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:12:20,707 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:20,707 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:12:20,707 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:20,707 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:12:20,707 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:33,289 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:12:33,291 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)
-2024-10-07 09:12:33,291 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-10-07T09:12:33.291792', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:33,292 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:12:33,292 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:12:33,293 - using serial LDA version on this node
-2024-10-07 09:12:33,293 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:12:33,293 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:12:33,297 - -8.051 per-word bound, 265.1 perplexity estimate based on a held-out corpus of 1 documents with 2218 words
-2024-10-07 09:12:33,297 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:12:33,298 - topic #0 (0.333): 0.013*"’" + 0.008*"Helens" + 0.007*"St" + 0.006*"well" + 0.006*"needs" + 0.005*"good" + 0.005*"effective" + 0.005*"10" + 0.005*"need" + 0.005*"21"
-2024-10-07 09:12:33,298 - topic #1 (0.333): 0.013*"’" + 0.008*"Helens" + 0.008*"needs" + 0.008*"St" + 0.005*"well" + 0.005*"good" + 0.005*"progress" + 0.004*"2023" + 0.004*"10" + 0.004*"21"
-2024-10-07 09:12:33,299 - topic #2 (0.333): 0.019*"’" + 0.008*"St" + 0.007*"progress" + 0.007*"well" + 0.007*"receive" + 0.007*"needs" + 0.007*"Helens" + 0.006*"risk" + 0.006*"need" + 0.006*"21"
-2024-10-07 09:12:33,299 - topic diff=0.781198, rho=1.000000
-2024-10-07 09:12:33,299 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:12:33.299337', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:34,238 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:12:34,238 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:34,239 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:12:34,239 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:34,239 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:12:34,239 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:34,239 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:12:34,239 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:34,240 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:12:34,240 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:34,240 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:12:34,240 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:44,998 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:12:45,000 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)
-2024-10-07 09:12:45,000 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-10-07T09:12:45.000918', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:45,001 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:12:45,002 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:12:45,002 - using serial LDA version on this node
-2024-10-07 09:12:45,002 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:12:45,002 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:12:45,006 - -7.996 per-word bound, 255.3 perplexity estimate based on a held-out corpus of 1 documents with 2334 words
-2024-10-07 09:12:45,006 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:12:45,007 - topic #0 (0.333): 0.019*"’" + 0.010*"needs" + 0.006*"quality" + 0.006*"practice" + 0.006*"ensure" + 0.006*"progress" + 0.005*"Staffordshire" + 0.005*"good" + 0.005*"plans" + 0.005*"oversight"
-2024-10-07 09:12:45,007 - topic #1 (0.333): 0.016*"’" + 0.014*"needs" + 0.006*"practice" + 0.006*"progress" + 0.006*"Staffordshire" + 0.006*"health" + 0.006*"oversight" + 0.005*"quality" + 0.005*"6" + 0.005*"ensure"
-2024-10-07 09:12:45,008 - topic #2 (0.333): 0.015*"’" + 0.011*"needs" + 0.006*"oversight" + 0.006*"quality" + 0.005*"health" + 0.005*"ensure" + 0.005*"plans" + 0.005*"progress" + 0.005*"Staffordshire" + 0.004*"practice"
-2024-10-07 09:12:45,008 - topic diff=0.799545, rho=1.000000
-2024-10-07 09:12:45,008 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:12:45.008268', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:45,967 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:12:45,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:45,967 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:12:45,967 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:45,968 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:12:45,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:45,968 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:12:45,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:45,968 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:12:45,968 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:45,969 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:12:45,969 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:55,798 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:12:55,800 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
-2024-10-07 09:12:55,800 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-10-07T09:12:55.800644', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:55,801 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:12:55,801 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:12:55,802 - using serial LDA version on this node
-2024-10-07 09:12:55,802 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:12:55,802 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:12:55,806 - -7.976 per-word bound, 251.7 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
-2024-10-07 09:12:55,806 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:12:55,807 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.008*"practice" + 0.007*"needs" + 0.006*"Stockport" + 0.006*"28" + 0.006*"strong" + 0.005*"1" + 0.005*"quality" + 0.004*"leaders"
-2024-10-07 09:12:55,807 - topic #1 (0.333): 0.008*"’" + 0.008*"well" + 0.007*"Stockport" + 0.007*"practice" + 0.007*"plans" + 0.006*"needs" + 0.005*"strong" + 0.005*"risk" + 0.005*"ensure" + 0.004*"need"
-2024-10-07 09:12:55,807 - topic #2 (0.333): 0.012*"’" + 0.008*"well" + 0.007*"practice" + 0.007*"Stockport" + 0.005*"risk" + 0.005*"strong" + 0.005*"plans" + 0.005*"team" + 0.005*"needs" + 0.005*"leaders"
-2024-10-07 09:12:55,807 - topic diff=0.792620, rho=1.000000
-2024-10-07 09:12:55,808 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1060, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:12:55.808036', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:12:56,824 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:12:56,825 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:56,825 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:12:56,825 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:56,825 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:12:56,825 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:56,826 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:12:56,826 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:56,826 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:12:56,826 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:12:56,826 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:12:56,826 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:07,739 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:13:07,741 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)
-2024-10-07 09:13:07,741 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-10-07T09:13:07.741538', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:07,742 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:13:07,742 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:13:07,742 - using serial LDA version on this node
-2024-10-07 09:13:07,743 - 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
-2024-10-07 09:13:07,743 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:13:07,746 - -7.968 per-word bound, 250.4 perplexity estimate based on a held-out corpus of 1 documents with 2269 words
-2024-10-07 09:13:07,746 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:13:07,748 - topic #0 (0.333): 0.019*"’" + 0.007*"plans" + 0.007*"well" + 0.007*"leaders" + 0.006*"needs" + 0.005*"quality" + 0.005*"good" + 0.005*"on-Tees" + 0.004*"Senior" + 0.004*"Stockton"
-2024-10-07 09:13:07,748 - topic #1 (0.333): 0.020*"’" + 0.008*"plans" + 0.008*"needs" + 0.007*"leaders" + 0.006*"senior" + 0.005*"Stockton" + 0.005*"6" + 0.005*"well" + 0.005*"carers" + 0.005*"on-Tees"
-2024-10-07 09:13:07,748 - topic #2 (0.333): 0.019*"’" + 0.011*"leaders" + 0.008*"plans" + 0.007*"on-Tees" + 0.007*"quality" + 0.007*"Stockton" + 0.007*"well" + 0.006*"good" + 0.006*"senior" + 0.006*"needs"
-2024-10-07 09:13:07,748 - topic diff=0.771517, rho=1.000000
-2024-10-07 09:13:07,748 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1044, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:13:07.748936', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:08,613 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:13:08,613 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:08,614 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:13:08,614 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:08,614 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:13:08,614 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:08,614 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:13:08,614 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:08,615 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:13:08,615 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:08,615 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:13:08,615 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:19,539 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:13:19,541 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)
-2024-10-07 09:13:19,541 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-10-07T09:13:19.541349', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:19,542 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:13:19,542 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:13:19,542 - using serial LDA version on this node
-2024-10-07 09:13:19,543 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:13:19,543 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:13:19,546 - -7.897 per-word bound, 238.4 perplexity estimate based on a held-out corpus of 1 documents with 2165 words
-2024-10-07 09:13:19,546 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:13:19,547 - topic #0 (0.333): 0.020*"’" + 0.008*"needs" + 0.008*"plans" + 0.007*"Stoke" + 0.007*"well" + 0.006*"on-Trent" + 0.006*"ensure" + 0.006*"However" + 0.005*"progress" + 0.005*"quality"
-2024-10-07 09:13:19,548 - topic #1 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"Stoke" + 0.006*"However" + 0.006*"on-Trent" + 0.005*"plans" + 0.005*"well" + 0.005*"need" + 0.004*"protection" + 0.004*"timely"
-2024-10-07 09:13:19,548 - topic #2 (0.333): 0.018*"’" + 0.009*"needs" + 0.008*"on-Trent" + 0.007*"well" + 0.007*"protection" + 0.007*"However" + 0.006*"Stoke" + 0.006*"ensure" + 0.006*"leaders" + 0.005*"plans"
-2024-10-07 09:13:19,548 - topic diff=0.786013, rho=1.000000
-2024-10-07 09:13:19,548 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=986, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:13:19.548629', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:20,458 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:13:20,458 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:20,458 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:13:20,458 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:20,459 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:13:20,459 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:20,459 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:13:20,459 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:20,459 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:13:20,459 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:20,459 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:13:20,459 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:33,440 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:13:33,442 - built Dictionary<1126 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2544 corpus positions)
-2024-10-07 09:13:33,442 - Dictionary lifecycle event {'msg': 'built Dictionary<1126 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2544 corpus positions)', 'datetime': '2024-10-07T09:13:33.442939', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:33,444 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:13:33,444 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:13:33,444 - using serial LDA version on this node
-2024-10-07 09:13:33,444 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:13:33,444 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:13:33,448 - -8.014 per-word bound, 258.5 perplexity estimate based on a held-out corpus of 1 documents with 2544 words
-2024-10-07 09:13:33,448 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:13:33,450 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"well" + 0.005*"Suffolk" + 0.004*"parents" + 0.004*"Council" + 0.004*"practice" + 0.003*"3" + 0.003*"good" + 0.003*"7"
-2024-10-07 09:13:33,450 - topic #1 (0.333): 0.026*"’" + 0.012*"needs" + 0.011*"Suffolk" + 0.009*"well" + 0.006*"Council" + 0.005*"protection" + 0.005*"practice" + 0.005*"County" + 0.005*"3" + 0.005*"June"
-2024-10-07 09:13:33,450 - topic #2 (0.333): 0.019*"’" + 0.011*"Suffolk" + 0.009*"needs" + 0.008*"well" + 0.005*"2024" + 0.005*"parents" + 0.005*"practice" + 0.005*"risks" + 0.005*"protection" + 0.005*"7"
-2024-10-07 09:13:33,450 - topic diff=0.825744, rho=1.000000
-2024-10-07 09:13:33,450 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1126, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:13:33.450659', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:35,423 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:13:35,423 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:35,423 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:13:35,424 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:35,424 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:13:35,424 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:35,424 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:13:35,424 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:35,424 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:13:35,425 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:35,425 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:13:35,425 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:46,446 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:13:46,448 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)
-2024-10-07 09:13:46,448 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-10-07T09:13:46.448280', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:46,449 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:13:46,449 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:13:46,449 - using serial LDA version on this node
-2024-10-07 09:13:46,450 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:13:46,450 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:13:46,453 - -8.051 per-word bound, 265.3 perplexity estimate based on a held-out corpus of 1 documents with 2409 words
-2024-10-07 09:13:46,453 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:13:46,455 - topic #0 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"quality" + 0.006*"Sunderland" + 0.006*"well" + 0.005*"council" + 0.004*"protection" + 0.004*"experienced" + 0.004*"robust" + 0.004*"parents"
-2024-10-07 09:13:46,455 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"practice" + 0.005*"quality" + 0.005*"Sunderland" + 0.004*"training" + 0.004*"experienced" + 0.004*"cared" + 0.004*"highly"
-2024-10-07 09:13:46,455 - topic #2 (0.333): 0.018*"’" + 0.008*"well" + 0.008*"quality" + 0.006*"Sunderland" + 0.006*"needs" + 0.006*"experienced" + 0.005*"TfC" + 0.005*"good" + 0.005*"parents" + 0.005*"council"
-2024-10-07 09:13:46,455 - topic diff=0.783315, rho=1.000000
-2024-10-07 09:13:46,455 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1128, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:13:46.455980', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:47,565 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:13:47,565 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:47,566 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:13:47,566 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:47,566 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:13:47,566 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:47,566 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:13:47,566 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:47,567 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:13:47,567 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:47,567 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:13:47,567 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:57,670 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:13:57,672 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)
-2024-10-07 09:13:57,673 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-10-07T09:13:57.673032', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:57,673 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:13:57,674 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:13:57,674 - using serial LDA version on this node
-2024-10-07 09:13:57,674 - 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
-2024-10-07 09:13:57,674 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:13:57,678 - -7.964 per-word bound, 249.7 perplexity estimate based on a held-out corpus of 1 documents with 2111 words
-2024-10-07 09:13:57,678 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:13:57,679 - topic #0 (0.333): 0.016*"’" + 0.012*"well" + 0.010*"needs" + 0.008*"practice" + 0.007*"progress" + 0.005*"plans" + 0.005*"However" + 0.005*"good" + 0.005*"effective" + 0.005*"Surrey"
-2024-10-07 09:13:57,679 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"practice" + 0.005*"quality" + 0.005*"carers" + 0.005*"17" + 0.005*"good" + 0.005*"effective" + 0.004*"progress"
-2024-10-07 09:13:57,680 - topic #2 (0.333): 0.011*"’" + 0.010*"needs" + 0.008*"progress" + 0.007*"well" + 0.007*"practice" + 0.005*"plans" + 0.005*"quality" + 0.005*"17" + 0.005*"effective" + 0.005*"carers"
-2024-10-07 09:13:57,680 - topic diff=0.764727, rho=1.000000
-2024-10-07 09:13:57,680 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1016, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:13:57.680412', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:13:58,599 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:13:58,599 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:58,599 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:13:58,600 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:58,600 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:13:58,600 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:58,600 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:13:58,600 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:58,601 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:13:58,601 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:13:58,601 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:13:58,601 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:09,393 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:14:09,395 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)
-2024-10-07 09:14:09,395 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-10-07T09:14:09.395659', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:09,396 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:14:09,396 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:14:09,396 - using serial LDA version on this node
-2024-10-07 09:14:09,397 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:14:09,397 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:14:09,400 - -7.832 per-word bound, 227.9 perplexity estimate based on a held-out corpus of 1 documents with 2229 words
-2024-10-07 09:14:09,400 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:14:09,402 - topic #0 (0.333): 0.027*"’" + 0.011*"needs" + 0.010*"Swindon" + 0.009*"need" + 0.008*"well" + 0.007*"always" + 0.006*"plans" + 0.006*"lack" + 0.005*"health" + 0.005*"effective"
-2024-10-07 09:14:09,402 - topic #1 (0.333): 0.018*"’" + 0.017*"needs" + 0.009*"well" + 0.008*"Swindon" + 0.007*"always" + 0.007*"need" + 0.006*"plans" + 0.006*"impact" + 0.006*"Council" + 0.005*"effective"
-2024-10-07 09:14:09,402 - topic #2 (0.333): 0.020*"’" + 0.010*"needs" + 0.008*"need" + 0.008*"Swindon" + 0.007*"well" + 0.007*"plans" + 0.006*"impact" + 0.005*"July" + 0.005*"effective" + 0.005*"always"
-2024-10-07 09:14:09,402 - topic diff=0.825442, rho=1.000000
-2024-10-07 09:14:09,402 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=951, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:14:09.402555', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:10,312 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:14:10,312 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:10,312 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:14:10,312 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:10,312 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:14:10,312 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:10,313 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:14:10,313 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:10,313 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:14:10,313 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:10,313 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:14:10,313 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:22,057 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:14:22,059 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)
-2024-10-07 09:14:22,060 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-10-07T09:14:22.060065', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:22,061 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:14:22,061 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:14:22,061 - using serial LDA version on this node
-2024-10-07 09:14:22,061 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:14:22,061 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:14:22,065 - -7.941 per-word bound, 245.7 perplexity estimate based on a held-out corpus of 1 documents with 2491 words
-2024-10-07 09:14:22,065 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:14:22,066 - topic #0 (0.333): 0.009*"’" + 0.006*"needs" + 0.005*"risk" + 0.005*"4" + 0.004*"practice" + 0.004*"quality" + 0.004*"response" + 0.004*"experienced" + 0.004*"plans" + 0.004*"impact"
-2024-10-07 09:14:22,067 - topic #1 (0.333): 0.018*"’" + 0.008*"needs" + 0.006*"Tameside" + 0.006*"practice" + 0.006*"impact" + 0.006*"risk" + 0.005*"2023" + 0.005*"planning" + 0.005*"understand" + 0.005*"quality"
-2024-10-07 09:14:22,067 - topic #2 (0.333): 0.018*"’" + 0.011*"needs" + 0.007*"impact" + 0.007*"risk" + 0.006*"quality" + 0.006*"experienced" + 0.005*"response" + 0.005*"2023" + 0.005*"15" + 0.005*"experiences"
-2024-10-07 09:14:22,067 - topic diff=0.834386, rho=1.000000
-2024-10-07 09:14:22,067 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:14:22.067453', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:22,995 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:14:22,995 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:22,995 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:14:22,995 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:22,995 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:14:22,995 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:22,996 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:14:22,996 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:22,996 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:14:22,996 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:22,996 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:14:22,996 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:35,147 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:14:35,149 - built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)
-2024-10-07 09:14:35,149 - Dictionary lifecycle event {'msg': "built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)", 'datetime': '2024-10-07T09:14:35.149696', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:35,150 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:14:35,150 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:14:35,151 - using serial LDA version on this node
-2024-10-07 09:14:35,151 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:14:35,151 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:14:35,155 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 2452 words
-2024-10-07 09:14:35,155 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:14:35,156 - topic #0 (0.333): 0.023*"’" + 0.013*"needs" + 0.008*"Wrekin" + 0.006*"effective" + 0.006*"Telford" + 0.006*"well" + 0.006*"plans" + 0.006*"benefit" + 0.005*"Family" + 0.005*"provide"
-2024-10-07 09:14:35,156 - topic #1 (0.333): 0.024*"’" + 0.010*"needs" + 0.008*"Telford" + 0.007*"Wrekin" + 0.006*"Family" + 0.006*"benefit" + 0.005*"effective" + 0.005*"well" + 0.005*"plans" + 0.005*"3"
-2024-10-07 09:14:35,157 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.009*"Telford" + 0.007*"Wrekin" + 0.007*"benefit" + 0.006*"well" + 0.005*"plans" + 0.005*"3" + 0.004*"Family" + 0.004*"PAs"
-2024-10-07 09:14:35,157 - topic diff=0.818801, rho=1.000000
-2024-10-07 09:14:35,157 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1077, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:14:35.157239', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:36,175 - Inspection date 2024-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:14:36,175 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:36,175 - Inspection date 2024-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:14:36,175 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:36,175 - Inspection date 2024-04-29 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:14:36,175 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:36,176 - Inspection date 2024-04-29 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:14:36,176 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:36,176 - Inspection date 2024-04-29 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:14:36,176 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:36,176 - Inspection date 2024-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:14:36,176 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:46,559 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:14:46,561 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)
-2024-10-07 09:14:46,561 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-10-07T09:14:46.561844', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:46,562 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:14:46,562 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:14:46,563 - using serial LDA version on this node
-2024-10-07 09:14:46,563 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:14:46,563 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:14:46,567 - -8.140 per-word bound, 282.1 perplexity estimate based on a held-out corpus of 1 documents with 2160 words
-2024-10-07 09:14:46,567 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:14:46,568 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"carers" + 0.006*"need" + 0.005*"Thurrock" + 0.004*"practice" + 0.004*"impact" + 0.004*"leaders" + 0.004*"vulnerable" + 0.004*"protection"
-2024-10-07 09:14:46,568 - topic #1 (0.333): 0.007*"’" + 0.006*"well" + 0.005*"carers" + 0.005*"ensure" + 0.004*"need" + 0.004*"needs" + 0.004*"effective" + 0.003*"leaders" + 0.003*"practice" + 0.003*"parents"
-2024-10-07 09:14:46,569 - topic #2 (0.333): 0.015*"’" + 0.010*"well" + 0.005*"needs" + 0.004*"carers" + 0.004*"practice" + 0.004*"need" + 0.004*"ensure" + 0.004*"leaders" + 0.004*"effective" + 0.003*"protection"
-2024-10-07 09:14:46,569 - topic diff=0.730897, rho=1.000000
-2024-10-07 09:14:46,569 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1138, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:14:46.569362', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:48,233 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:14:48,234 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:48,234 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:14:48,234 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:48,234 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:14:48,234 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:48,235 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:14:48,235 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:48,235 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:14:48,235 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:48,235 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:14:48,235 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:58,027 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:14:58,029 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)
-2024-10-07 09:14:58,029 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-10-07T09:14:58.029350', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:58,030 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:14:58,030 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:14:58,030 - using serial LDA version on this node
-2024-10-07 09:14:58,031 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:14:58,031 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:14:58,034 - -8.041 per-word bound, 263.4 perplexity estimate based on a held-out corpus of 1 documents with 2065 words
-2024-10-07 09:14:58,034 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:14:58,036 - topic #0 (0.333): 0.020*"’" + 0.011*"well" + 0.007*"Torbay" + 0.007*"needs" + 0.007*"good" + 0.005*"team" + 0.005*"timely" + 0.005*"effective" + 0.005*"plans" + 0.005*"1"
-2024-10-07 09:14:58,036 - topic #1 (0.333): 0.017*"’" + 0.008*"Torbay" + 0.007*"well" + 0.006*"good" + 0.005*"effective" + 0.005*"21" + 0.005*"needs" + 0.004*"agencies" + 0.004*"April" + 0.004*"March"
-2024-10-07 09:14:58,036 - topic #2 (0.333): 0.012*"’" + 0.009*"well" + 0.007*"Torbay" + 0.006*"needs" + 0.004*"quality" + 0.004*"effective" + 0.004*"progress" + 0.004*"good" + 0.004*"2022" + 0.004*"21"
-2024-10-07 09:14:58,036 - topic diff=0.753651, rho=1.000000
-2024-10-07 09:14:58,036 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1054, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:14:58.036602', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:14:58,974 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:14:58,974 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:58,974 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:14:58,974 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:58,974 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:14:58,975 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:58,975 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:14:58,975 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:58,975 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:14:58,975 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:14:58,975 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:14:58,975 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:11,233 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:15:11,235 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)
-2024-10-07 09:15:11,236 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-10-07T09:15:11.236007', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:11,237 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:15:11,237 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:15:11,237 - using serial LDA version on this node
-2024-10-07 09:15:11,237 - 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
-2024-10-07 09:15:11,237 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:15:11,241 - -7.906 per-word bound, 239.9 perplexity estimate based on a held-out corpus of 1 documents with 2448 words
-2024-10-07 09:15:11,241 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:15:11,242 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"plans" + 0.007*"well" + 0.007*"Trafford" + 0.006*"quality" + 0.006*"practice" + 0.005*"2" + 0.004*"team" + 0.004*"November"
-2024-10-07 09:15:11,242 - topic #1 (0.333): 0.019*"’" + 0.009*"Trafford" + 0.008*"needs" + 0.007*"leaders" + 0.007*"quality" + 0.006*"well" + 0.006*"plans" + 0.005*"practice" + 0.005*"placed" + 0.005*"ensure"
-2024-10-07 09:15:11,243 - topic #2 (0.333): 0.016*"’" + 0.011*"needs" + 0.008*"Trafford" + 0.007*"well" + 0.007*"plans" + 0.006*"quality" + 0.006*"impact" + 0.005*"leaders" + 0.005*"team" + 0.005*"placed"
-2024-10-07 09:15:11,243 - topic diff=0.819286, rho=1.000000
-2024-10-07 09:15:11,243 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:15:11.243210', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:12,293 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:15:12,293 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:12,294 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:15:12,294 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:12,294 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:15:12,294 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:12,294 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:15:12,294 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:12,294 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:15:12,295 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:12,295 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:15:12,295 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:24,077 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:15:24,081 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions)
-2024-10-07 09:15:24,081 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-10-07T09:15:24.081635', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:24,083 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:15:24,083 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:15:24,084 - using serial LDA version on this node
-2024-10-07 09:15:24,084 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:15:24,084 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:15:24,091 - -8.048 per-word bound, 264.6 perplexity estimate based on a held-out corpus of 1 documents with 2626 words
-2024-10-07 09:15:24,091 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:15:24,094 - topic #0 (0.333): 0.020*"’" + 0.007*"leaders" + 0.006*"needs" + 0.005*"well" + 0.005*"Walsall" + 0.004*"practice" + 0.004*"risks" + 0.004*"15" + 0.004*"oversight" + 0.004*"supported"
-2024-10-07 09:15:24,094 - topic #1 (0.333): 0.024*"’" + 0.008*"leaders" + 0.006*"Walsall" + 0.006*"needs" + 0.006*"well" + 0.006*"information" + 0.005*"4" + 0.005*"good" + 0.005*"oversight" + 0.005*"2021"
-2024-10-07 09:15:24,094 - topic #2 (0.333): 0.017*"’" + 0.007*"needs" + 0.005*"leaders" + 0.005*"well" + 0.005*"4" + 0.004*"Senior" + 0.004*"Walsall" + 0.004*"oversight" + 0.004*"information" + 0.004*"positive"
-2024-10-07 09:15:24,095 - topic diff=0.822320, rho=1.000000
-2024-10-07 09:15:24,096 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1162, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:15:24.096013', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:25,027 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:15:25,027 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:25,027 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:15:25,027 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:25,028 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:15:25,028 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:25,028 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:15:25,028 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:25,028 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:15:25,028 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:25,029 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:15:25,029 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:39,220 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:15:39,222 - built Dictionary<1158 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2700 corpus positions)
-2024-10-07 09:15:39,222 - Dictionary lifecycle event {'msg': 'built Dictionary<1158 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2700 corpus positions)', 'datetime': '2024-10-07T09:15:39.222937', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:39,224 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:15:39,224 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:15:39,224 - using serial LDA version on this node
-2024-10-07 09:15:39,224 - 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
-2024-10-07 09:15:39,224 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:15:39,228 - -8.022 per-word bound, 259.9 perplexity estimate based on a held-out corpus of 1 documents with 2700 words
-2024-10-07 09:15:39,228 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:15:39,230 - topic #0 (0.333): 0.020*"’" + 0.007*"needs" + 0.007*"Warrington" + 0.007*"leaders" + 0.006*"well" + 0.006*"2024" + 0.006*"effective" + 0.006*"practice" + 0.006*"experiences" + 0.005*"14"
-2024-10-07 09:15:39,230 - topic #1 (0.333): 0.021*"’" + 0.009*"needs" + 0.008*"experiences" + 0.007*"effective" + 0.006*"Warrington" + 0.005*"well" + 0.005*"leaders" + 0.005*"10" + 0.005*"14" + 0.005*"practice"
-2024-10-07 09:15:39,230 - topic #2 (0.333): 0.014*"’" + 0.007*"Warrington" + 0.005*"experiences" + 0.004*"leaders" + 0.004*"effective" + 0.004*"plans" + 0.004*"carers" + 0.004*"practice" + 0.004*"needs" + 0.004*"10"
-2024-10-07 09:15:39,230 - topic diff=0.819687, rho=1.000000
-2024-10-07 09:15:39,230 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1158, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:15:39.230887', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:40,167 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:15:40,167 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:40,168 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:15:40,168 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:40,168 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:15:40,168 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:40,168 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:15:40,168 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:40,169 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:15:40,169 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:40,169 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:15:40,169 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:49,953 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:15:49,955 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)
-2024-10-07 09:15:49,955 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-10-07T09:15:49.955211', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:49,956 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:15:49,956 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:15:49,956 - using serial LDA version on this node
-2024-10-07 09:15:49,956 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:15:49,957 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:15:49,960 - -8.003 per-word bound, 256.6 perplexity estimate based on a held-out corpus of 1 documents with 2113 words
-2024-10-07 09:15:49,960 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:15:49,962 - topic #0 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"Warwickshire" + 0.006*"needs" + 0.005*"progress" + 0.005*"plans" + 0.005*"supported" + 0.004*"clear" + 0.004*"22" + 0.004*"good"
-2024-10-07 09:15:49,962 - topic #1 (0.333): 0.010*"’" + 0.006*"plans" + 0.006*"Warwickshire" + 0.006*"needs" + 0.006*"practice" + 0.005*"well" + 0.004*"3" + 0.004*"carers" + 0.004*"good" + 0.004*"agencies"
-2024-10-07 09:15:49,962 - topic #2 (0.333): 0.012*"’" + 0.007*"needs" + 0.007*"plans" + 0.007*"well" + 0.005*"Warwickshire" + 0.005*"carers" + 0.005*"good" + 0.005*"3" + 0.005*"practice" + 0.004*"information"
-2024-10-07 09:15:49,962 - topic diff=0.754255, rho=1.000000
-2024-10-07 09:15:49,962 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1040, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:15:49.962692', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:15:50,884 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:15:50,884 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:50,884 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:15:50,884 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:50,885 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:15:50,885 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:50,885 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:15:50,885 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:50,885 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:15:50,885 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:15:50,886 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:15:50,886 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:00,591 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:16:00,593 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)
-2024-10-07 09:16:00,593 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-10-07T09:16:00.593280', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:00,594 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:16:00,594 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:16:00,594 - using serial LDA version on this node
-2024-10-07 09:16:00,595 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:16:00,595 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:16:00,598 - -8.109 per-word bound, 276.2 perplexity estimate based on a held-out corpus of 1 documents with 2146 words
-2024-10-07 09:16:00,598 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:16:00,600 - topic #0 (0.333): 0.012*"’" + 0.006*"West" + 0.005*"Berkshire" + 0.005*"plans" + 0.005*"well" + 0.004*"needs" + 0.004*"early" + 0.004*"need" + 0.004*"18" + 0.003*"ensure"
-2024-10-07 09:16:00,600 - topic #1 (0.333): 0.014*"’" + 0.006*"well" + 0.006*"West" + 0.006*"Berkshire" + 0.004*"agency" + 0.004*"18" + 0.004*"needs" + 0.004*"plans" + 0.004*"education" + 0.004*"2022"
-2024-10-07 09:16:00,600 - topic #2 (0.333): 0.017*"’" + 0.007*"Berkshire" + 0.007*"West" + 0.006*"well" + 0.005*"need" + 0.004*"working" + 0.004*"14" + 0.004*"needs" + 0.004*"strong" + 0.004*"early"
-2024-10-07 09:16:00,600 - topic diff=0.712706, rho=1.000000
-2024-10-07 09:16:00,600 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:16:00.600904', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:01,444 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:16:01,444 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:01,444 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:16:01,445 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:01,445 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:16:01,445 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:01,445 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:16:01,446 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:01,446 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:16:01,446 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:01,446 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:16:01,446 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:11,930 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:16:11,932 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)
-2024-10-07 09:16:11,933 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-10-07T09:16:11.932972', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:11,933 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:16:11,934 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:16:11,934 - using serial LDA version on this node
-2024-10-07 09:16:11,934 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:16:11,934 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:16:11,938 - -8.043 per-word bound, 263.8 perplexity estimate based on a held-out corpus of 1 documents with 2224 words
-2024-10-07 09:16:11,938 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:16:11,939 - topic #0 (0.333): 0.017*"’" + 0.010*"Northamptonshire" + 0.008*"West" + 0.007*"quality" + 0.006*"practice" + 0.006*"well" + 0.005*"impact" + 0.005*"plans" + 0.005*"need" + 0.005*"needs"
-2024-10-07 09:16:11,940 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"quality" + 0.006*"West" + 0.006*"Northamptonshire" + 0.006*"practice" + 0.005*"needs" + 0.005*"2022" + 0.005*"14" + 0.005*"NCT"
-2024-10-07 09:16:11,940 - topic #2 (0.333): 0.014*"’" + 0.008*"Northamptonshire" + 0.006*"well" + 0.005*"However" + 0.005*"quality" + 0.005*"needs" + 0.004*"West" + 0.004*"experiences" + 0.004*"NCT" + 0.004*"need"
-2024-10-07 09:16:11,940 - topic diff=0.758006, rho=1.000000
-2024-10-07 09:16:11,940 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1087, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:16:11.940513', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:12,781 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:16:12,781 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:12,781 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:16:12,782 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:12,782 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:16:12,782 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:12,782 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:16:12,782 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:12,782 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:16:12,782 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:12,783 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:16:12,783 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:25,808 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:16:25,810 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
-2024-10-07 09:16:25,811 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-10-07T09:16:25.810972', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:25,812 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:16:25,812 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:16:25,812 - using serial LDA version on this node
-2024-10-07 09:16:25,812 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:16:25,813 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:16:25,817 - -8.124 per-word bound, 279.0 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
-2024-10-07 09:16:25,817 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:16:25,818 - topic #0 (0.333): 0.018*"’" + 0.007*"plans" + 0.007*"well" + 0.006*"needs" + 0.005*"Sussex" + 0.005*"West" + 0.005*"number" + 0.004*"13" + 0.004*"quality" + 0.004*"supported"
-2024-10-07 09:16:25,818 - topic #1 (0.333): 0.013*"’" + 0.006*"plans" + 0.006*"well" + 0.005*"West" + 0.005*"13" + 0.005*"Sussex" + 0.005*"quality" + 0.004*"health" + 0.004*"needs" + 0.004*"practice"
-2024-10-07 09:16:25,818 - topic #2 (0.333): 0.009*"’" + 0.006*"needs" + 0.005*"well" + 0.005*"plans" + 0.005*"supported" + 0.004*"Sussex" + 0.004*"practice" + 0.004*"13" + 0.004*"number" + 0.004*"West"
-2024-10-07 09:16:25,819 - topic diff=0.808747, rho=1.000000
-2024-10-07 09:16:25,819 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1233, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:16:25.819249', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:26,744 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:16:26,744 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:26,745 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:16:26,745 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:26,745 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:16:26,745 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:26,745 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:16:26,745 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:26,746 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:16:26,746 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:26,746 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:16:26,746 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:39,462 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:16:39,465 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)
-2024-10-07 09:16:39,465 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)", 'datetime': '2024-10-07T09:16:39.465773', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:39,467 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:16:39,467 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:16:39,468 - using serial LDA version on this node
-2024-10-07 09:16:39,468 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:16:39,468 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:16:39,475 - -7.965 per-word bound, 249.9 perplexity estimate based on a held-out corpus of 1 documents with 2451 words
-2024-10-07 09:16:39,475 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:16:39,477 - topic #0 (0.333): 0.011*"’" + 0.008*"plans" + 0.006*"Westmorland" + 0.006*"need" + 0.006*"Furness" + 0.006*"needs" + 0.006*"appropriate" + 0.005*"quality" + 0.005*"progress" + 0.004*"protection"
-2024-10-07 09:16:39,477 - topic #1 (0.333): 0.014*"’" + 0.006*"plans" + 0.005*"needs" + 0.005*"Furness" + 0.005*"need" + 0.005*"Westmorland" + 0.005*"22" + 0.004*"appropriate" + 0.004*"well" + 0.004*"April"
-2024-10-07 09:16:39,478 - topic #2 (0.333): 0.013*"’" + 0.008*"plans" + 0.008*"needs" + 0.007*"Westmorland" + 0.007*"Furness" + 0.006*"appropriate" + 0.006*"need" + 0.006*"quality" + 0.006*"protection" + 0.005*"progress"
-2024-10-07 09:16:39,478 - topic diff=0.804874, rho=1.000000
-2024-10-07 09:16:39,478 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:16:39.478426', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:40,507 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:16:40,507 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:40,507 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:16:40,507 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:40,508 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:16:40,508 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:40,508 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:16:40,508 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:40,508 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:16:40,508 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:40,509 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:16:40,509 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:50,932 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:16:50,934 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)
-2024-10-07 09:16:50,934 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-10-07T09:16:50.934221', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:50,935 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:16:50,935 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:16:50,935 - using serial LDA version on this node
-2024-10-07 09:16:50,936 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:16:50,936 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:16:50,939 - -7.961 per-word bound, 249.2 perplexity estimate based on a held-out corpus of 1 documents with 2416 words
-2024-10-07 09:16:50,939 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:16:50,941 - topic #0 (0.333): 0.013*"’" + 0.008*"practice" + 0.007*"plans" + 0.007*"May" + 0.006*"quality" + 0.006*"needs" + 0.005*"Wigan" + 0.005*"leaders" + 0.005*"appropriate" + 0.004*"increased"
-2024-10-07 09:16:50,941 - topic #1 (0.333): 0.010*"’" + 0.007*"quality" + 0.006*"May" + 0.005*"Wigan" + 0.005*"needs" + 0.005*"practice" + 0.005*"plans" + 0.005*"20" + 0.005*"appropriate" + 0.005*"leaders"
-2024-10-07 09:16:50,941 - topic #2 (0.333): 0.013*"’" + 0.009*"May" + 0.007*"Wigan" + 0.007*"plans" + 0.006*"needs" + 0.006*"practice" + 0.006*"appropriate" + 0.005*"timely" + 0.005*"9" + 0.004*"2022"
-2024-10-07 09:16:50,941 - topic diff=0.792379, rho=1.000000
-2024-10-07 09:16:50,941 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:16:50.941729', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:16:51,887 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:16:51,887 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:51,888 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:16:51,888 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:51,888 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:16:51,888 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:51,888 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:16:51,888 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:51,889 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:16:51,889 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:16:51,889 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:16:51,889 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:02,521 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:17:02,523 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)
-2024-10-07 09:17:02,523 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-10-07T09:17:02.523739', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:02,524 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:17:02,524 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:17:02,525 - using serial LDA version on this node
-2024-10-07 09:17:02,525 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:17:02,525 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:17:02,529 - -7.959 per-word bound, 248.8 perplexity estimate based on a held-out corpus of 1 documents with 2600 words
-2024-10-07 09:17:02,529 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:17:02,530 - topic #0 (0.333): 0.015*"’" + 0.011*"well" + 0.007*"needs" + 0.006*"progress" + 0.006*"risk" + 0.005*"supported" + 0.005*"plans" + 0.005*"ensure" + 0.005*"parents" + 0.005*"need"
-2024-10-07 09:17:02,530 - topic #1 (0.333): 0.012*"’" + 0.010*"well" + 0.007*"Wiltshire" + 0.007*"needs" + 0.006*"parents" + 0.006*"supported" + 0.006*"need" + 0.005*"quality" + 0.005*"ensure" + 0.005*"plans"
-2024-10-07 09:17:02,531 - topic #2 (0.333): 0.017*"’" + 0.012*"well" + 0.008*"need" + 0.008*"needs" + 0.007*"including" + 0.006*"Wiltshire" + 0.006*"progress" + 0.006*"risk" + 0.005*"parents" + 0.005*"quality"
-2024-10-07 09:17:02,531 - topic diff=0.833399, rho=1.000000
-2024-10-07 09:17:02,531 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1090, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:17:02.531539', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:03,410 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:17:03,411 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:03,411 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:17:03,411 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:03,411 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:17:03,411 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:03,411 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:17:03,412 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:03,412 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:17:03,412 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:03,412 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:17:03,412 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:14,988 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:17:14,990 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
-2024-10-07 09:17:14,990 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-10-07T09:17:14.990275', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:14,991 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:17:14,991 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:17:14,991 - using serial LDA version on this node
-2024-10-07 09:17:14,991 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:17:14,992 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:17:14,995 - -7.901 per-word bound, 239.0 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
-2024-10-07 09:17:14,995 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:17:14,997 - topic #0 (0.333): 0.013*"’" + 0.010*"needs" + 0.009*"Wirral" + 0.008*"plans" + 0.007*"well" + 0.007*"ensure" + 0.006*"practice" + 0.005*"number" + 0.005*"good" + 0.005*"18"
-2024-10-07 09:17:14,998 - topic #1 (0.333): 0.008*"’" + 0.007*"needs" + 0.006*"practice" + 0.005*"number" + 0.005*"Wirral" + 0.005*"small" + 0.004*"29" + 0.004*"response" + 0.004*"2023" + 0.004*"18"
-2024-10-07 09:17:14,998 - topic #2 (0.333): 0.010*"’" + 0.010*"needs" + 0.009*"ensure" + 0.007*"Wirral" + 0.007*"plans" + 0.006*"practice" + 0.005*"September" + 0.005*"well" + 0.005*"appropriate" + 0.005*"response"
-2024-10-07 09:17:14,998 - topic diff=0.808210, rho=1.000000
-2024-10-07 09:17:14,998 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:17:14.998494', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:16,142 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:17:16,142 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:16,142 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:17:16,142 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:16,143 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:17:16,143 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:16,143 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:17:16,143 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:16,143 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:17:16,143 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:16,143 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:17:16,143 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:27,535 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:17:27,537 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)
-2024-10-07 09:17:27,537 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-10-07T09:17:27.537217', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:27,538 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:17:27,538 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:17:27,538 - using serial LDA version on this node
-2024-10-07 09:17:27,538 - 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
-2024-10-07 09:17:27,539 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:17:27,542 - -8.059 per-word bound, 266.6 perplexity estimate based on a held-out corpus of 1 documents with 2214 words
-2024-10-07 09:17:27,542 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:17:27,544 - topic #0 (0.333): 0.011*"’" + 0.006*"needs" + 0.005*"effective" + 0.005*"progress" + 0.005*"6" + 0.005*"plans" + 0.004*"appropriate" + 0.004*"17" + 0.004*"well" + 0.004*"provided"
-2024-10-07 09:17:27,544 - topic #1 (0.333): 0.015*"’" + 0.009*"plans" + 0.007*"effective" + 0.006*"needs" + 0.006*"well" + 0.006*"progress" + 0.006*"17" + 0.005*"impact" + 0.005*"provided" + 0.005*"experiences"
-2024-10-07 09:17:27,544 - topic #2 (0.333): 0.010*"’" + 0.006*"effective" + 0.006*"plans" + 0.005*"progress" + 0.005*"needs" + 0.005*"well" + 0.005*"parents" + 0.005*"provided" + 0.004*"ensure" + 0.004*"Wokingham"
-2024-10-07 09:17:27,544 - topic diff=0.758640, rho=1.000000
-2024-10-07 09:17:27,544 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1096, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:17:27.544814', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:28,388 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:17:28,388 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:28,389 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:17:28,389 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:28,389 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:17:28,389 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:28,389 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:17:28,389 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:28,390 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:17:28,390 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:28,390 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:17:28,390 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:38,602 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:17:38,604 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
-2024-10-07 09:17:38,604 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-10-07T09:17:38.604381', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:38,605 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:17:38,605 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:17:38,605 - using serial LDA version on this node
-2024-10-07 09:17:38,606 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:17:38,606 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:17:38,609 - -8.047 per-word bound, 264.5 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
-2024-10-07 09:17:38,609 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:17:38,611 - topic #0 (0.333): 0.010*"’" + 0.007*"needs" + 0.005*"effective" + 0.005*"risks" + 0.005*"receive" + 0.005*"leaders" + 0.005*"strong" + 0.005*"supported" + 0.004*"plans" + 0.004*"quality"
-2024-10-07 09:17:38,611 - topic #1 (0.333): 0.017*"’" + 0.008*"needs" + 0.007*"Wolverhampton" + 0.006*"risk" + 0.006*"risks" + 0.005*"quality" + 0.005*"receive" + 0.005*"effective" + 0.005*"education" + 0.005*"plans"
-2024-10-07 09:17:38,611 - topic #2 (0.333): 0.014*"’" + 0.008*"needs" + 0.007*"effective" + 0.005*"plans" + 0.005*"Wolverhampton" + 0.005*"leaders" + 0.004*"well" + 0.004*"education" + 0.004*"practice" + 0.004*"experiences"
-2024-10-07 09:17:38,611 - topic diff=0.740666, rho=1.000000
-2024-10-07 09:17:38,611 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1095, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:17:38.611895', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:39,510 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:17:39,511 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:39,511 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:17:39,511 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:39,511 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:17:39,511 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:39,511 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:17:39,512 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:39,512 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:17:39,512 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:39,512 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:17:39,512 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:51,288 - adding document #0 to Dictionary<0 unique tokens: []>
-2024-10-07 09:17:51,292 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)
-2024-10-07 09:17:51,292 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-10-07T09:17:51.292498', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:51,294 - using symmetric alpha at 0.3333333333333333
-2024-10-07 09:17:51,294 - using symmetric eta at 0.3333333333333333
-2024-10-07 09:17:51,294 - using serial LDA version on this node
-2024-10-07 09:17:51,295 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
-2024-10-07 09:17:51,295 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
-2024-10-07 09:17:51,301 - -7.939 per-word bound, 245.3 perplexity estimate based on a held-out corpus of 1 documents with 2343 words
-2024-10-07 09:17:51,301 - PROGRESS: pass 0, at document #1/1
-2024-10-07 09:17:51,304 - topic #0 (0.333): 0.018*"’" + 0.007*"plans" + 0.006*"well" + 0.006*"Worcestershire" + 0.006*"needs" + 0.006*"progress" + 0.006*"ensure" + 0.006*"leaders" + 0.005*"PAs" + 0.005*"appropriate"
-2024-10-07 09:17:51,304 - topic #1 (0.333): 0.020*"’" + 0.010*"well" + 0.009*"needs" + 0.008*"plans" + 0.007*"Worcestershire" + 0.007*"leaders" + 0.007*"progress" + 0.006*"ensure" + 0.006*"appropriate" + 0.005*"26"
-2024-10-07 09:17:51,304 - topic #2 (0.333): 0.018*"’" + 0.008*"well" + 0.008*"plans" + 0.007*"Worcestershire" + 0.007*"leaders" + 0.006*"progress" + 0.006*"needs" + 0.005*"Senior" + 0.005*"appropriate" + 0.005*"ensure"
-2024-10-07 09:17:51,304 - topic diff=0.803975, rho=1.000000
-2024-10-07 09:17:51,304 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1041, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-07T09:17:51.304964', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
-2024-10-07 09:17:52,740 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
-2024-10-07 09:17:52,740 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:52,741 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
-2024-10-07 09:17:52,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:52,741 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
-2024-10-07 09:17:52,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:52,741 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
-2024-10-07 09:17:52,741 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:52,741 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
-2024-10-07 09:17:52,742 - Index(['judgement', 'grade'], dtype='object')
-2024-10-07 09:17:52,742 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
-2024-10-07 09:17:52,742 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:28,857 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:32:28,860 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)
+2024-10-14 08:32:28,862 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-10-14T08:32:28.860677', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:32:28,863 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:32:28,864 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:32:28,864 - using serial LDA version on this node
+2024-10-14 08:32:28,864 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:32:28,864 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:32:28,869 - -8.101 per-word bound, 274.6 perplexity estimate based on a held-out corpus of 1 documents with 2696 words
+2024-10-14 08:32:28,869 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:32:28,871 - topic #0 (0.333): 0.017*"’" + 0.006*"leaders" + 0.006*"within" + 0.005*"needs" + 0.005*"practice" + 0.004*"Barnsley" + 0.004*"11" + 0.004*"15" + 0.003*"senior" + 0.003*"understand"
+2024-10-14 08:32:28,871 - topic #1 (0.333): 0.021*"’" + 0.008*"needs" + 0.008*"leaders" + 0.007*"within" + 0.006*"Barnsley" + 0.005*"practice" + 0.005*"plans" + 0.005*"response" + 0.004*"senior" + 0.004*"quality"
+2024-10-14 08:32:28,871 - topic #2 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"leaders" + 0.007*"practice" + 0.006*"Barnsley" + 0.005*"within" + 0.004*"11" + 0.004*"plans" + 0.004*"senior" + 0.004*"15"
+2024-10-14 08:32:28,871 - topic diff=0.801349, rho=1.000000
+2024-10-14 08:32:28,872 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1216, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:32:28.872005', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:32:28,873 - Failed to import jpype dependencies. Fallback to subprocess.
+2024-10-14 08:32:28,874 - No module named 'jpype'
+2024-10-14 08:32:31,438 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:32:31,438 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:31,438 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:32:31,438 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:31,439 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:32:31,439 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:31,439 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:32:31,439 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:31,439 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:32:31,439 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:31,439 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:32:31,439 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:39,864 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:32:39,866 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)
+2024-10-14 08:32:39,867 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-10-14T08:32:39.867077', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:32:39,868 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:32:39,868 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:32:39,868 - using serial LDA version on this node
+2024-10-14 08:32:39,868 - 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
+2024-10-14 08:32:39,868 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:32:39,872 - -8.020 per-word bound, 259.6 perplexity estimate based on a held-out corpus of 1 documents with 2085 words
+2024-10-14 08:32:39,872 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:32:39,873 - topic #0 (0.333): 0.010*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"plans" + 0.005*"leaders" + 0.004*"February" + 0.004*"good" + 0.004*"practice" + 0.004*"4" + 0.004*"2022"
+2024-10-14 08:32:39,873 - topic #1 (0.333): 0.020*"’" + 0.010*"well" + 0.006*"needs" + 0.006*"plans" + 0.005*"effective" + 0.005*"practice" + 0.005*"leaders" + 0.005*"4" + 0.005*"receive" + 0.005*"Bath"
+2024-10-14 08:32:39,874 - topic #2 (0.333): 0.022*"’" + 0.009*"well" + 0.007*"practice" + 0.005*"East" + 0.005*"Somerset" + 0.005*"needs" + 0.005*"North" + 0.005*"clear" + 0.004*"plans" + 0.004*"leaders"
+2024-10-14 08:32:39,874 - topic diff=0.744666, rho=1.000000
+2024-10-14 08:32:39,874 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:32:39.874332', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:32:40,910 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:32:40,910 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:40,911 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:32:40,911 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:40,911 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:32:40,911 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:40,911 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:32:40,911 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:40,911 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:32:40,911 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:40,912 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:32:40,912 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:52,002 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:32:52,004 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)
+2024-10-14 08:32:52,005 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-10-14T08:32:52.005155', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:32:52,006 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:32:52,006 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:32:52,006 - using serial LDA version on this node
+2024-10-14 08:32:52,007 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:32:52,007 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:32:52,010 - -8.114 per-word bound, 277.1 perplexity estimate based on a held-out corpus of 1 documents with 2585 words
+2024-10-14 08:32:52,010 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:32:52,012 - topic #0 (0.333): 0.022*"’" + 0.007*"ensure" + 0.006*"well" + 0.006*"good" + 0.005*"needs" + 0.005*"plans" + 0.005*"education" + 0.005*"supported" + 0.005*"Bedford" + 0.004*"26"
+2024-10-14 08:32:52,012 - topic #1 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"Bedford" + 0.007*"well" + 0.005*"ensure" + 0.005*"progress" + 0.005*"plans" + 0.005*"supported" + 0.005*"need" + 0.004*"family"
+2024-10-14 08:32:52,012 - topic #2 (0.333): 0.019*"’" + 0.007*"ensure" + 0.006*"needs" + 0.005*"plans" + 0.004*"Borough" + 0.004*"good" + 0.004*"supported" + 0.004*"family" + 0.004*"15" + 0.004*"progress"
+2024-10-14 08:32:52,012 - topic diff=0.786860, rho=1.000000
+2024-10-14 08:32:52,012 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1202, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:32:52.012912', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:32:52,834 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:32:52,834 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:52,834 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:32:52,834 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:52,834 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:32:52,835 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:52,835 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:32:52,835 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:52,835 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:32:52,835 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:32:52,835 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:32:52,835 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:03,317 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:33:03,319 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)
+2024-10-14 08:33:03,319 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-10-14T08:33:03.319454', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:03,320 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:33:03,320 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:33:03,320 - using serial LDA version on this node
+2024-10-14 08:33:03,321 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:33:03,321 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:33:03,326 - -7.966 per-word bound, 250.1 perplexity estimate based on a held-out corpus of 1 documents with 2378 words
+2024-10-14 08:33:03,326 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:33:03,329 - topic #0 (0.333): 0.015*"’" + 0.010*"needs" + 0.009*"effective" + 0.007*"well" + 0.006*"plans" + 0.006*"trust" + 0.006*"Birmingham" + 0.005*"progress" + 0.005*"appropriate" + 0.005*"timely"
+2024-10-14 08:33:03,329 - topic #1 (0.333): 0.014*"’" + 0.008*"needs" + 0.006*"plans" + 0.006*"well" + 0.005*"impact" + 0.005*"progress" + 0.004*"Birmingham" + 0.004*"effective" + 0.004*"ensure" + 0.004*"20"
+2024-10-14 08:33:03,329 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.007*"well" + 0.006*"Birmingham" + 0.006*"3" + 0.006*"trust" + 0.006*"progress" + 0.006*"plans" + 0.005*"effective" + 0.005*"appropriate"
+2024-10-14 08:33:03,329 - topic diff=0.789973, rho=1.000000
+2024-10-14 08:33:03,329 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1065, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:33:03.329914', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:04,281 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:33:04,281 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:04,282 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:33:04,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:04,282 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:33:04,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:04,282 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:33:04,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:04,282 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:33:04,283 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:04,283 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:33:04,283 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:14,762 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:33:14,767 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)
+2024-10-14 08:33:14,768 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-10-14T08:33:14.767982', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:14,770 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:33:14,770 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:33:14,771 - using serial LDA version on this node
+2024-10-14 08:33:14,771 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:33:14,771 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:33:14,777 - -7.962 per-word bound, 249.4 perplexity estimate based on a held-out corpus of 1 documents with 2353 words
+2024-10-14 08:33:14,778 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:33:14,780 - topic #0 (0.333): 0.014*"’" + 0.009*"practice" + 0.009*"Blackburn" + 0.008*"needs" + 0.008*"quality" + 0.006*"Darwen" + 0.006*"well" + 0.006*"means" + 0.005*"February" + 0.005*"result"
+2024-10-14 08:33:14,780 - topic #1 (0.333): 0.015*"’" + 0.007*"quality" + 0.007*"impact" + 0.007*"practice" + 0.007*"Darwen" + 0.006*"well" + 0.006*"needs" + 0.005*"plans" + 0.005*"planning" + 0.005*"Blackburn"
+2024-10-14 08:33:14,781 - topic #2 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"impact" + 0.005*"Darwen" + 0.005*"well" + 0.005*"Blackburn" + 0.005*"quality" + 0.004*"4" + 0.004*"24" + 0.004*"effective"
+2024-10-14 08:33:14,781 - topic diff=0.820095, rho=1.000000
+2024-10-14 08:33:14,781 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1055, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:33:14.781670', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:15,676 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:33:15,677 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:15,677 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:33:15,677 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:15,681 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:33:15,681 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:15,681 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:33:15,681 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:15,686 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:33:15,686 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:15,686 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:33:15,687 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:26,784 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:33:26,786 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)
+2024-10-14 08:33:26,786 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-10-14T08:33:26.786415', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:26,787 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:33:26,787 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:33:26,787 - using serial LDA version on this node
+2024-10-14 08:33:26,788 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:33:26,788 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:33:26,791 - -7.924 per-word bound, 242.9 perplexity estimate based on a held-out corpus of 1 documents with 2392 words
+2024-10-14 08:33:26,791 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:33:26,793 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Blackpool" + 0.006*"progress" + 0.005*"carers" + 0.005*"quality" + 0.005*"effective" + 0.005*"supported" + 0.005*"good"
+2024-10-14 08:33:26,793 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.009*"needs" + 0.007*"Blackpool" + 0.006*"effective" + 0.006*"practice" + 0.006*"16" + 0.005*"plans" + 0.005*"supported" + 0.005*"experiences"
+2024-10-14 08:33:26,793 - topic #2 (0.333): 0.018*"’" + 0.013*"needs" + 0.009*"well" + 0.008*"Blackpool" + 0.005*"effective" + 0.005*"plans" + 0.005*"experiences" + 0.005*"practice" + 0.004*"supported" + 0.004*"including"
+2024-10-14 08:33:26,793 - topic diff=0.826983, rho=1.000000
+2024-10-14 08:33:26,793 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1037, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:33:26.793703', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:27,666 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:33:27,667 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:27,667 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:33:27,667 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:27,667 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:33:27,667 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:27,667 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:33:27,667 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:27,668 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:33:27,668 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:27,668 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:33:27,668 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:37,281 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:33:37,283 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)
+2024-10-14 08:33:37,284 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-10-14T08:33:37.284071', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:37,285 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:33:37,285 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:33:37,285 - using serial LDA version on this node
+2024-10-14 08:33:37,285 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:33:37,285 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:33:37,288 - -7.911 per-word bound, 240.7 perplexity estimate based on a held-out corpus of 1 documents with 2055 words
+2024-10-14 08:33:37,288 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:33:37,290 - topic #0 (0.333): 0.021*"’" + 0.010*"needs" + 0.010*"well" + 0.008*"Bolton" + 0.006*"effective" + 0.005*"supported" + 0.005*"plans" + 0.005*"planning" + 0.005*"appropriate" + 0.005*"timely"
+2024-10-14 08:33:37,290 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.009*"plans" + 0.008*"Bolton" + 0.008*"well" + 0.005*"need" + 0.005*"response" + 0.005*"supported" + 0.004*"strong" + 0.004*"planning"
+2024-10-14 08:33:37,290 - topic #2 (0.333): 0.019*"’" + 0.008*"plans" + 0.008*"needs" + 0.008*"Bolton" + 0.006*"need" + 0.006*"well" + 0.006*"supported" + 0.005*"15" + 0.005*"strong" + 0.005*"11"
+2024-10-14 08:33:37,290 - topic diff=0.773391, rho=1.000000
+2024-10-14 08:33:37,290 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:33:37.290589', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:38,160 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:33:38,160 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:38,161 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:33:38,161 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:38,161 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:33:38,161 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:38,161 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:33:38,161 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:38,161 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:33:38,161 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:38,162 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:33:38,162 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:46,921 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:33:46,923 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)
+2024-10-14 08:33:46,923 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-10-14T08:33:46.923205', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:46,924 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:33:46,924 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:33:46,924 - using serial LDA version on this node
+2024-10-14 08:33:46,924 - 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
+2024-10-14 08:33:46,924 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:33:46,928 - -8.032 per-word bound, 261.7 perplexity estimate based on a held-out corpus of 1 documents with 2004 words
+2024-10-14 08:33:46,928 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:33:46,929 - topic #0 (0.333): 0.012*"’" + 0.005*"quality" + 0.005*"progress" + 0.005*"practice" + 0.004*"time" + 0.004*"impact" + 0.004*"6" + 0.004*"positive" + 0.004*"Poole" + 0.004*"17"
+2024-10-14 08:33:46,929 - topic #1 (0.333): 0.022*"’" + 0.007*"practice" + 0.006*"quality" + 0.005*"progress" + 0.005*"Poole" + 0.005*"time" + 0.005*"many" + 0.005*"risk" + 0.005*"Bournemouth" + 0.005*"impact"
+2024-10-14 08:33:46,929 - topic #2 (0.333): 0.016*"’" + 0.007*"quality" + 0.005*"Christchurch" + 0.005*"17" + 0.005*"practice" + 0.005*"risk" + 0.005*"progress" + 0.005*"6" + 0.004*"Bournemouth" + 0.004*"2021"
+2024-10-14 08:33:46,930 - topic diff=0.763150, rho=1.000000
+2024-10-14 08:33:46,930 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1035, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:33:46.930173', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:49,017 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:33:49,018 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:49,018 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:33:49,018 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:49,018 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:33:49,018 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:49,018 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:33:49,018 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:49,018 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:33:49,018 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:49,019 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:33:49,019 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:57,817 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:33:57,819 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)
+2024-10-14 08:33:57,819 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-10-14T08:33:57.819872', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:57,820 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:33:57,820 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:33:57,821 - using serial LDA version on this node
+2024-10-14 08:33:57,821 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:33:57,821 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:33:57,824 - -7.855 per-word bound, 231.5 perplexity estimate based on a held-out corpus of 1 documents with 1846 words
+2024-10-14 08:33:57,824 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:33:57,825 - topic #0 (0.333): 0.019*"’" + 0.007*"needs" + 0.007*"Bracknell" + 0.006*"Forest" + 0.006*"good" + 0.006*"risk" + 0.006*"quality" + 0.005*"effective" + 0.005*"provided" + 0.005*"well"
+2024-10-14 08:33:57,825 - topic #1 (0.333): 0.013*"’" + 0.006*"Forest" + 0.006*"quality" + 0.006*"Bracknell" + 0.005*"good" + 0.005*"provided" + 0.005*"risk" + 0.004*"impact" + 0.004*"progress" + 0.004*"leaders"
+2024-10-14 08:33:57,826 - topic #2 (0.333): 0.016*"’" + 0.007*"needs" + 0.007*"risk" + 0.007*"Forest" + 0.007*"effective" + 0.007*"Bracknell" + 0.006*"plans" + 0.006*"progress" + 0.006*"well" + 0.006*"good"
+2024-10-14 08:33:57,826 - topic diff=0.768572, rho=1.000000
+2024-10-14 08:33:57,826 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=900, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:33:57.826311', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:33:58,653 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:33:58,653 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:58,653 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:33:58,653 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:58,653 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:33:58,653 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:58,654 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:33:58,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:58,654 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:33:58,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:33:58,654 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:33:58,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:08,639 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:34:08,641 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)
+2024-10-14 08:34:08,641 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)", 'datetime': '2024-10-14T08:34:08.641603', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:08,642 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:34:08,642 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:34:08,642 - using serial LDA version on this node
+2024-10-14 08:34:08,643 - 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
+2024-10-14 08:34:08,643 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:34:08,646 - -8.090 per-word bound, 272.5 perplexity estimate based on a held-out corpus of 1 documents with 2249 words
+2024-10-14 08:34:08,646 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:34:08,648 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"Hove" + 0.006*"needs" + 0.006*"Brighton" + 0.006*"practice" + 0.006*"relationships" + 0.005*"experiences" + 0.005*"progress" + 0.005*"PAs"
+2024-10-14 08:34:08,648 - topic #1 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"Brighton" + 0.006*"practice" + 0.006*"well" + 0.005*"progress" + 0.005*"Hove" + 0.005*"receive" + 0.005*"need" + 0.004*"2024"
+2024-10-14 08:34:08,648 - topic #2 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"Hove" + 0.006*"needs" + 0.006*"practice" + 0.006*"experiences" + 0.005*"Brighton" + 0.005*"relationships" + 0.005*"progress" + 0.004*"carers"
+2024-10-14 08:34:08,648 - topic diff=0.742991, rho=1.000000
+2024-10-14 08:34:08,648 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:34:08.648829', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:09,571 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:34:09,571 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:09,571 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:34:09,572 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:09,572 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:34:09,572 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:09,572 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:34:09,572 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:09,572 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:34:09,572 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:09,572 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:34:09,572 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:22,457 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:34:22,459 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)
+2024-10-14 08:34:22,459 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-10-14T08:34:22.459699', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:22,460 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:34:22,461 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:34:22,461 - using serial LDA version on this node
+2024-10-14 08:34:22,461 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:34:22,461 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:34:22,465 - -8.029 per-word bound, 261.3 perplexity estimate based on a held-out corpus of 1 documents with 2647 words
+2024-10-14 08:34:22,465 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:34:22,466 - topic #0 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"Bristol" + 0.007*"good" + 0.006*"health" + 0.006*"progress" + 0.005*"16" + 0.005*"leaders" + 0.005*"27"
+2024-10-14 08:34:22,467 - topic #1 (0.333): 0.018*"’" + 0.008*"good" + 0.008*"well" + 0.008*"Bristol" + 0.007*"needs" + 0.006*"risk" + 0.005*"need" + 0.005*"receive" + 0.005*"progress" + 0.004*"plans"
+2024-10-14 08:34:22,467 - topic #2 (0.333): 0.021*"’" + 0.010*"well" + 0.008*"good" + 0.007*"Bristol" + 0.007*"needs" + 0.005*"always" + 0.005*"progress" + 0.005*"health" + 0.005*"arrangements" + 0.004*"plans"
+2024-10-14 08:34:22,467 - topic diff=0.813628, rho=1.000000
+2024-10-14 08:34:22,467 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1151, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:34:22.467438', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:23,306 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:34:23,306 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:23,306 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:34:23,306 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:23,307 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:34:23,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:23,307 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:34:23,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:23,307 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:34:23,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:23,307 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:34:23,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:33,752 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:34:33,754 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)
+2024-10-14 08:34:33,755 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-10-14T08:34:33.755017', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:33,756 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:34:33,756 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:34:33,756 - using serial LDA version on this node
+2024-10-14 08:34:33,757 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:34:33,757 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:34:33,761 - -8.239 per-word bound, 302.2 perplexity estimate based on a held-out corpus of 1 documents with 2404 words
+2024-10-14 08:34:33,761 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:34:33,762 - topic #0 (0.333): 0.009*"’" + 0.006*"plans" + 0.005*"number" + 0.004*"17" + 0.004*"teams" + 0.004*"Buckinghamshire" + 0.004*"6" + 0.004*"many" + 0.004*"protection" + 0.004*"practice"
+2024-10-14 08:34:33,762 - topic #1 (0.333): 0.010*"’" + 0.005*"17" + 0.004*"plans" + 0.004*"number" + 0.004*"protection" + 0.004*"6" + 0.004*"Buckinghamshire" + 0.004*"December" + 0.003*"impact" + 0.003*"needs"
+2024-10-14 08:34:33,762 - topic #2 (0.333): 0.019*"’" + 0.005*"Buckinghamshire" + 0.005*"plans" + 0.005*"number" + 0.004*"many" + 0.004*"17" + 0.004*"2021" + 0.004*"December" + 0.004*"6" + 0.004*"protection"
+2024-10-14 08:34:33,763 - topic diff=0.729880, rho=1.000000
+2024-10-14 08:34:33,763 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1263, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:34:33.763146', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:34,653 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:34:34,653 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:34,654 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:34:34,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:34,654 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:34:34,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:34,654 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:34:34,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:34,654 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:34:34,654 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:34,655 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:34:34,655 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:44,705 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:34:44,707 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)
+2024-10-14 08:34:44,707 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-10-14T08:34:44.707683', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:44,708 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:34:44,708 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:34:44,709 - using serial LDA version on this node
+2024-10-14 08:34:44,709 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:34:44,709 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:34:44,712 - -7.976 per-word bound, 251.7 perplexity estimate based on a held-out corpus of 1 documents with 2427 words
+2024-10-14 08:34:44,713 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:34:44,714 - topic #0 (0.333): 0.014*"’" + 0.008*"2021" + 0.006*"team" + 0.006*"needs" + 0.005*"risk" + 0.005*"impact" + 0.005*"practice" + 0.005*"need" + 0.005*"quality" + 0.004*"protection"
+2024-10-14 08:34:44,714 - topic #1 (0.333): 0.007*"’" + 0.006*"protection" + 0.006*"needs" + 0.005*"practice" + 0.005*"team" + 0.005*"2021" + 0.005*"quality" + 0.004*"delay" + 0.004*"impact" + 0.004*"25"
+2024-10-14 08:34:44,714 - topic #2 (0.333): 0.011*"’" + 0.008*"protection" + 0.007*"needs" + 0.006*"need" + 0.006*"practice" + 0.006*"2021" + 0.005*"Bury" + 0.005*"impact" + 0.005*"team" + 0.005*"risk"
+2024-10-14 08:34:44,714 - topic diff=0.811684, rho=1.000000
+2024-10-14 08:34:44,714 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:34:44.714857', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:45,595 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:34:45,596 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:45,596 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:34:45,596 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:45,596 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:34:45,596 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:45,596 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:34:45,596 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:45,597 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:34:45,597 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:45,597 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:34:45,597 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:55,877 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:34:55,879 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)
+2024-10-14 08:34:55,879 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-10-14T08:34:55.879666', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:55,880 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:34:55,880 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:34:55,881 - using serial LDA version on this node
+2024-10-14 08:34:55,881 - 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
+2024-10-14 08:34:55,881 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:34:55,885 - -8.041 per-word bound, 263.3 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
+2024-10-14 08:34:55,885 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:34:55,886 - topic #0 (0.333): 0.017*"’" + 0.008*"Calderdale" + 0.006*"ensure" + 0.005*"needs" + 0.005*"progress" + 0.005*"19" + 0.005*"risk" + 0.005*"plans" + 0.005*"well" + 0.004*"understand"
+2024-10-14 08:34:55,886 - topic #1 (0.333): 0.020*"’" + 0.012*"needs" + 0.007*"well" + 0.007*"Calderdale" + 0.007*"plans" + 0.006*"progress" + 0.005*"ensure" + 0.005*"risk" + 0.005*"PAs" + 0.004*"parents"
+2024-10-14 08:34:55,886 - topic #2 (0.333): 0.023*"’" + 0.011*"needs" + 0.010*"Calderdale" + 0.006*"well" + 0.006*"ensure" + 0.005*"plans" + 0.005*"progress" + 0.005*"parents" + 0.005*"risk" + 0.005*"information"
+2024-10-14 08:34:55,886 - topic diff=0.787479, rho=1.000000
+2024-10-14 08:34:55,887 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:34:55.886992', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:34:56,689 - Inspection date 2024-02-19 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:34:56,689 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:56,689 - Inspection date 2024-02-19 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:34:56,690 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:56,690 - Inspection date 2024-02-19 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:34:56,690 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:56,690 - Inspection date 2024-02-19 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:34:56,690 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:56,690 - Inspection date 2024-02-19 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:34:56,690 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:34:56,691 - Inspection date 2024-02-19 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:34:56,691 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:08,177 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:35:08,179 - built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)
+2024-10-14 08:35:08,179 - Dictionary lifecycle event {'msg': "built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)", 'datetime': '2024-10-14T08:35:08.179939', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:08,180 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:35:08,181 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:35:08,181 - using serial LDA version on this node
+2024-10-14 08:35:08,181 - 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
+2024-10-14 08:35:08,181 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:35:08,185 - -8.009 per-word bound, 257.5 perplexity estimate based on a held-out corpus of 1 documents with 2339 words
+2024-10-14 08:35:08,185 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:35:08,186 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"leaders" + 0.005*"Cambridgeshire" + 0.005*"effective" + 0.004*"However" + 0.004*"strong" + 0.004*"leadership" + 0.004*"good" + 0.004*"15"
+2024-10-14 08:35:08,186 - topic #1 (0.333): 0.017*"’" + 0.007*"Cambridgeshire" + 0.006*"needs" + 0.006*"good" + 0.006*"leaders" + 0.005*"well" + 0.005*"15" + 0.005*"practice" + 0.005*"4" + 0.005*"quality"
+2024-10-14 08:35:08,186 - topic #2 (0.333): 0.019*"’" + 0.007*"leaders" + 0.007*"needs" + 0.006*"effective" + 0.006*"Cambridgeshire" + 0.005*"good" + 0.005*"response" + 0.005*"quality" + 0.005*"well" + 0.005*"practice"
+2024-10-14 08:35:08,186 - topic diff=0.788921, rho=1.000000
+2024-10-14 08:35:08,187 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1082, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:35:08.187004', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:09,072 - Inspection date 2024-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:35:09,072 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:09,073 - Inspection date 2024-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:35:09,073 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:09,073 - Inspection date 2024-03-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:35:09,073 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:09,073 - Inspection date 2024-03-04 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:35:09,073 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:09,073 - Inspection date 2024-03-04 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:35:09,073 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:09,073 - Inspection date 2024-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:35:09,073 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:18,757 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:35:18,759 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
+2024-10-14 08:35:18,759 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-10-14T08:35:18.759836', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:18,760 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:35:18,760 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:35:18,761 - using serial LDA version on this node
+2024-10-14 08:35:18,761 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:35:18,761 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:35:18,764 - -7.964 per-word bound, 249.7 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
+2024-10-14 08:35:18,765 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:35:18,766 - topic #0 (0.333): 0.014*"’" + 0.010*"well" + 0.009*"needs" + 0.006*"good" + 0.006*"need" + 0.006*"plans" + 0.005*"carers" + 0.005*"Central" + 0.005*"education" + 0.005*"progress"
+2024-10-14 08:35:18,766 - topic #1 (0.333): 0.018*"’" + 0.009*"well" + 0.007*"need" + 0.006*"needs" + 0.006*"plans" + 0.006*"carers" + 0.005*"effective" + 0.005*"number" + 0.005*"good" + 0.005*"progress"
+2024-10-14 08:35:18,766 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.007*"good" + 0.006*"needs" + 0.006*"progress" + 0.006*"need" + 0.006*"carers" + 0.005*"Central" + 0.005*"plans" + 0.005*"Bedfordshire"
+2024-10-14 08:35:18,766 - topic diff=0.782364, rho=1.000000
+2024-10-14 08:35:18,766 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1030, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:35:18.766901', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:19,561 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:35:19,561 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:19,561 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:35:19,561 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:19,562 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:35:19,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:19,562 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:35:19,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:19,562 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:35:19,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:19,562 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:35:19,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:30,289 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:35:30,292 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)
+2024-10-14 08:35:30,292 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-10-14T08:35:30.292238', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:30,293 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:35:30,293 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:35:30,293 - using serial LDA version on this node
+2024-10-14 08:35:30,293 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:35:30,294 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:35:30,297 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2272 words
+2024-10-14 08:35:30,297 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:35:30,298 - topic #0 (0.333): 0.012*"’" + 0.008*"2024" + 0.007*"plans" + 0.007*"needs" + 0.006*"practice" + 0.006*"well" + 0.006*"quality" + 0.005*"need" + 0.005*"Cheshire" + 0.005*"vulnerable"
+2024-10-14 08:35:30,298 - topic #1 (0.333): 0.013*"’" + 0.008*"2024" + 0.007*"needs" + 0.007*"well" + 0.007*"practice" + 0.006*"effective" + 0.006*"quality" + 0.006*"plans" + 0.005*"Cheshire" + 0.005*"means"
+2024-10-14 08:35:30,299 - topic #2 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"2024" + 0.007*"plans" + 0.006*"East" + 0.006*"leaders" + 0.006*"well" + 0.006*"Cheshire" + 0.006*"practice" + 0.006*"quality"
+2024-10-14 08:35:30,299 - topic diff=0.775923, rho=1.000000
+2024-10-14 08:35:30,299 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:35:30.299331', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:31,222 - Inspection date 2024-02-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:35:31,222 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:31,222 - Inspection date 2024-02-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:35:31,222 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:31,222 - Inspection date 2024-02-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:35:31,222 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:31,222 - Inspection date 2024-02-26 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:35:31,223 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:31,223 - Inspection date 2024-02-26 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:35:31,223 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:31,223 - Inspection date 2024-02-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:35:31,223 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:41,574 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:35:41,576 - built Dictionary<1010 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2203 corpus positions)
+2024-10-14 08:35:41,576 - Dictionary lifecycle event {'msg': "built Dictionary<1010 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2203 corpus positions)", 'datetime': '2024-10-14T08:35:41.576692', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:41,577 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:35:41,577 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:35:41,578 - using serial LDA version on this node
+2024-10-14 08:35:41,578 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:35:41,578 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:35:41,581 - -7.931 per-word bound, 244.1 perplexity estimate based on a held-out corpus of 1 documents with 2203 words
+2024-10-14 08:35:41,581 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:35:41,583 - topic #0 (0.333): 0.017*"’" + 0.006*"plans" + 0.006*"needs" + 0.006*"progress" + 0.006*"19" + 0.005*"West" + 0.005*"Chester" + 0.005*"access" + 0.005*"Cheshire" + 0.005*"well"
+2024-10-14 08:35:41,583 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.005*"impact" + 0.005*"plans" + 0.005*"needs" + 0.005*"progress" + 0.005*"leaders" + 0.004*"protection" + 0.004*"15" + 0.004*"experiences"
+2024-10-14 08:35:41,583 - topic #2 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"progress" + 0.005*"good" + 0.005*"2024" + 0.005*"impact" + 0.005*"meetings" + 0.005*"practice" + 0.005*"15"
+2024-10-14 08:35:41,583 - topic diff=0.786543, rho=1.000000
+2024-10-14 08:35:41,583 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1010, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:35:41.583751', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:42,425 - Inspection date 2024-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:35:42,426 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:42,426 - Inspection date 2024-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:35:42,426 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:42,426 - Inspection date 2024-07-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:35:42,426 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:42,426 - Inspection date 2024-07-15 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:35:42,427 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:42,427 - Inspection date 2024-07-15 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:35:42,427 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:42,427 - Inspection date 2024-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:35:42,427 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:53,235 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:35:53,237 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)
+2024-10-14 08:35:53,237 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-10-14T08:35:53.237759', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:53,238 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:35:53,238 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:35:53,239 - using serial LDA version on this node
+2024-10-14 08:35:53,239 - 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
+2024-10-14 08:35:53,239 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:35:53,243 - -8.049 per-word bound, 264.8 perplexity estimate based on a held-out corpus of 1 documents with 2639 words
+2024-10-14 08:35:53,243 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:35:53,244 - topic #0 (0.333): 0.023*"’" + 0.007*"plans" + 0.006*"needs" + 0.005*"need" + 0.005*"quality" + 0.005*"impact" + 0.005*"practice" + 0.005*"Bradford" + 0.005*"risk" + 0.005*"City"
+2024-10-14 08:35:53,244 - topic #1 (0.333): 0.013*"’" + 0.006*"plans" + 0.004*"need" + 0.004*"2" + 0.004*"lack" + 0.004*"◼" + 0.004*"changes" + 0.004*"21" + 0.004*"December" + 0.004*"many"
+2024-10-14 08:35:53,244 - topic #2 (0.333): 0.023*"’" + 0.006*"Bradford" + 0.006*"plans" + 0.005*"2" + 0.005*"2022" + 0.005*"Borough" + 0.004*"needs" + 0.004*"December" + 0.004*"risk" + 0.004*"impact"
+2024-10-14 08:35:53,245 - topic diff=0.812883, rho=1.000000
+2024-10-14 08:35:53,245 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1164, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:35:53.245159', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:35:54,122 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:35:54,122 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:54,122 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:35:54,123 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:54,123 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:35:54,123 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:54,123 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:35:54,123 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:54,123 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:35:54,123 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:35:54,123 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:35:54,124 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:02,233 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:36:02,235 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)
+2024-10-14 08:36:02,235 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-10-14T08:36:02.235261', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:02,236 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:36:02,236 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:36:02,236 - using serial LDA version on this node
+2024-10-14 08:36:02,237 - 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
+2024-10-14 08:36:02,237 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:36:02,240 - -7.840 per-word bound, 229.1 perplexity estimate based on a held-out corpus of 1 documents with 1767 words
+2024-10-14 08:36:02,240 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:36:02,241 - topic #0 (0.333): 0.012*"’" + 0.011*"needs" + 0.011*"well" + 0.008*"ensure" + 0.006*"effective" + 0.006*"progress" + 0.006*"clear" + 0.005*"supported" + 0.005*"practice" + 0.005*"plans"
+2024-10-14 08:36:02,241 - topic #1 (0.333): 0.011*"needs" + 0.010*"’" + 0.008*"well" + 0.007*"ensure" + 0.007*"effective" + 0.006*"clear" + 0.005*"individual" + 0.005*"within" + 0.004*"plans" + 0.004*"understanding"
+2024-10-14 08:36:02,241 - topic #2 (0.333): 0.012*"’" + 0.012*"needs" + 0.010*"well" + 0.009*"ensure" + 0.007*"progress" + 0.007*"effective" + 0.007*"good" + 0.006*"clear" + 0.006*"plans" + 0.006*"experiences"
+2024-10-14 08:36:02,241 - topic diff=0.751393, rho=1.000000
+2024-10-14 08:36:02,242 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=876, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:36:02.242043', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:03,291 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:36:03,291 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:03,292 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:36:03,292 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:03,292 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:36:03,292 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:03,292 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:36:03,292 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:03,292 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:36:03,292 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:03,292 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:36:03,293 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:12,773 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:36:12,775 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)
+2024-10-14 08:36:12,775 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-10-14T08:36:12.775389', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:12,776 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:36:12,776 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:36:12,776 - using serial LDA version on this node
+2024-10-14 08:36:12,777 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:36:12,777 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:36:12,780 - -7.907 per-word bound, 240.1 perplexity estimate based on a held-out corpus of 1 documents with 2281 words
+2024-10-14 08:36:12,780 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:36:12,781 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"effective" + 0.007*"Wakefield" + 0.007*"good" + 0.007*"quality" + 0.007*"November" + 0.006*"progress" + 0.006*"leaders" + 0.005*"19"
+2024-10-14 08:36:12,782 - topic #1 (0.333): 0.014*"’" + 0.007*"November" + 0.007*"leaders" + 0.006*"well" + 0.006*"quality" + 0.006*"practice" + 0.005*"good" + 0.005*"progress" + 0.005*"Wakefield" + 0.005*"plans"
+2024-10-14 08:36:12,782 - topic #2 (0.333): 0.021*"’" + 0.010*"Wakefield" + 0.008*"quality" + 0.008*"leaders" + 0.007*"November" + 0.007*"well" + 0.007*"effective" + 0.007*"plans" + 0.006*"good" + 0.005*"receive"
+2024-10-14 08:36:12,782 - topic diff=0.804940, rho=1.000000
+2024-10-14 08:36:12,782 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1007, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:36:12.782390', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:13,640 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:36:13,640 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:13,640 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:36:13,640 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:13,641 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:36:13,641 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:13,641 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:36:13,641 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:13,641 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:36:13,641 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:13,641 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:36:13,641 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:22,683 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:36:22,685 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)
+2024-10-14 08:36:22,685 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-10-14T08:36:22.685462', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:22,686 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:36:22,686 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:36:22,686 - using serial LDA version on this node
+2024-10-14 08:36:22,686 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:36:22,687 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:36:22,690 - -7.865 per-word bound, 233.1 perplexity estimate based on a held-out corpus of 1 documents with 1855 words
+2024-10-14 08:36:22,690 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:36:22,691 - topic #0 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"March" + 0.006*"quality" + 0.005*"However" + 0.005*"effective" + 0.005*"York" + 0.005*"education" + 0.005*"ensure" + 0.005*"18"
+2024-10-14 08:36:22,691 - topic #1 (0.333): 0.014*"’" + 0.007*"effective" + 0.007*"March" + 0.006*"needs" + 0.006*"quality" + 0.006*"York" + 0.005*"7" + 0.005*"training" + 0.005*"However" + 0.005*"plans"
+2024-10-14 08:36:22,691 - topic #2 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"quality" + 0.007*"March" + 0.006*"ensure" + 0.005*"effective" + 0.005*"plans" + 0.005*"need" + 0.005*"However" + 0.005*"well"
+2024-10-14 08:36:22,691 - topic diff=0.762055, rho=1.000000
+2024-10-14 08:36:22,691 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=909, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:36:22.691910', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:23,525 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:36:23,525 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:23,525 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:36:23,525 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:23,525 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:36:23,525 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:23,525 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:36:23,525 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:23,526 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:36:23,526 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:23,526 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:36:23,526 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:33,192 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:36:33,194 - built Dictionary<1053 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2351 corpus positions)
+2024-10-14 08:36:33,194 - Dictionary lifecycle event {'msg': "built Dictionary<1053 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2351 corpus positions)", 'datetime': '2024-10-14T08:36:33.194539', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:33,195 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:36:33,195 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:36:33,195 - using serial LDA version on this node
+2024-10-14 08:36:33,196 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:36:33,196 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:36:33,199 - -7.958 per-word bound, 248.7 perplexity estimate based on a held-out corpus of 1 documents with 2351 words
+2024-10-14 08:36:33,199 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:36:33,201 - topic #0 (0.333): 0.012*"’" + 0.007*"needs" + 0.007*"Cornwall" + 0.006*"need" + 0.006*"receive" + 0.005*"effective" + 0.004*"well" + 0.004*"5" + 0.004*"progress" + 0.004*"risk"
+2024-10-14 08:36:33,201 - topic #1 (0.333): 0.020*"’" + 0.012*"needs" + 0.007*"need" + 0.007*"Cornwall" + 0.006*"well" + 0.006*"oversight" + 0.005*"effective" + 0.005*"1" + 0.005*"2024" + 0.005*"receive"
+2024-10-14 08:36:33,201 - topic #2 (0.333): 0.021*"’" + 0.009*"Cornwall" + 0.008*"well" + 0.007*"need" + 0.006*"needs" + 0.005*"progress" + 0.005*"receive" + 0.005*"5" + 0.004*"approach" + 0.004*"leaders"
+2024-10-14 08:36:33,201 - topic diff=0.794861, rho=1.000000
+2024-10-14 08:36:33,201 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1053, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:36:33.201904', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:34,170 - Inspection date 2024-07-01 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:36:34,170 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:34,170 - Inspection date 2024-07-01 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:36:34,170 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:34,171 - Inspection date 2024-07-01 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:36:34,171 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:34,171 - Inspection date 2024-07-01 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:36:34,171 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:34,171 - Inspection date 2024-07-01 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:36:34,171 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:34,171 - Inspection date 2024-07-01 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:36:34,171 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:41,911 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:36:41,913 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)
+2024-10-14 08:36:41,913 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-10-14T08:36:41.913541', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:41,914 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:36:41,914 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:36:41,914 - using serial LDA version on this node
+2024-10-14 08:36:41,914 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:36:41,914 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:36:41,917 - -7.690 per-word bound, 206.5 perplexity estimate based on a held-out corpus of 1 documents with 1521 words
+2024-10-14 08:36:41,917 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:36:41,918 - topic #0 (0.333): 0.015*"’" + 0.011*"Isles" + 0.009*"Scilly" + 0.008*"information" + 0.007*"need" + 0.006*"practice" + 0.006*"needs" + 0.006*"place" + 0.006*"protection" + 0.005*"quality"
+2024-10-14 08:36:41,919 - topic #1 (0.333): 0.023*"’" + 0.012*"Isles" + 0.012*"Scilly" + 0.010*"information" + 0.009*"practice" + 0.008*"need" + 0.007*"needs" + 0.007*"protection" + 0.006*"place" + 0.006*"quality"
+2024-10-14 08:36:41,919 - topic #2 (0.333): 0.022*"’" + 0.013*"Scilly" + 0.012*"Isles" + 0.009*"practice" + 0.009*"information" + 0.008*"need" + 0.007*"protection" + 0.007*"needs" + 0.006*"quality" + 0.006*"risks"
+2024-10-14 08:36:41,919 - topic diff=0.760563, rho=1.000000
+2024-10-14 08:36:41,919 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=754, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:36:41.919400', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:42,836 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:36:42,836 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:42,836 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:36:42,836 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:42,836 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:36:42,837 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:42,837 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:36:42,837 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:42,837 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:36:42,837 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:42,837 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:36:42,837 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:53,997 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:36:53,999 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)
+2024-10-14 08:36:53,999 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-10-14T08:36:53.999441', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:54,000 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:36:54,000 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:36:54,000 - using serial LDA version on this node
+2024-10-14 08:36:54,001 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:36:54,001 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:36:54,004 - -7.850 per-word bound, 230.7 perplexity estimate based on a held-out corpus of 1 documents with 2074 words
+2024-10-14 08:36:54,004 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:36:54,005 - topic #0 (0.333): 0.019*"’" + 0.010*"Coventry" + 0.008*"well" + 0.007*"plans" + 0.006*"supported" + 0.006*"need" + 0.006*"family" + 0.006*"needs" + 0.005*"strong" + 0.005*"2022"
+2024-10-14 08:36:54,005 - topic #1 (0.333): 0.020*"’" + 0.010*"needs" + 0.008*"supported" + 0.008*"well" + 0.008*"Coventry" + 0.006*"plans" + 0.006*"strong" + 0.006*"family" + 0.005*"1" + 0.004*"2022"
+2024-10-14 08:36:54,005 - topic #2 (0.333): 0.019*"’" + 0.009*"well" + 0.006*"needs" + 0.006*"Coventry" + 0.006*"supported" + 0.005*"family" + 0.005*"strong" + 0.005*"need" + 0.004*"plans" + 0.004*"1"
+2024-10-14 08:36:54,006 - topic diff=0.797633, rho=1.000000
+2024-10-14 08:36:54,006 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=938, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:36:54.006141', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:36:54,941 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:36:54,941 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:54,942 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:36:54,942 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:54,942 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:36:54,942 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:54,943 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:36:54,943 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:54,943 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:36:54,943 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:36:54,944 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:36:54,944 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:07,791 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:37:07,794 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)
+2024-10-14 08:37:07,794 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-10-14T08:37:07.794475', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:07,795 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:37:07,795 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:37:07,796 - using serial LDA version on this node
+2024-10-14 08:37:07,796 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:37:07,796 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:37:07,800 - -8.084 per-word bound, 271.4 perplexity estimate based on a held-out corpus of 1 documents with 2653 words
+2024-10-14 08:37:07,800 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:37:07,801 - topic #0 (0.333): 0.022*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"practice" + 0.006*"leaders" + 0.006*"effective" + 0.005*"Darlington" + 0.005*"October" + 0.005*"supported" + 0.004*"education"
+2024-10-14 08:37:07,802 - topic #1 (0.333): 0.018*"’" + 0.008*"October" + 0.007*"well" + 0.007*"Darlington" + 0.006*"practice" + 0.006*"needs" + 0.006*"leaders" + 0.005*"quality" + 0.005*"plans" + 0.005*"education"
+2024-10-14 08:37:07,802 - topic #2 (0.333): 0.015*"’" + 0.008*"well" + 0.008*"leaders" + 0.007*"needs" + 0.006*"October" + 0.005*"Darlington" + 0.005*"practice" + 0.005*"10" + 0.005*"effective" + 0.004*"quality"
+2024-10-14 08:37:07,802 - topic diff=0.798647, rho=1.000000
+2024-10-14 08:37:07,802 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1195, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:37:07.802440', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:08,704 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:37:08,704 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:08,704 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:37:08,705 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:08,705 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:37:08,705 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:08,705 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:37:08,705 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:08,705 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:37:08,705 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:08,705 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:37:08,705 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:19,646 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:37:19,650 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)
+2024-10-14 08:37:19,650 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-10-14T08:37:19.650688', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:19,653 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:37:19,653 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:37:19,653 - using serial LDA version on this node
+2024-10-14 08:37:19,653 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:37:19,654 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:37:19,660 - -8.040 per-word bound, 263.2 perplexity estimate based on a held-out corpus of 1 documents with 2396 words
+2024-10-14 08:37:19,660 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:37:19,663 - topic #0 (0.333): 0.024*"’" + 0.010*"needs" + 0.007*"Derby" + 0.006*"quality" + 0.006*"progress" + 0.006*"good" + 0.006*"leaders" + 0.006*"well" + 0.006*"need" + 0.006*"receive"
+2024-10-14 08:37:19,663 - topic #1 (0.333): 0.022*"’" + 0.008*"Derby" + 0.008*"needs" + 0.007*"receive" + 0.006*"quality" + 0.006*"progress" + 0.006*"plans" + 0.005*"appropriate" + 0.005*"need" + 0.005*"good"
+2024-10-14 08:37:19,666 - topic #2 (0.333): 0.015*"’" + 0.010*"needs" + 0.007*"quality" + 0.006*"Derby" + 0.005*"plans" + 0.005*"receive" + 0.004*"well" + 0.004*"leaders" + 0.004*"need" + 0.004*"appropriate"
+2024-10-14 08:37:19,666 - topic diff=0.775395, rho=1.000000
+2024-10-14 08:37:19,666 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1121, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:37:19.666429', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:20,581 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:37:20,581 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:20,582 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:37:20,582 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:20,582 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:37:20,582 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:20,582 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:37:20,582 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:20,583 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:37:20,583 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:20,583 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:37:20,583 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:29,416 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:37:29,418 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)
+2024-10-14 08:37:29,418 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-10-14T08:37:29.418281', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:29,419 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:37:29,419 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:37:29,419 - using serial LDA version on this node
+2024-10-14 08:37:29,419 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:37:29,420 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:37:29,423 - -8.041 per-word bound, 263.4 perplexity estimate based on a held-out corpus of 1 documents with 2035 words
+2024-10-14 08:37:29,423 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:37:29,424 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.005*"plans" + 0.005*"Derbyshire" + 0.005*"positive" + 0.004*"health" + 0.004*"good" + 0.004*"10" + 0.004*"November" + 0.004*"needs"
+2024-10-14 08:37:29,424 - topic #1 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"Derbyshire" + 0.005*"needs" + 0.005*"positive" + 0.005*"plans" + 0.005*"education" + 0.005*"10" + 0.004*"2023" + 0.004*"progress"
+2024-10-14 08:37:29,425 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.007*"Derbyshire" + 0.005*"need" + 0.005*"effective" + 0.005*"leaders" + 0.004*"number" + 0.004*"plans" + 0.004*"education" + 0.004*"good"
+2024-10-14 08:37:29,425 - topic diff=0.738010, rho=1.000000
+2024-10-14 08:37:29,425 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:37:29.425229', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:30,427 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:37:30,427 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:30,427 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:37:30,427 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:30,427 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:37:30,428 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:30,428 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:37:30,428 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:30,428 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:37:30,428 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:30,428 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:37:30,428 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:41,274 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:37:41,276 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)
+2024-10-14 08:37:41,276 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-10-14T08:37:41.276958', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:41,278 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:37:41,278 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:37:41,278 - using serial LDA version on this node
+2024-10-14 08:37:41,278 - 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
+2024-10-14 08:37:41,278 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:37:41,282 - -8.144 per-word bound, 283.0 perplexity estimate based on a held-out corpus of 1 documents with 2313 words
+2024-10-14 08:37:41,282 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:37:41,284 - topic #0 (0.333): 0.010*"’" + 0.006*"well" + 0.005*"health" + 0.005*"progress" + 0.005*"risk" + 0.005*"leaders" + 0.004*"case" + 0.004*"quality" + 0.004*"plans" + 0.004*"protection"
+2024-10-14 08:37:41,284 - topic #1 (0.333): 0.007*"’" + 0.006*"well" + 0.005*"leaders" + 0.004*"Devon" + 0.004*"living" + 0.004*"protection" + 0.004*"health" + 0.004*"time" + 0.004*"risk" + 0.004*"progress"
+2024-10-14 08:37:41,284 - topic #2 (0.333): 0.011*"’" + 0.005*"well" + 0.005*"risk" + 0.004*"health" + 0.004*"risks" + 0.004*"areas" + 0.004*"progress" + 0.004*"leaders" + 0.004*"right" + 0.003*"practice"
+2024-10-14 08:37:41,284 - topic diff=0.728457, rho=1.000000
+2024-10-14 08:37:41,284 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:37:41.284725', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:42,257 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:37:42,257 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:42,258 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:37:42,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:42,258 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:37:42,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:42,258 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:37:42,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:42,258 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:37:42,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:42,259 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:37:42,259 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:52,802 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:37:52,804 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)
+2024-10-14 08:37:52,804 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-10-14T08:37:52.804703', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:52,805 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:37:52,805 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:37:52,806 - using serial LDA version on this node
+2024-10-14 08:37:52,806 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:37:52,806 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:37:52,810 - -8.114 per-word bound, 277.0 perplexity estimate based on a held-out corpus of 1 documents with 2429 words
+2024-10-14 08:37:52,810 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:37:52,811 - topic #0 (0.333): 0.019*"’" + 0.006*"well" + 0.005*"many" + 0.005*"14" + 0.005*"information" + 0.004*"leaders" + 0.004*"progress" + 0.004*"Doncaster" + 0.004*"protection" + 0.004*"Trust"
+2024-10-14 08:37:52,811 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"Doncaster" + 0.005*"leaders" + 0.005*"records" + 0.005*"many" + 0.004*"progress" + 0.004*"arrangements" + 0.004*"quality" + 0.004*"2022"
+2024-10-14 08:37:52,812 - topic #2 (0.333): 0.021*"’" + 0.007*"Doncaster" + 0.006*"well" + 0.006*"quality" + 0.005*"plans" + 0.005*"oversight" + 0.005*"progress" + 0.005*"records" + 0.005*"leaders" + 0.004*"information"
+2024-10-14 08:37:52,812 - topic diff=0.769365, rho=1.000000
+2024-10-14 08:37:52,812 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:37:52.812283', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:37:54,645 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:37:54,646 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:54,646 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:37:54,646 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:54,646 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:37:54,646 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:54,646 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:37:54,646 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:54,647 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:37:54,647 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:37:54,647 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:37:54,647 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:02,490 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:38:02,492 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)
+2024-10-14 08:38:02,492 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-10-14T08:38:02.492879', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:02,493 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:38:02,494 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:38:02,494 - using serial LDA version on this node
+2024-10-14 08:38:02,494 - 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
+2024-10-14 08:38:02,494 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:38:02,498 - -8.100 per-word bound, 274.3 perplexity estimate based on a held-out corpus of 1 documents with 1942 words
+2024-10-14 08:38:02,498 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:38:02,499 - topic #0 (0.333): 0.016*"’" + 0.009*"Dorset" + 0.006*"well" + 0.006*"good" + 0.004*"needs" + 0.004*"quality" + 0.004*"arrangements" + 0.004*"home" + 0.004*"need" + 0.004*"October"
+2024-10-14 08:38:02,499 - topic #1 (0.333): 0.009*"’" + 0.007*"Dorset" + 0.006*"good" + 0.006*"well" + 0.004*"need" + 0.004*"arrangements" + 0.004*"2021" + 0.004*"needs" + 0.004*"leaders" + 0.004*"October"
+2024-10-14 08:38:02,499 - topic #2 (0.333): 0.015*"’" + 0.007*"Dorset" + 0.006*"good" + 0.005*"well" + 0.005*"8" + 0.005*"arrangements" + 0.005*"needs" + 0.004*"including" + 0.004*"leaders" + 0.004*"27"
+2024-10-14 08:38:02,499 - topic diff=0.714790, rho=1.000000
+2024-10-14 08:38:02,500 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1067, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:38:02.500072', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:03,430 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:38:03,430 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:03,431 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:38:03,431 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:03,431 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:38:03,431 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:03,431 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:38:03,431 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:03,431 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:38:03,432 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:03,432 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:38:03,432 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:13,572 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:38:13,574 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)
+2024-10-14 08:38:13,574 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-10-14T08:38:13.574748', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:13,575 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:38:13,575 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:38:13,576 - using serial LDA version on this node
+2024-10-14 08:38:13,576 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:38:13,576 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:38:13,579 - -8.011 per-word bound, 258.0 perplexity estimate based on a held-out corpus of 1 documents with 2138 words
+2024-10-14 08:38:13,579 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:38:13,581 - topic #0 (0.333): 0.012*"’" + 0.009*"needs" + 0.005*"Dudley" + 0.005*"ensure" + 0.005*"always" + 0.004*"plans" + 0.004*"well" + 0.004*"arrangements" + 0.004*"oversight" + 0.004*"practice"
+2024-10-14 08:38:13,581 - topic #1 (0.333): 0.012*"’" + 0.009*"needs" + 0.009*"Dudley" + 0.006*"well" + 0.005*"plans" + 0.005*"quality" + 0.005*"always" + 0.005*"October" + 0.004*"progress" + 0.004*"oversight"
+2024-10-14 08:38:13,581 - topic #2 (0.333): 0.018*"’" + 0.014*"needs" + 0.009*"Dudley" + 0.006*"arrangements" + 0.006*"well" + 0.006*"always" + 0.005*"plans" + 0.005*"quality" + 0.005*"ensure" + 0.005*"oversight"
+2024-10-14 08:38:13,581 - topic diff=0.769745, rho=1.000000
+2024-10-14 08:38:13,581 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1050, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:38:13.581657', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:14,409 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:38:14,410 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:14,410 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:38:14,410 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:14,410 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:38:14,410 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:14,410 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:38:14,410 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:14,410 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:38:14,410 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:14,411 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:38:14,411 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:25,270 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:38:25,272 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)
+2024-10-14 08:38:25,272 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-10-14T08:38:25.272463', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:25,273 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:38:25,273 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:38:25,273 - using serial LDA version on this node
+2024-10-14 08:38:25,274 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:38:25,274 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:38:25,277 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
+2024-10-14 08:38:25,277 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:38:25,278 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"Durham" + 0.007*"ensure" + 0.007*"May" + 0.005*"well" + 0.005*"practice" + 0.005*"plans" + 0.004*"leaders" + 0.004*"risks"
+2024-10-14 08:38:25,279 - topic #1 (0.333): 0.016*"’" + 0.011*"needs" + 0.007*"May" + 0.007*"Durham" + 0.006*"well" + 0.006*"plans" + 0.005*"ensure" + 0.005*"carers" + 0.004*"progress" + 0.004*"risks"
+2024-10-14 08:38:25,279 - topic #2 (0.333): 0.014*"’" + 0.011*"needs" + 0.008*"well" + 0.008*"plans" + 0.007*"May" + 0.007*"Durham" + 0.006*"practice" + 0.005*"ensure" + 0.005*"leaders" + 0.004*"family"
+2024-10-14 08:38:25,279 - topic diff=0.770080, rho=1.000000
+2024-10-14 08:38:25,279 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:38:25.279474', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:26,136 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:38:26,136 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:26,137 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:38:26,137 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:26,137 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:38:26,137 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:26,137 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:38:26,137 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:26,137 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:38:26,137 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:26,137 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:38:26,138 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:35,846 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:38:35,848 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)
+2024-10-14 08:38:35,848 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-10-14T08:38:35.848305', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:35,849 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:38:35,849 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:38:35,849 - using serial LDA version on this node
+2024-10-14 08:38:35,849 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:38:35,849 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:38:35,853 - -7.923 per-word bound, 242.8 perplexity estimate based on a held-out corpus of 1 documents with 2014 words
+2024-10-14 08:38:35,853 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:38:35,854 - topic #0 (0.333): 0.021*"’" + 0.010*"needs" + 0.009*"plans" + 0.009*"well" + 0.008*"progress" + 0.007*"East" + 0.006*"Riding" + 0.004*"30" + 0.004*"effective" + 0.004*"quality"
+2024-10-14 08:38:35,854 - topic #1 (0.333): 0.016*"’" + 0.009*"plans" + 0.009*"well" + 0.008*"needs" + 0.007*"progress" + 0.007*"Riding" + 0.006*"East" + 0.006*"10" + 0.005*"good" + 0.005*"education"
+2024-10-14 08:38:35,854 - topic #2 (0.333): 0.010*"’" + 0.009*"needs" + 0.006*"plans" + 0.006*"well" + 0.005*"progress" + 0.005*"East" + 0.005*"Riding" + 0.005*"10" + 0.005*"partners" + 0.005*"January"
+2024-10-14 08:38:35,854 - topic diff=0.774098, rho=1.000000
+2024-10-14 08:38:35,854 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:38:35.854953', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:36,663 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:38:36,664 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:36,664 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:38:36,664 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:36,664 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:38:36,664 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:36,664 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:38:36,664 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:36,664 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:38:36,664 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:36,665 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:38:36,665 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:46,428 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:38:46,430 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)
+2024-10-14 08:38:46,431 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-10-14T08:38:46.431053', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:46,432 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:38:46,432 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:38:46,432 - using serial LDA version on this node
+2024-10-14 08:38:46,432 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:38:46,432 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:38:46,436 - -8.075 per-word bound, 269.7 perplexity estimate based on a held-out corpus of 1 documents with 2220 words
+2024-10-14 08:38:46,436 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:38:46,437 - topic #0 (0.333): 0.018*"’" + 0.011*"well" + 0.008*"needs" + 0.008*"plans" + 0.008*"East" + 0.007*"Sussex" + 0.007*"progress" + 0.007*"including" + 0.005*"provide" + 0.005*"impact"
+2024-10-14 08:38:46,438 - topic #1 (0.333): 0.017*"’" + 0.009*"needs" + 0.009*"well" + 0.008*"plans" + 0.006*"impact" + 0.006*"East" + 0.005*"Sussex" + 0.005*"progress" + 0.005*"experiences" + 0.005*"effective"
+2024-10-14 08:38:46,438 - topic #2 (0.333): 0.011*"’" + 0.007*"well" + 0.007*"plans" + 0.005*"needs" + 0.005*"progress" + 0.005*"East" + 0.005*"Sussex" + 0.004*"relationships" + 0.004*"11" + 0.004*"including"
+2024-10-14 08:38:46,438 - topic diff=0.765049, rho=1.000000
+2024-10-14 08:38:46,438 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1111, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:38:46.438395', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:47,370 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:38:47,371 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:47,371 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:38:47,371 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:47,371 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:38:47,371 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:47,372 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:38:47,372 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:47,372 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:38:47,372 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:47,372 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:38:47,372 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:58,292 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:38:58,295 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)
+2024-10-14 08:38:58,295 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-10-14T08:38:58.295170', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:58,296 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:38:58,296 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:38:58,296 - using serial LDA version on this node
+2024-10-14 08:38:58,297 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:38:58,297 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:38:58,300 - -8.008 per-word bound, 257.5 perplexity estimate based on a held-out corpus of 1 documents with 2686 words
+2024-10-14 08:38:58,300 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:38:58,302 - topic #0 (0.333): 0.010*"’" + 0.008*"well" + 0.006*"progress" + 0.005*"family" + 0.005*"needs" + 0.005*"understand" + 0.004*"plans" + 0.004*"risk" + 0.004*"parents" + 0.004*"advisers"
+2024-10-14 08:38:58,302 - topic #1 (0.333): 0.022*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"progress" + 0.006*"plans" + 0.005*"risk" + 0.005*"family" + 0.005*"practice" + 0.005*"experiences" + 0.005*"new"
+2024-10-14 08:38:58,302 - topic #2 (0.333): 0.019*"’" + 0.007*"progress" + 0.006*"plans" + 0.005*"Essex" + 0.005*"‘" + 0.005*"well" + 0.005*"family" + 0.004*"needs" + 0.004*"leaders" + 0.004*"experiences"
+2024-10-14 08:38:58,302 - topic diff=0.813133, rho=1.000000
+2024-10-14 08:38:58,302 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:38:58.302692', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:38:59,175 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:38:59,176 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:59,176 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:38:59,176 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:59,176 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:38:59,176 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:59,176 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:38:59,176 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:59,176 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:38:59,176 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:38:59,177 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:38:59,177 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:08,890 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:39:08,893 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)
+2024-10-14 08:39:08,893 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-10-14T08:39:08.893473', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:08,894 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:39:08,894 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:39:08,894 - using serial LDA version on this node
+2024-10-14 08:39:08,895 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:39:08,895 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:39:08,898 - -8.043 per-word bound, 263.8 perplexity estimate based on a held-out corpus of 1 documents with 2356 words
+2024-10-14 08:39:08,899 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:39:08,900 - topic #0 (0.333): 0.013*"’" + 0.007*"effective" + 0.006*"practice" + 0.006*"timely" + 0.006*"good" + 0.006*"needs" + 0.005*"quality" + 0.005*"well" + 0.005*"early" + 0.004*"team"
+2024-10-14 08:39:08,900 - topic #1 (0.333): 0.015*"’" + 0.010*"effective" + 0.007*"practice" + 0.007*"good" + 0.007*"quality" + 0.006*"well" + 0.006*"needs" + 0.005*"progress" + 0.005*"improve" + 0.005*"early"
+2024-10-14 08:39:08,900 - topic #2 (0.333): 0.013*"’" + 0.008*"effective" + 0.006*"good" + 0.006*"quality" + 0.005*"practice" + 0.005*"timely" + 0.005*"plans" + 0.005*"well" + 0.005*"needs" + 0.004*"need"
+2024-10-14 08:39:08,900 - topic diff=0.764182, rho=1.000000
+2024-10-14 08:39:08,900 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:39:08.900924', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:09,791 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:39:09,791 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:09,791 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:39:09,791 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:09,792 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:39:09,792 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:09,792 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:39:09,792 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:09,792 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:39:09,792 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:09,792 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:39:09,792 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:20,276 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:39:20,279 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)
+2024-10-14 08:39:20,279 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-10-14T08:39:20.279461', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:20,280 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:39:20,280 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:39:20,280 - using serial LDA version on this node
+2024-10-14 08:39:20,281 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:39:20,281 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:39:20,285 - -8.058 per-word bound, 266.4 perplexity estimate based on a held-out corpus of 1 documents with 2579 words
+2024-10-14 08:39:20,285 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:39:20,286 - topic #0 (0.333): 0.014*"’" + 0.007*"needs" + 0.006*"plans" + 0.006*"progress" + 0.005*"well" + 0.005*"February" + 0.005*"2022" + 0.005*"timely" + 0.004*"Gloucestershire" + 0.004*"need"
+2024-10-14 08:39:20,286 - topic #1 (0.333): 0.022*"’" + 0.010*"needs" + 0.008*"February" + 0.008*"2022" + 0.007*"plans" + 0.006*"protection" + 0.005*"leaders" + 0.005*"experienced" + 0.005*"good" + 0.005*"family"
+2024-10-14 08:39:20,286 - topic #2 (0.333): 0.014*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"2022" + 0.006*"February" + 0.005*"plans" + 0.005*"Gloucestershire" + 0.005*"progress" + 0.005*"experienced" + 0.005*"appropriate"
+2024-10-14 08:39:20,286 - topic diff=0.832500, rho=1.000000
+2024-10-14 08:39:20,287 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:39:20.287007', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:21,228 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:39:21,228 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:21,229 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:39:21,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:21,229 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:39:21,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:21,229 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:39:21,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:21,229 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:39:21,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:21,229 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:39:21,230 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:33,224 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:39:33,226 - built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)
+2024-10-14 08:39:33,226 - Dictionary lifecycle event {'msg': "built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)", 'datetime': '2024-10-14T08:39:33.226509', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:33,227 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:39:33,227 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:39:33,228 - using serial LDA version on this node
+2024-10-14 08:39:33,228 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:39:33,228 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:39:33,232 - -8.056 per-word bound, 266.1 perplexity estimate based on a held-out corpus of 1 documents with 2652 words
+2024-10-14 08:39:33,232 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:39:33,234 - topic #0 (0.333): 0.016*"’" + 0.006*"needs" + 0.005*"plans" + 0.005*"always" + 0.005*"quality" + 0.005*"need" + 0.004*"24" + 0.004*"recently" + 0.004*"protection" + 0.004*"2024"
+2024-10-14 08:39:33,234 - topic #1 (0.333): 0.017*"’" + 0.008*"Halton" + 0.008*"needs" + 0.007*"many" + 0.006*"quality" + 0.006*"including" + 0.006*"need" + 0.005*"lack" + 0.005*"experiences" + 0.005*"Leaders"
+2024-10-14 08:39:33,234 - topic #2 (0.333): 0.012*"’" + 0.008*"needs" + 0.006*"protection" + 0.006*"quality" + 0.006*"including" + 0.005*"Halton" + 0.005*"many" + 0.005*"Leaders" + 0.004*"13" + 0.004*"need"
+2024-10-14 08:39:33,234 - topic diff=0.804827, rho=1.000000
+2024-10-14 08:39:33,234 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1172, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:39:33.234711', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:34,022 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:39:34,023 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:34,023 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:39:34,023 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:34,023 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:39:34,023 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:34,024 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:39:34,024 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:34,024 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:39:34,024 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:34,024 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:39:34,024 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:44,525 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:39:44,527 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)
+2024-10-14 08:39:44,528 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)", 'datetime': '2024-10-14T08:39:44.528109', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:44,529 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:39:44,529 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:39:44,529 - using serial LDA version on this node
+2024-10-14 08:39:44,529 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:39:44,529 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:39:44,533 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 2524 words
+2024-10-14 08:39:44,533 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:39:44,534 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"plans" + 0.007*"family" + 0.006*"new" + 0.006*"receive" + 0.006*"progress" + 0.005*"practice" + 0.005*"quality" + 0.005*"Hampshire"
+2024-10-14 08:39:44,534 - topic #1 (0.333): 0.014*"’" + 0.008*"new" + 0.007*"progress" + 0.007*"family" + 0.006*"well" + 0.006*"plans" + 0.005*"needs" + 0.005*"14" + 0.005*"practice" + 0.005*"quality"
+2024-10-14 08:39:44,535 - topic #2 (0.333): 0.014*"’" + 0.007*"family" + 0.006*"new" + 0.006*"well" + 0.006*"quality" + 0.006*"plans" + 0.005*"progress" + 0.005*"needs" + 0.005*"achieve" + 0.004*"10"
+2024-10-14 08:39:44,535 - topic diff=0.813907, rho=1.000000
+2024-10-14 08:39:44,535 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:39:44.535316', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:45,378 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:39:45,378 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:45,379 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:39:45,379 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:45,379 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:39:45,379 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:45,379 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:39:45,379 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:45,379 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:39:45,379 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:45,380 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:39:45,380 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:57,364 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:39:57,366 - built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)
+2024-10-14 08:39:57,367 - Dictionary lifecycle event {'msg': "built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)", 'datetime': '2024-10-14T08:39:57.366967', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:57,368 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:39:57,368 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:39:57,368 - using serial LDA version on this node
+2024-10-14 08:39:57,368 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:39:57,368 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:39:57,372 - -8.071 per-word bound, 268.9 perplexity estimate based on a held-out corpus of 1 documents with 2584 words
+2024-10-14 08:39:57,372 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:39:57,374 - topic #0 (0.333): 0.016*"’" + 0.006*"Hartlepool" + 0.006*"March" + 0.005*"well" + 0.005*"leaders" + 0.005*"needs" + 0.004*"18" + 0.004*"clear" + 0.004*"22" + 0.004*"family"
+2024-10-14 08:39:57,374 - topic #1 (0.333): 0.023*"’" + 0.008*"March" + 0.008*"Hartlepool" + 0.007*"needs" + 0.006*"well" + 0.005*"need" + 0.005*"strong" + 0.005*"18" + 0.005*"effective" + 0.005*"plans"
+2024-10-14 08:39:57,374 - topic #2 (0.333): 0.019*"’" + 0.007*"needs" + 0.007*"March" + 0.007*"leaders" + 0.006*"Hartlepool" + 0.006*"well" + 0.005*"plans" + 0.005*"supported" + 0.005*"ensure" + 0.004*"progress"
+2024-10-14 08:39:57,374 - topic diff=0.798398, rho=1.000000
+2024-10-14 08:39:57,374 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1171, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:39:57.374664', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:39:58,228 - Inspection date 2024-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:39:58,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:58,229 - Inspection date 2024-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:39:58,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:58,229 - Inspection date 2024-03-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:39:58,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:58,229 - Inspection date 2024-03-18 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:39:58,230 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:58,230 - Inspection date 2024-03-18 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:39:58,230 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:39:58,230 - Inspection date 2024-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:39:58,230 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:09,498 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:40:09,501 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
+2024-10-14 08:40:09,501 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-10-14T08:40:09.501237', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:09,502 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:40:09,502 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:40:09,502 - using serial LDA version on this node
+2024-10-14 08:40:09,503 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:40:09,503 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:40:09,506 - -8.043 per-word bound, 263.7 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
+2024-10-14 08:40:09,506 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:40:09,508 - topic #0 (0.333): 0.018*"’" + 0.005*"lack" + 0.005*"Herefordshire" + 0.005*"practice" + 0.005*"needs" + 0.004*"many" + 0.004*"agency" + 0.004*"management" + 0.004*"progress" + 0.004*"plans"
+2024-10-14 08:40:09,508 - topic #1 (0.333): 0.017*"’" + 0.005*"practice" + 0.004*"need" + 0.004*"impact" + 0.004*"Herefordshire" + 0.004*"lack" + 0.004*"plans" + 0.004*"carers" + 0.004*"needs" + 0.004*"oversight"
+2024-10-14 08:40:09,508 - topic #2 (0.333): 0.017*"’" + 0.006*"practice" + 0.006*"Herefordshire" + 0.006*"impact" + 0.005*"many" + 0.005*"needs" + 0.005*"lack" + 0.005*"identified" + 0.004*"18" + 0.004*"July"
+2024-10-14 08:40:09,508 - topic diff=0.788218, rho=1.000000
+2024-10-14 08:40:09,508 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:40:09.508687', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:10,329 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:40:10,329 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:10,330 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:40:10,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:10,330 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:40:10,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:10,330 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:40:10,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:10,330 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:40:10,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:10,330 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:40:10,331 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:21,441 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:40:21,445 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)
+2024-10-14 08:40:21,445 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-10-14T08:40:21.445725', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:21,447 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:40:21,447 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:40:21,448 - using serial LDA version on this node
+2024-10-14 08:40:21,448 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:40:21,449 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:40:21,455 - -8.137 per-word bound, 281.5 perplexity estimate based on a held-out corpus of 1 documents with 2456 words
+2024-10-14 08:40:21,455 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:40:21,457 - topic #0 (0.333): 0.025*"’" + 0.007*"Hertfordshire" + 0.006*"well" + 0.005*"needs" + 0.005*"receive" + 0.005*"plans" + 0.005*"positive" + 0.004*"family" + 0.004*"27" + 0.004*"January"
+2024-10-14 08:40:21,458 - topic #1 (0.333): 0.022*"’" + 0.006*"Hertfordshire" + 0.005*"well" + 0.005*"needs" + 0.005*"receive" + 0.005*"leaders" + 0.004*"plans" + 0.004*"2023" + 0.004*"know" + 0.004*"23"
+2024-10-14 08:40:21,458 - topic #2 (0.333): 0.021*"’" + 0.007*"needs" + 0.007*"well" + 0.007*"Hertfordshire" + 0.005*"receive" + 0.005*"23" + 0.005*"risk" + 0.004*"need" + 0.004*"plans" + 0.004*"‘"
+2024-10-14 08:40:21,458 - topic diff=0.790071, rho=1.000000
+2024-10-14 08:40:21,458 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:40:21.458825', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:23,120 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:40:23,121 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:23,121 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:40:23,121 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:23,121 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:40:23,121 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:23,121 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:40:23,121 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:23,121 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:40:23,121 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:23,121 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:40:23,121 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:32,101 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:40:32,103 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)
+2024-10-14 08:40:32,103 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-10-14T08:40:32.103766', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:32,104 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:40:32,104 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:40:32,104 - using serial LDA version on this node
+2024-10-14 08:40:32,105 - 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
+2024-10-14 08:40:32,105 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:40:32,108 - -7.953 per-word bound, 247.8 perplexity estimate based on a held-out corpus of 1 documents with 1934 words
+2024-10-14 08:40:32,108 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:40:32,109 - topic #0 (0.333): 0.017*"’" + 0.007*"leaders" + 0.006*"needs" + 0.006*"Isle" + 0.005*"3" + 0.005*"supported" + 0.005*"progress" + 0.005*"plans" + 0.005*"well" + 0.004*"Wight"
+2024-10-14 08:40:32,109 - topic #1 (0.333): 0.015*"’" + 0.008*"leaders" + 0.006*"protection" + 0.006*"well" + 0.006*"needs" + 0.006*"3" + 0.005*"progress" + 0.005*"plans" + 0.005*"Senior" + 0.005*"Wight"
+2024-10-14 08:40:32,110 - topic #2 (0.333): 0.020*"’" + 0.009*"leaders" + 0.006*"well" + 0.005*"practice" + 0.005*"Senior" + 0.005*"good" + 0.005*"Wight" + 0.005*"information" + 0.005*"PAs" + 0.005*"needs"
+2024-10-14 08:40:32,110 - topic diff=0.768820, rho=1.000000
+2024-10-14 08:40:32,110 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:40:32.110290', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:33,027 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:40:33,027 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:33,027 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:40:33,027 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:33,027 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:40:33,027 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:33,027 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:40:33,028 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:33,028 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:40:33,028 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:33,028 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:40:33,028 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:44,670 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:40:44,675 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)
+2024-10-14 08:40:44,675 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-10-14T08:40:44.675472', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:44,677 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:40:44,678 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:40:44,678 - using serial LDA version on this node
+2024-10-14 08:40:44,679 - 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
+2024-10-14 08:40:44,679 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:40:44,686 - -8.166 per-word bound, 287.2 perplexity estimate based on a held-out corpus of 1 documents with 2888 words
+2024-10-14 08:40:44,686 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:40:44,688 - topic #0 (0.333): 0.017*"’" + 0.010*"Kent" + 0.006*"Council" + 0.006*"supported" + 0.005*"needs" + 0.005*"progress" + 0.005*"County" + 0.004*"provide" + 0.004*"impact" + 0.004*"2022"
+2024-10-14 08:40:44,689 - topic #1 (0.333): 0.019*"’" + 0.011*"Kent" + 0.010*"needs" + 0.007*"well" + 0.006*"supported" + 0.006*"County" + 0.006*"Council" + 0.005*"practice" + 0.005*"including" + 0.004*"progress"
+2024-10-14 08:40:44,689 - topic #2 (0.333): 0.018*"’" + 0.007*"Kent" + 0.007*"well" + 0.005*"needs" + 0.005*"Council" + 0.004*"supported" + 0.004*"progress" + 0.004*"practice" + 0.004*"response" + 0.004*"County"
+2024-10-14 08:40:44,689 - topic diff=0.802108, rho=1.000000
+2024-10-14 08:40:44,689 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1298, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:40:44.689880', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:45,638 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:40:45,638 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:45,638 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:40:45,638 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:45,638 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:40:45,638 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:45,639 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:40:45,639 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:45,639 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:40:45,639 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:45,639 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:40:45,639 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:54,459 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:40:54,461 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)
+2024-10-14 08:40:54,461 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-10-14T08:40:54.461280', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:54,462 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:40:54,462 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:40:54,462 - using serial LDA version on this node
+2024-10-14 08:40:54,462 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:40:54,462 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:40:54,466 - -7.947 per-word bound, 246.7 perplexity estimate based on a held-out corpus of 1 documents with 1970 words
+2024-10-14 08:40:54,466 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:40:54,467 - topic #0 (0.333): 0.012*"’" + 0.006*"protection" + 0.006*"planning" + 0.005*"number" + 0.005*"risks" + 0.005*"practice" + 0.005*"need" + 0.005*"small" + 0.005*"management" + 0.004*"Hull"
+2024-10-14 08:40:54,467 - topic #1 (0.333): 0.017*"’" + 0.009*"number" + 0.008*"planning" + 0.007*"need" + 0.006*"management" + 0.006*"well" + 0.006*"practice" + 0.005*"Hull" + 0.005*"impact" + 0.005*"progress"
+2024-10-14 08:40:54,467 - topic #2 (0.333): 0.017*"’" + 0.007*"protection" + 0.007*"well" + 0.006*"practice" + 0.006*"Hull" + 0.005*"number" + 0.005*"planning" + 0.005*"oversight" + 0.005*"small" + 0.005*"agency"
+2024-10-14 08:40:54,467 - topic diff=0.760757, rho=1.000000
+2024-10-14 08:40:54,467 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:40:54.467850', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:40:55,306 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:40:55,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:55,307 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:40:55,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:55,307 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:40:55,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:55,307 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:40:55,307 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:55,308 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:40:55,308 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:40:55,308 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:40:55,308 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:05,565 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:41:05,567 - built Dictionary<963 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2139 corpus positions)
+2024-10-14 08:41:05,567 - Dictionary lifecycle event {'msg': "built Dictionary<963 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2139 corpus positions)", 'datetime': '2024-10-14T08:41:05.567947', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:05,569 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:41:05,569 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:41:05,570 - using serial LDA version on this node
+2024-10-14 08:41:05,570 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:41:05,571 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:41:05,574 - -7.871 per-word bound, 234.0 perplexity estimate based on a held-out corpus of 1 documents with 2139 words
+2024-10-14 08:41:05,574 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:41:05,575 - topic #0 (0.333): 0.025*"’" + 0.008*"plans" + 0.007*"Kirklees" + 0.007*"effective" + 0.006*"needs" + 0.006*"well" + 0.005*"receive" + 0.005*"impact" + 0.005*"ensure" + 0.005*"leaders"
+2024-10-14 08:41:05,575 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"Kirklees" + 0.007*"need" + 0.007*"effective" + 0.007*"impact" + 0.006*"well" + 0.006*"leaders" + 0.005*"timely"
+2024-10-14 08:41:05,576 - topic #2 (0.333): 0.014*"’" + 0.006*"effective" + 0.006*"Kirklees" + 0.006*"needs" + 0.005*"well" + 0.005*"plans" + 0.005*"quality" + 0.005*"ensure" + 0.005*"PAs" + 0.005*"impact"
+2024-10-14 08:41:05,576 - topic diff=0.799072, rho=1.000000
+2024-10-14 08:41:05,576 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=963, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:41:05.576337', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:06,526 - Inspection date 2024-07-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:41:06,527 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:06,527 - Inspection date 2024-07-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:41:06,527 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:06,527 - Inspection date 2024-07-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:41:06,527 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:06,527 - Inspection date 2024-07-08 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:41:06,527 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:06,528 - Inspection date 2024-07-08 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:41:06,528 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:06,528 - Inspection date 2024-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:41:06,528 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:14,552 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:41:14,555 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)
+2024-10-14 08:41:14,555 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-10-14T08:41:14.555880', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:14,557 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:41:14,557 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:41:14,557 - using serial LDA version on this node
+2024-10-14 08:41:14,558 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:41:14,558 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:41:14,563 - -7.825 per-word bound, 226.8 perplexity estimate based on a held-out corpus of 1 documents with 1837 words
+2024-10-14 08:41:14,564 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:41:14,566 - topic #0 (0.333): 0.014*"’" + 0.008*"quality" + 0.007*"needs" + 0.006*"plans" + 0.006*"progress" + 0.005*"need" + 0.005*"Knowsley" + 0.005*"leaders" + 0.005*"good" + 0.004*"experiences"
+2024-10-14 08:41:14,566 - topic #1 (0.333): 0.014*"’" + 0.008*"progress" + 0.008*"needs" + 0.007*"plans" + 0.007*"2021" + 0.006*"Knowsley" + 0.006*"quality" + 0.005*"11" + 0.005*"good" + 0.005*"experiences"
+2024-10-14 08:41:14,566 - topic #2 (0.333): 0.015*"’" + 0.009*"progress" + 0.008*"plans" + 0.007*"needs" + 0.006*"quality" + 0.006*"Knowsley" + 0.005*"2021" + 0.005*"22" + 0.005*"abuse" + 0.005*"experiences"
+2024-10-14 08:41:14,566 - topic diff=0.740288, rho=1.000000
+2024-10-14 08:41:14,567 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=886, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:41:14.567192', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:15,408 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:41:15,408 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:15,408 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:41:15,408 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:15,409 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:41:15,409 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:15,409 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:41:15,409 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:15,409 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:41:15,409 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:15,409 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:41:15,409 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:25,110 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:41:25,112 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)
+2024-10-14 08:41:25,112 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-10-14T08:41:25.112315', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:25,113 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:41:25,113 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:41:25,113 - using serial LDA version on this node
+2024-10-14 08:41:25,114 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:41:25,114 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:41:25,117 - -7.974 per-word bound, 251.4 perplexity estimate based on a held-out corpus of 1 documents with 2263 words
+2024-10-14 08:41:25,117 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:41:25,118 - topic #0 (0.333): 0.015*"’" + 0.010*"well" + 0.008*"needs" + 0.006*"need" + 0.006*"practice" + 0.005*"Lancashire" + 0.005*"plans" + 0.005*"supported" + 0.005*"information" + 0.005*"health"
+2024-10-14 08:41:25,118 - topic #1 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"need" + 0.007*"Lancashire" + 0.007*"needs" + 0.006*"positive" + 0.006*"plans" + 0.006*"supported" + 0.005*"progress" + 0.005*"parents"
+2024-10-14 08:41:25,119 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"need" + 0.006*"practice" + 0.005*"Lancashire" + 0.005*"health" + 0.005*"information" + 0.005*"live" + 0.004*"supported"
+2024-10-14 08:41:25,119 - topic diff=0.782520, rho=1.000000
+2024-10-14 08:41:25,119 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:41:25.119226', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:26,042 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:41:26,042 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:26,042 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:41:26,043 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:26,043 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:41:26,043 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:26,043 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:41:26,043 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:26,043 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:41:26,043 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:26,043 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:41:26,043 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:36,098 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:41:36,100 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)
+2024-10-14 08:41:36,100 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-10-14T08:41:36.100837', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:36,101 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:41:36,101 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:41:36,102 - using serial LDA version on this node
+2024-10-14 08:41:36,102 - 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
+2024-10-14 08:41:36,102 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:41:36,105 - -8.009 per-word bound, 257.5 perplexity estimate based on a held-out corpus of 1 documents with 2261 words
+2024-10-14 08:41:36,105 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:41:36,107 - topic #0 (0.333): 0.015*"’" + 0.006*"Leeds" + 0.006*"needs" + 0.005*"risk" + 0.005*"well" + 0.004*"protection" + 0.004*"supported" + 0.004*"2022" + 0.004*"practice" + 0.004*"21"
+2024-10-14 08:41:36,107 - topic #1 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"Leeds" + 0.006*"risk" + 0.006*"well" + 0.005*"practice" + 0.005*"4" + 0.005*"2022" + 0.004*"plans" + 0.004*"including"
+2024-10-14 08:41:36,107 - topic #2 (0.333): 0.018*"’" + 0.008*"Leeds" + 0.007*"needs" + 0.006*"well" + 0.005*"February" + 0.005*"ensure" + 0.005*"protection" + 0.004*"plans" + 0.004*"practice" + 0.004*"4"
+2024-10-14 08:41:36,107 - topic diff=0.772852, rho=1.000000
+2024-10-14 08:41:36,107 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1071, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:41:36.107764', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:37,020 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:41:37,020 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:37,020 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:41:37,021 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:37,021 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:41:37,021 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:37,021 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:41:37,021 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:37,021 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:41:37,021 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:37,021 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:41:37,021 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:45,690 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:41:45,692 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)
+2024-10-14 08:41:45,692 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-10-14T08:41:45.692585', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:45,693 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:41:45,693 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:41:45,693 - using serial LDA version on this node
+2024-10-14 08:41:45,694 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:41:45,694 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:41:45,697 - -7.875 per-word bound, 234.8 perplexity estimate based on a held-out corpus of 1 documents with 1950 words
+2024-10-14 08:41:45,697 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:41:45,698 - topic #0 (0.333): 0.015*"’" + 0.006*"2021" + 0.006*"Leicester" + 0.006*"well" + 0.005*"good" + 0.005*"ensure" + 0.004*"Council" + 0.004*"City" + 0.004*"needs" + 0.004*"20"
+2024-10-14 08:41:45,698 - topic #1 (0.333): 0.022*"’" + 0.009*"Leicester" + 0.009*"well" + 0.009*"2021" + 0.008*"needs" + 0.007*"ensure" + 0.006*"good" + 0.006*"number" + 0.005*"1" + 0.005*"City"
+2024-10-14 08:41:45,698 - topic #2 (0.333): 0.020*"’" + 0.011*"well" + 0.010*"2021" + 0.007*"needs" + 0.007*"Leicester" + 0.006*"good" + 0.006*"20" + 0.005*"1" + 0.005*"September" + 0.005*"number"
+2024-10-14 08:41:45,699 - topic diff=0.790137, rho=1.000000
+2024-10-14 08:41:45,699 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=932, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:41:45.699181', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:46,657 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:41:46,657 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:46,657 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:41:46,657 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:46,657 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:41:46,658 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:46,658 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:41:46,658 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:46,658 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:41:46,658 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:46,658 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:41:46,658 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:41:59,565 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:41:59,568 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)
+2024-10-14 08:41:59,568 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)", 'datetime': '2024-10-14T08:41:59.568456', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:41:59,569 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:41:59,569 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:41:59,569 - using serial LDA version on this node
+2024-10-14 08:41:59,570 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:41:59,570 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:41:59,574 - -8.105 per-word bound, 275.3 perplexity estimate based on a held-out corpus of 1 documents with 2745 words
+2024-10-14 08:41:59,574 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:41:59,575 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"family" + 0.006*"needs" + 0.006*"experiences" + 0.006*"Leicestershire" + 0.005*"need" + 0.005*"progress" + 0.005*"understand" + 0.005*"risk"
+2024-10-14 08:41:59,575 - topic #1 (0.333): 0.019*"’" + 0.007*"well" + 0.007*"Leicestershire" + 0.005*"family" + 0.005*"PAs" + 0.005*"risk" + 0.005*"plans" + 0.005*"understand" + 0.004*"experiences" + 0.004*"leaders"
+2024-10-14 08:41:59,575 - topic #2 (0.333): 0.017*"’" + 0.010*"well" + 0.007*"need" + 0.006*"Leicestershire" + 0.005*"needs" + 0.005*"understand" + 0.005*"plans" + 0.005*"family" + 0.005*"supported" + 0.005*"progress"
+2024-10-14 08:41:59,576 - topic diff=0.810744, rho=1.000000
+2024-10-14 08:41:59,576 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:41:59.576108', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:00,511 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:42:00,511 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:00,512 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:42:00,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:00,512 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:42:00,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:00,512 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:42:00,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:00,513 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:42:00,513 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:00,513 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:42:00,513 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:13,043 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:42:13,046 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)
+2024-10-14 08:42:13,046 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-10-14T08:42:13.046242', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:13,047 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:42:13,047 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:42:13,047 - using serial LDA version on this node
+2024-10-14 08:42:13,048 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:42:13,048 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:42:13,052 - -8.193 per-word bound, 292.6 perplexity estimate based on a held-out corpus of 1 documents with 2927 words
+2024-10-14 08:42:13,052 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:42:13,053 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"Lincolnshire" + 0.006*"well" + 0.004*"family" + 0.004*"28" + 0.004*"plans" + 0.004*"offer" + 0.004*"progress" + 0.004*"education"
+2024-10-14 08:42:13,054 - topic #1 (0.333): 0.027*"’" + 0.008*"Lincolnshire" + 0.008*"needs" + 0.006*"plans" + 0.006*"progress" + 0.005*"well" + 0.005*"family" + 0.005*"24" + 0.004*"need" + 0.004*"28"
+2024-10-14 08:42:13,054 - topic #2 (0.333): 0.019*"’" + 0.008*"Lincolnshire" + 0.006*"well" + 0.005*"needs" + 0.004*"2023" + 0.004*"‘" + 0.004*"progress" + 0.004*"education" + 0.003*"plans" + 0.003*"24"
+2024-10-14 08:42:13,054 - topic diff=0.790152, rho=1.000000
+2024-10-14 08:42:13,054 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1323, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:42:13.054510', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:13,959 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:42:13,959 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:13,960 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:42:13,960 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:13,960 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:42:13,960 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:13,960 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:42:13,960 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:13,960 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:42:13,960 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:13,960 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:42:13,961 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:25,780 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:42:25,783 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
+2024-10-14 08:42:25,783 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-10-14T08:42:25.783301', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:25,784 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:42:25,784 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:42:25,784 - using serial LDA version on this node
+2024-10-14 08:42:25,785 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:42:25,785 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:42:25,788 - -7.990 per-word bound, 254.3 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
+2024-10-14 08:42:25,788 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:42:25,790 - topic #0 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"always" + 0.006*"Liverpool" + 0.006*"practice" + 0.006*"quality" + 0.006*"need" + 0.005*"PAs" + 0.005*"timely" + 0.005*"protection"
+2024-10-14 08:42:25,790 - topic #1 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"practice" + 0.006*"need" + 0.005*"Liverpool" + 0.005*"quality" + 0.005*"24" + 0.004*"protection" + 0.004*"including" + 0.004*"PAs"
+2024-10-14 08:42:25,791 - topic #2 (0.333): 0.023*"’" + 0.007*"need" + 0.007*"practice" + 0.007*"needs" + 0.007*"always" + 0.005*"24" + 0.005*"Liverpool" + 0.005*"quality" + 0.005*"protection" + 0.004*"met"
+2024-10-14 08:42:25,791 - topic diff=0.839057, rho=1.000000
+2024-10-14 08:42:25,791 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1134, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:42:25.791320', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:26,715 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:42:26,715 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:26,715 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:42:26,715 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:26,716 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:42:26,716 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:26,716 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:42:26,716 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:26,716 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:42:26,716 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:26,716 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:42:26,716 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:38,151 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:42:38,155 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)
+2024-10-14 08:42:38,155 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-10-14T08:42:38.155914', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:38,157 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:42:38,157 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:42:38,157 - using serial LDA version on this node
+2024-10-14 08:42:38,157 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:42:38,157 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:42:38,161 - -8.097 per-word bound, 273.8 perplexity estimate based on a held-out corpus of 1 documents with 2610 words
+2024-10-14 08:42:38,161 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:42:38,163 - topic #0 (0.333): 0.021*"’" + 0.010*"needs" + 0.007*"good" + 0.006*"plans" + 0.006*"carers" + 0.005*"London" + 0.005*"21" + 0.005*"practice" + 0.004*"Barking" + 0.004*"e"
+2024-10-14 08:42:38,163 - topic #1 (0.333): 0.024*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"information" + 0.005*"plans" + 0.005*"progress" + 0.005*"practice" + 0.004*"timely" + 0.004*"Dagenham" + 0.004*"ensure"
+2024-10-14 08:42:38,163 - topic #2 (0.333): 0.021*"’" + 0.006*"needs" + 0.006*"good" + 0.005*"progress" + 0.005*"well" + 0.005*"10" + 0.005*"plans" + 0.005*"practice" + 0.005*"planning" + 0.005*"carers"
+2024-10-14 08:42:38,163 - topic diff=0.799752, rho=1.000000
+2024-10-14 08:42:38,163 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1193, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:42:38.163647', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:39,063 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:42:39,063 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:39,063 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:42:39,063 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:39,063 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:42:39,063 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:39,063 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:42:39,063 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:39,064 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:42:39,064 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:39,064 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:42:39,064 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:49,824 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:42:49,826 - built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)
+2024-10-14 08:42:49,826 - Dictionary lifecycle event {'msg': "built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)", 'datetime': '2024-10-14T08:42:49.826758', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:49,827 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:42:49,827 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:42:49,828 - using serial LDA version on this node
+2024-10-14 08:42:49,828 - 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
+2024-10-14 08:42:49,828 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:42:49,832 - -8.052 per-word bound, 265.4 perplexity estimate based on a held-out corpus of 1 documents with 2445 words
+2024-10-14 08:42:49,832 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:42:49,833 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.008*"Barnet" + 0.006*"plans" + 0.006*"well" + 0.005*"experiences" + 0.004*"effective" + 0.004*"2024" + 0.004*"June" + 0.004*"risk"
+2024-10-14 08:42:49,833 - topic #1 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"plans" + 0.007*"needs" + 0.006*"Barnet" + 0.005*"strong" + 0.004*"risk" + 0.004*"experiences" + 0.004*"effective" + 0.004*"14"
+2024-10-14 08:42:49,833 - topic #2 (0.333): 0.024*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"Barnet" + 0.007*"plans" + 0.005*"10" + 0.004*"understand" + 0.004*"experiences" + 0.004*"14" + 0.004*"parents"
+2024-10-14 08:42:49,834 - topic diff=0.792046, rho=1.000000
+2024-10-14 08:42:49,834 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1132, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:42:49.834117', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:42:50,742 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:42:50,742 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:50,742 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:42:50,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:50,743 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:42:50,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:50,743 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:42:50,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:50,743 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:42:50,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:42:50,743 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:42:50,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:02,154 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:43:02,156 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)
+2024-10-14 08:43:02,157 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-10-14T08:43:02.157042', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:02,158 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:43:02,158 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:43:02,158 - using serial LDA version on this node
+2024-10-14 08:43:02,158 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:43:02,158 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:43:02,162 - -8.094 per-word bound, 273.3 perplexity estimate based on a held-out corpus of 1 documents with 2563 words
+2024-10-14 08:43:02,162 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:43:02,164 - topic #0 (0.333): 0.020*"’" + 0.005*"needs" + 0.005*"well" + 0.005*"Bexley" + 0.005*"plans" + 0.004*"10" + 0.004*"6" + 0.004*"make" + 0.004*"including" + 0.004*"effective"
+2024-10-14 08:43:02,164 - topic #1 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"Bexley" + 0.005*"well" + 0.005*"effective" + 0.005*"need" + 0.004*"plans" + 0.004*"10" + 0.004*"including" + 0.004*"oversight"
+2024-10-14 08:43:02,164 - topic #2 (0.333): 0.022*"’" + 0.007*"well" + 0.007*"need" + 0.007*"needs" + 0.007*"effective" + 0.006*"plans" + 0.005*"practice" + 0.005*"progress" + 0.005*"Bexley" + 0.005*"make"
+2024-10-14 08:43:02,164 - topic diff=0.788448, rho=1.000000
+2024-10-14 08:43:02,164 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1190, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:43:02.164624', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:03,113 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:43:03,113 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:03,114 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:43:03,114 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:03,114 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:43:03,114 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:03,114 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:43:03,114 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:03,114 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:43:03,114 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:03,114 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:43:03,114 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:13,122 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:43:13,124 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)
+2024-10-14 08:43:13,124 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-10-14T08:43:13.124917', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:13,125 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:43:13,126 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:43:13,126 - using serial LDA version on this node
+2024-10-14 08:43:13,126 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:43:13,126 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:43:13,130 - -7.928 per-word bound, 243.5 perplexity estimate based on a held-out corpus of 1 documents with 2371 words
+2024-10-14 08:43:13,130 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:43:13,131 - topic #0 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"plans" + 0.006*"leaders" + 0.006*"progress" + 0.006*"senior" + 0.006*"However" + 0.005*"quality" + 0.005*"good" + 0.005*"Brent"
+2024-10-14 08:43:13,132 - topic #1 (0.333): 0.014*"’" + 0.007*"leaders" + 0.006*"progress" + 0.006*"good" + 0.006*"plans" + 0.006*"well" + 0.005*"needs" + 0.005*"senior" + 0.005*"Brent" + 0.005*"quality"
+2024-10-14 08:43:13,132 - topic #2 (0.333): 0.019*"’" + 0.010*"well" + 0.007*"leaders" + 0.007*"progress" + 0.006*"number" + 0.006*"plans" + 0.006*"practice" + 0.006*"Brent" + 0.006*"quality" + 0.006*"good"
+2024-10-14 08:43:13,132 - topic diff=0.824346, rho=1.000000
+2024-10-14 08:43:13,132 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:43:13.132435', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:14,035 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:43:14,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:14,036 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:43:14,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:14,036 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:43:14,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:14,036 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:43:14,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:14,037 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:43:14,037 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:14,037 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:43:14,037 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:26,385 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:43:26,387 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)
+2024-10-14 08:43:26,388 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-10-14T08:43:26.388047', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:26,389 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:43:26,389 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:43:26,389 - using serial LDA version on this node
+2024-10-14 08:43:26,390 - 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
+2024-10-14 08:43:26,390 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:43:26,394 - -8.182 per-word bound, 290.4 perplexity estimate based on a held-out corpus of 1 documents with 2640 words
+2024-10-14 08:43:26,394 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:43:26,395 - topic #0 (0.333): 0.016*"’" + 0.008*"Bromley" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.005*"education" + 0.004*"leaders" + 0.004*"practice" + 0.004*"health" + 0.004*"13"
+2024-10-14 08:43:26,396 - topic #1 (0.333): 0.023*"’" + 0.010*"Bromley" + 0.007*"needs" + 0.007*"well" + 0.006*"leaders" + 0.005*"health" + 0.005*"practice" + 0.005*"17" + 0.005*"plans" + 0.004*"helping"
+2024-10-14 08:43:26,396 - topic #2 (0.333): 0.019*"’" + 0.009*"Bromley" + 0.006*"well" + 0.006*"plans" + 0.006*"needs" + 0.005*"leaders" + 0.005*"practice" + 0.004*"education" + 0.004*"YPAs" + 0.004*"strong"
+2024-10-14 08:43:26,396 - topic diff=0.772661, rho=1.000000
+2024-10-14 08:43:26,396 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1266, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:43:26.396398', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:27,389 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:43:27,389 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:27,389 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:43:27,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:27,390 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:43:27,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:27,390 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:43:27,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:27,390 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:43:27,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:27,390 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:43:27,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:35,372 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:43:35,374 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)
+2024-10-14 08:43:35,374 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-10-14T08:43:35.374299', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:35,375 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:43:35,375 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:43:35,375 - using serial LDA version on this node
+2024-10-14 08:43:35,375 - 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
+2024-10-14 08:43:35,375 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:43:35,379 - -8.064 per-word bound, 267.6 perplexity estimate based on a held-out corpus of 1 documents with 1735 words
+2024-10-14 08:43:35,379 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:43:35,380 - topic #0 (0.333): 0.010*"’" + 0.007*"Camden" + 0.006*"needs" + 0.006*"well" + 0.005*"protection" + 0.005*"leaders" + 0.005*"29" + 0.005*"practice" + 0.005*"appropriate" + 0.004*"response"
+2024-10-14 08:43:35,380 - topic #1 (0.333): 0.011*"’" + 0.008*"Camden" + 0.007*"leaders" + 0.007*"practice" + 0.005*"well" + 0.005*"protection" + 0.004*"25" + 0.004*"response" + 0.004*"appropriate" + 0.004*"needs"
+2024-10-14 08:43:35,380 - topic #2 (0.333): 0.011*"’" + 0.006*"leaders" + 0.006*"practice" + 0.005*"Camden" + 0.005*"well" + 0.005*"response" + 0.005*"needs" + 0.004*"meetings" + 0.004*"progress" + 0.004*"protection"
+2024-10-14 08:43:35,380 - topic diff=0.699915, rho=1.000000
+2024-10-14 08:43:35,381 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=993, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:43:35.381053', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:36,289 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:43:36,290 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:36,290 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:43:36,290 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:36,290 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:43:36,290 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:36,290 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:43:36,290 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:36,291 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:43:36,291 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:36,291 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:43:36,291 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:46,471 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:43:46,473 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)
+2024-10-14 08:43:46,473 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-10-14T08:43:46.473487', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:46,474 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:43:46,474 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:43:46,474 - using serial LDA version on this node
+2024-10-14 08:43:46,475 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:43:46,475 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:43:46,478 - -7.986 per-word bound, 253.5 perplexity estimate based on a held-out corpus of 1 documents with 2209 words
+2024-10-14 08:43:46,478 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:43:46,479 - topic #0 (0.333): 0.015*"’" + 0.009*"well" + 0.007*"needs" + 0.005*"Croydon" + 0.005*"good" + 0.005*"ensure" + 0.005*"education" + 0.005*"risk" + 0.005*"plans" + 0.005*"improved"
+2024-10-14 08:43:46,480 - topic #1 (0.333): 0.007*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"need" + 0.005*"quality" + 0.005*"Croydon" + 0.005*"Senior" + 0.005*"ensure" + 0.004*"effective" + 0.004*"plans"
+2024-10-14 08:43:46,480 - topic #2 (0.333): 0.012*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"Senior" + 0.006*"Croydon" + 0.006*"quality" + 0.006*"need" + 0.005*"health" + 0.005*"good" + 0.005*"risk"
+2024-10-14 08:43:46,480 - topic diff=0.769191, rho=1.000000
+2024-10-14 08:43:46,480 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:43:46.480368', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:47,499 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:43:47,499 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:47,500 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:43:47,500 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:47,500 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:43:47,500 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:47,500 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:43:47,500 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:47,500 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:43:47,500 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:47,501 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:43:47,501 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:58,241 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:43:58,244 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)
+2024-10-14 08:43:58,244 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)", 'datetime': '2024-10-14T08:43:58.244212', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:58,245 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:43:58,245 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:43:58,245 - using serial LDA version on this node
+2024-10-14 08:43:58,246 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:43:58,246 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:43:58,249 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2365 words
+2024-10-14 08:43:58,249 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:43:58,251 - topic #0 (0.333): 0.020*"’" + 0.009*"Ealing" + 0.009*"well" + 0.007*"needs" + 0.006*"progress" + 0.006*"effective" + 0.006*"3" + 0.006*"plans" + 0.005*"London" + 0.005*"good"
+2024-10-14 08:43:58,251 - topic #1 (0.333): 0.015*"’" + 0.008*"Ealing" + 0.007*"well" + 0.006*"plans" + 0.006*"progress" + 0.005*"needs" + 0.005*"need" + 0.004*"including" + 0.004*"London" + 0.004*"effective"
+2024-10-14 08:43:58,251 - topic #2 (0.333): 0.015*"’" + 0.007*"Ealing" + 0.005*"well" + 0.005*"need" + 0.005*"progress" + 0.004*"plans" + 0.004*"22" + 0.004*"health" + 0.004*"effective" + 0.004*"experiences"
+2024-10-14 08:43:58,251 - topic diff=0.794744, rho=1.000000
+2024-10-14 08:43:58,251 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:43:58.251730', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:43:59,195 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:43:59,195 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:59,195 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:43:59,195 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:59,195 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:43:59,195 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:59,195 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:43:59,195 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:59,196 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:43:59,196 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:43:59,196 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:43:59,196 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:09,791 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:44:09,794 - built Dictionary<1108 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
+2024-10-14 08:44:09,794 - Dictionary lifecycle event {'msg': "built Dictionary<1108 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-10-14T08:44:09.794226', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:09,795 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:44:09,795 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:44:09,795 - using serial LDA version on this node
+2024-10-14 08:44:09,796 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:44:09,796 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:44:09,799 - -7.997 per-word bound, 255.5 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
+2024-10-14 08:44:09,799 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:44:09,800 - topic #0 (0.333): 0.022*"’" + 0.011*"needs" + 0.008*"well" + 0.007*"Enfield" + 0.006*"plans" + 0.006*"practice" + 0.005*"timely" + 0.005*"need" + 0.005*"education" + 0.004*"good"
+2024-10-14 08:44:09,801 - topic #1 (0.333): 0.016*"’" + 0.012*"needs" + 0.010*"well" + 0.008*"plans" + 0.008*"Enfield" + 0.007*"need" + 0.006*"receive" + 0.005*"timely" + 0.005*"protection" + 0.005*"practice"
+2024-10-14 08:44:09,801 - topic #2 (0.333): 0.011*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"Enfield" + 0.006*"plans" + 0.005*"receive" + 0.004*"need" + 0.004*"education" + 0.004*"good" + 0.004*"July"
+2024-10-14 08:44:09,801 - topic diff=0.805773, rho=1.000000
+2024-10-14 08:44:09,801 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1108, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:44:09.801368', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:10,731 - Inspection date 2024-07-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:44:10,731 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:10,732 - Inspection date 2024-07-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:44:10,732 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:10,732 - Inspection date 2024-07-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:44:10,732 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:10,732 - Inspection date 2024-07-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:44:10,732 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:10,732 - Inspection date 2024-07-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:44:10,732 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:10,733 - Inspection date 2024-07-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:44:10,733 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:20,819 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:44:20,821 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)
+2024-10-14 08:44:20,821 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)", 'datetime': '2024-10-14T08:44:20.821608', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:20,822 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:44:20,822 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:44:20,822 - using serial LDA version on this node
+2024-10-14 08:44:20,823 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:44:20,823 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:44:20,826 - -7.985 per-word bound, 253.4 perplexity estimate based on a held-out corpus of 1 documents with 2078 words
+2024-10-14 08:44:20,826 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:44:20,827 - topic #0 (0.333): 0.018*"’" + 0.010*"Greenwich" + 0.007*"needs" + 0.007*"well" + 0.006*"plans" + 0.005*"3" + 0.005*"progress" + 0.005*"provide" + 0.004*"7" + 0.004*"Royal"
+2024-10-14 08:44:20,828 - topic #1 (0.333): 0.015*"’" + 0.011*"Greenwich" + 0.007*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"7" + 0.005*"3" + 0.005*"progress" + 0.004*"2024" + 0.004*"Royal"
+2024-10-14 08:44:20,828 - topic #2 (0.333): 0.019*"’" + 0.011*"Greenwich" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.005*"June" + 0.005*"provide" + 0.004*"2024" + 0.004*"quality" + 0.004*"Borough"
+2024-10-14 08:44:20,828 - topic diff=0.755078, rho=1.000000
+2024-10-14 08:44:20,828 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:44:20.828522', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:21,700 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:44:21,700 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:21,701 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:44:21,701 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:21,701 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:44:21,701 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:21,701 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:44:21,701 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:21,701 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:44:21,701 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:21,702 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:44:21,702 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:34,126 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:44:34,128 - built Dictionary<1222 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2748 corpus positions)
+2024-10-14 08:44:34,129 - Dictionary lifecycle event {'msg': 'built Dictionary<1222 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2748 corpus positions)', 'datetime': '2024-10-14T08:44:34.129150', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:34,130 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:44:34,130 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:44:34,130 - using serial LDA version on this node
+2024-10-14 08:44:34,131 - 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
+2024-10-14 08:44:34,131 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:44:34,134 - -8.103 per-word bound, 275.0 perplexity estimate based on a held-out corpus of 1 documents with 2748 words
+2024-10-14 08:44:34,135 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:44:34,136 - topic #0 (0.333): 0.016*"’" + 0.009*"Hackney" + 0.008*"needs" + 0.006*"carers" + 0.005*"well" + 0.005*"1" + 0.004*"need" + 0.004*"leaders" + 0.004*"education" + 0.004*"Leaders"
+2024-10-14 08:44:34,136 - topic #1 (0.333): 0.018*"’" + 0.009*"Hackney" + 0.007*"needs" + 0.006*"carers" + 0.006*"12" + 0.005*"need" + 0.005*"well" + 0.005*"practice" + 0.005*"timely" + 0.004*"leaders"
+2024-10-14 08:44:34,136 - topic #2 (0.333): 0.018*"’" + 0.009*"Hackney" + 0.009*"needs" + 0.006*"well" + 0.005*"effective" + 0.005*"12" + 0.004*"July" + 0.004*"timely" + 0.004*"practice" + 0.004*"2024"
+2024-10-14 08:44:34,136 - topic diff=0.800796, rho=1.000000
+2024-10-14 08:44:34,136 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1222, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:44:34.136954', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:35,045 - Inspection date 2024-07-01 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:44:35,045 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:35,045 - Inspection date 2024-07-01 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:44:35,045 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:35,045 - Inspection date 2024-07-01 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:44:35,046 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:35,046 - Inspection date 2024-07-01 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:44:35,046 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:35,046 - Inspection date 2024-07-01 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:44:35,046 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:35,046 - Inspection date 2024-07-01 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:44:35,046 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:47,877 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:44:47,881 - built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
+2024-10-14 08:44:47,881 - Dictionary lifecycle event {'msg': "built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-10-14T08:44:47.881196', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:47,882 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:44:47,882 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:44:47,882 - using serial LDA version on this node
+2024-10-14 08:44:47,883 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:44:47,883 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:44:47,887 - -8.203 per-word bound, 294.6 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
+2024-10-14 08:44:47,887 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:44:47,889 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"needs" + 0.006*"receive" + 0.005*"practice" + 0.005*"Hammersmith" + 0.005*"place" + 0.004*"leaders" + 0.004*"15" + 0.004*"Fulham"
+2024-10-14 08:44:47,889 - topic #1 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"receive" + 0.005*"needs" + 0.005*"protection" + 0.004*"leaders" + 0.004*"Leaders" + 0.004*"supported" + 0.004*"2024" + 0.004*"Fulham"
+2024-10-14 08:44:47,889 - topic #2 (0.333): 0.012*"’" + 0.007*"well" + 0.005*"plans" + 0.005*"receive" + 0.004*"Fulham" + 0.004*"effective" + 0.004*"Hammersmith" + 0.004*"needs" + 0.004*"2024" + 0.004*"March"
+2024-10-14 08:44:47,889 - topic diff=0.796885, rho=1.000000
+2024-10-14 08:44:47,889 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1330, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:44:47.889588', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:44:48,778 - Inspection date 2024-03-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:44:48,778 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:48,778 - Inspection date 2024-03-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:44:48,778 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:48,778 - Inspection date 2024-03-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:44:48,778 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:48,778 - Inspection date 2024-03-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:44:48,779 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:48,779 - Inspection date 2024-03-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:44:48,779 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:44:48,779 - Inspection date 2024-03-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:44:48,779 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:00,539 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:45:00,542 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)
+2024-10-14 08:45:00,542 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-10-14T08:45:00.542416', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:00,543 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:45:00,543 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:45:00,543 - using serial LDA version on this node
+2024-10-14 08:45:00,544 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:45:00,544 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:45:00,548 - -8.170 per-word bound, 288.0 perplexity estimate based on a held-out corpus of 1 documents with 2620 words
+2024-10-14 08:45:00,548 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:45:00,549 - topic #0 (0.333): 0.017*"’" + 0.011*"Haringey" + 0.009*"needs" + 0.007*"plans" + 0.006*"well" + 0.005*"good" + 0.005*"progress" + 0.005*"education" + 0.005*"need" + 0.004*"impact"
+2024-10-14 08:45:00,549 - topic #1 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"plans" + 0.006*"well" + 0.006*"Haringey" + 0.005*"progress" + 0.005*"need" + 0.004*"timely" + 0.004*"good" + 0.004*"risk"
+2024-10-14 08:45:00,550 - topic #2 (0.333): 0.015*"’" + 0.007*"Haringey" + 0.006*"plans" + 0.006*"needs" + 0.006*"good" + 0.005*"need" + 0.005*"well" + 0.004*"education" + 0.004*"progress" + 0.004*"risk"
+2024-10-14 08:45:00,550 - topic diff=0.776474, rho=1.000000
+2024-10-14 08:45:00,550 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1252, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:45:00.550307', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:01,459 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:45:01,460 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:01,460 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:45:01,460 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:01,460 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:45:01,460 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:01,460 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:45:01,460 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:01,461 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:45:01,461 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:01,461 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:45:01,461 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:09,367 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:45:09,369 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)
+2024-10-14 08:45:09,369 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-10-14T08:45:09.369333', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:09,370 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:45:09,370 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:45:09,370 - using serial LDA version on this node
+2024-10-14 08:45:09,370 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:45:09,370 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:45:09,374 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 1732 words
+2024-10-14 08:45:09,374 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:45:09,375 - topic #0 (0.333): 0.016*"’" + 0.013*"good" + 0.009*"well" + 0.008*"needs" + 0.007*"impact" + 0.006*"plans" + 0.006*"protection" + 0.006*"need" + 0.005*"practice" + 0.005*"experiences"
+2024-10-14 08:45:09,375 - topic #1 (0.333): 0.009*"good" + 0.008*"well" + 0.008*"needs" + 0.006*"’" + 0.005*"plans" + 0.004*"need" + 0.004*"Harrow" + 0.004*"impact" + 0.004*"early" + 0.004*"experiences"
+2024-10-14 08:45:09,375 - topic #2 (0.333): 0.010*"’" + 0.008*"needs" + 0.008*"well" + 0.007*"good" + 0.005*"practice" + 0.005*"early" + 0.005*"experiences" + 0.005*"protection" + 0.004*"plans" + 0.004*"need"
+2024-10-14 08:45:09,375 - topic diff=0.713502, rho=1.000000
+2024-10-14 08:45:09,376 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=942, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:45:09.376060', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:11,218 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:45:11,218 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:11,218 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:45:11,218 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:11,218 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:45:11,218 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:11,219 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:45:11,219 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:11,219 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:45:11,219 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:11,219 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:45:11,219 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:21,481 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:45:21,484 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)
+2024-10-14 08:45:21,484 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-10-14T08:45:21.484418', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:21,485 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:45:21,485 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:45:21,485 - using serial LDA version on this node
+2024-10-14 08:45:21,486 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:45:21,486 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:45:21,489 - -8.013 per-word bound, 258.3 perplexity estimate based on a held-out corpus of 1 documents with 2243 words
+2024-10-14 08:45:21,489 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:45:21,491 - topic #0 (0.333): 0.011*"’" + 0.010*"Havering" + 0.006*"quality" + 0.006*"plans" + 0.005*"oversight" + 0.004*"needs" + 0.004*"effective" + 0.004*"well" + 0.003*"many" + 0.003*"2023"
+2024-10-14 08:45:21,491 - topic #1 (0.333): 0.019*"’" + 0.010*"Havering" + 0.009*"quality" + 0.007*"plans" + 0.006*"effective" + 0.005*"11" + 0.005*"oversight" + 0.005*"needs" + 0.004*"well" + 0.004*"December"
+2024-10-14 08:45:21,491 - topic #2 (0.333): 0.021*"’" + 0.013*"Havering" + 0.010*"quality" + 0.007*"plans" + 0.005*"oversight" + 0.005*"effective" + 0.005*"22" + 0.005*"practice" + 0.005*"needs" + 0.004*"2023"
+2024-10-14 08:45:21,491 - topic diff=0.776074, rho=1.000000
+2024-10-14 08:45:21,491 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:45:21.491541', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:22,377 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:45:22,377 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:22,377 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:45:22,377 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:22,377 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:45:22,377 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:22,378 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:45:22,378 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:22,378 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:45:22,378 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:22,378 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:45:22,378 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:32,898 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:45:32,901 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)
+2024-10-14 08:45:32,901 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-10-14T08:45:32.901589', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:32,902 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:45:32,902 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:45:32,903 - using serial LDA version on this node
+2024-10-14 08:45:32,903 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:45:32,903 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:45:32,907 - -8.072 per-word bound, 269.1 perplexity estimate based on a held-out corpus of 1 documents with 2511 words
+2024-10-14 08:45:32,907 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:45:32,908 - topic #0 (0.333): 0.018*"’" + 0.009*"needs" + 0.009*"well" + 0.008*"plans" + 0.008*"Hillingdon" + 0.004*"6" + 0.004*"need" + 0.004*"2" + 0.004*"team" + 0.004*"2023"
+2024-10-14 08:45:32,908 - topic #1 (0.333): 0.010*"’" + 0.008*"needs" + 0.006*"well" + 0.006*"Hillingdon" + 0.006*"plans" + 0.005*"team" + 0.004*"experiences" + 0.004*"leaders" + 0.004*"need" + 0.003*"2"
+2024-10-14 08:45:32,908 - topic #2 (0.333): 0.022*"’" + 0.010*"needs" + 0.008*"Hillingdon" + 0.008*"plans" + 0.007*"well" + 0.005*"team" + 0.005*"need" + 0.005*"2" + 0.005*"6" + 0.004*"PAs"
+2024-10-14 08:45:32,909 - topic diff=0.798553, rho=1.000000
+2024-10-14 08:45:32,909 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:45:32.909166', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:33,861 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:45:33,861 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:33,862 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:45:33,862 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:33,862 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:45:33,862 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:33,862 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:45:33,862 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:33,862 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:45:33,862 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:33,863 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:45:33,863 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:45,114 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:45:45,116 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)
+2024-10-14 08:45:45,116 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-10-14T08:45:45.116927', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:45,117 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:45:45,118 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:45:45,118 - using serial LDA version on this node
+2024-10-14 08:45:45,118 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:45:45,118 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:45:45,122 - -7.997 per-word bound, 255.5 perplexity estimate based on a held-out corpus of 1 documents with 2271 words
+2024-10-14 08:45:45,122 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:45:45,123 - topic #0 (0.333): 0.021*"’" + 0.009*"needs" + 0.009*"well" + 0.008*"effective" + 0.007*"Hounslow" + 0.006*"plans" + 0.005*"strong" + 0.005*"timely" + 0.005*"experiences" + 0.005*"20"
+2024-10-14 08:45:45,123 - topic #1 (0.333): 0.024*"’" + 0.013*"needs" + 0.010*"well" + 0.008*"effective" + 0.008*"timely" + 0.007*"Hounslow" + 0.005*"plans" + 0.005*"education" + 0.005*"oversight" + 0.004*"progress"
+2024-10-14 08:45:45,123 - topic #2 (0.333): 0.011*"well" + 0.010*"needs" + 0.009*"’" + 0.006*"Hounslow" + 0.005*"effective" + 0.005*"16" + 0.005*"timely" + 0.004*"plans" + 0.004*"appropriate" + 0.004*"progress"
+2024-10-14 08:45:45,123 - topic diff=0.792595, rho=1.000000
+2024-10-14 08:45:45,124 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1070, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:45:45.124081', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:46,053 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:45:46,053 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:46,053 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:45:46,053 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:46,053 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:45:46,053 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:46,054 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:45:46,054 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:46,054 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:45:46,054 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:46,054 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:45:46,054 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:54,473 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:45:54,475 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)
+2024-10-14 08:45:54,476 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-10-14T08:45:54.476128', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:54,477 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:45:54,477 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:45:54,477 - using serial LDA version on this node
+2024-10-14 08:45:54,477 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:45:54,477 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:45:54,480 - -7.925 per-word bound, 243.0 perplexity estimate based on a held-out corpus of 1 documents with 1982 words
+2024-10-14 08:45:54,481 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:45:54,482 - topic #0 (0.333): 0.011*"’" + 0.010*"well" + 0.009*"needs" + 0.006*"plans" + 0.006*"highly" + 0.006*"good" + 0.006*"effective" + 0.005*"quality" + 0.005*"leaders" + 0.005*"Islington"
+2024-10-14 08:45:54,482 - topic #1 (0.333): 0.015*"’" + 0.010*"well" + 0.010*"needs" + 0.007*"plans" + 0.006*"quality" + 0.005*"risk" + 0.005*"leaders" + 0.005*"good" + 0.005*"highly" + 0.005*"Senior"
+2024-10-14 08:45:54,482 - topic #2 (0.333): 0.014*"needs" + 0.012*"’" + 0.011*"well" + 0.006*"good" + 0.006*"plans" + 0.006*"highly" + 0.005*"quality" + 0.005*"Islington" + 0.005*"effective" + 0.005*"practice"
+2024-10-14 08:45:54,482 - topic diff=0.736633, rho=1.000000
+2024-10-14 08:45:54,482 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:45:54.482687', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:45:56,245 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:45:56,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:56,246 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:45:56,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:56,246 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:45:56,247 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:56,247 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:45:56,247 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:56,247 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:45:56,247 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:45:56,247 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:45:56,247 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:07,127 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:46:07,129 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)
+2024-10-14 08:46:07,129 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-10-14T08:46:07.129895', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:07,130 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:46:07,130 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:46:07,131 - using serial LDA version on this node
+2024-10-14 08:46:07,131 - 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
+2024-10-14 08:46:07,131 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:46:07,134 - -7.910 per-word bound, 240.5 perplexity estimate based on a held-out corpus of 1 documents with 2090 words
+2024-10-14 08:46:07,134 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:46:07,136 - topic #0 (0.333): 0.013*"’" + 0.009*"well" + 0.007*"needs" + 0.007*"good" + 0.006*"plans" + 0.006*"leaders" + 0.006*"impact" + 0.005*"Lambeth" + 0.005*"progress" + 0.005*"Leaders"
+2024-10-14 08:46:07,136 - topic #1 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"Lambeth" + 0.007*"plans" + 0.007*"good" + 0.006*"need" + 0.006*"impact" + 0.005*"progress" + 0.005*"carers"
+2024-10-14 08:46:07,136 - topic #2 (0.333): 0.018*"’" + 0.010*"needs" + 0.009*"plans" + 0.008*"well" + 0.006*"progress" + 0.006*"need" + 0.006*"good" + 0.006*"Lambeth" + 0.005*"leaders" + 0.005*"4"
+2024-10-14 08:46:07,136 - topic diff=0.801435, rho=1.000000
+2024-10-14 08:46:07,136 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:46:07.136640', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:08,040 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:46:08,040 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:08,040 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:46:08,041 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:08,041 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:46:08,041 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:08,041 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:46:08,041 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:08,041 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:46:08,041 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:08,041 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:46:08,041 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:18,943 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:46:18,947 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)
+2024-10-14 08:46:18,947 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-10-14T08:46:18.947526', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:18,949 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:46:18,949 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:46:18,950 - using serial LDA version on this node
+2024-10-14 08:46:18,950 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:46:18,950 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:46:18,955 - -8.050 per-word bound, 265.0 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
+2024-10-14 08:46:18,956 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:46:18,957 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"effective" + 0.006*"Lewisham" + 0.005*"plans" + 0.005*"4" + 0.005*"progress" + 0.005*"good" + 0.005*"ensure"
+2024-10-14 08:46:18,957 - topic #1 (0.333): 0.010*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"effective" + 0.006*"Lewisham" + 0.005*"plans" + 0.004*"4" + 0.004*"2023" + 0.004*"arrangements" + 0.004*"health"
+2024-10-14 08:46:18,957 - topic #2 (0.333): 0.021*"’" + 0.009*"well" + 0.009*"plans" + 0.007*"needs" + 0.006*"effective" + 0.006*"Lewisham" + 0.005*"progress" + 0.005*"arrangements" + 0.005*"good" + 0.005*"receive"
+2024-10-14 08:46:18,957 - topic diff=0.776953, rho=1.000000
+2024-10-14 08:46:18,958 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:46:18.958050', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:19,837 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:46:19,837 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:19,837 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:46:19,837 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:19,838 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:46:19,838 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:19,838 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:46:19,838 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:19,838 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:46:19,838 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:19,839 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:46:19,839 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:28,962 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:46:28,964 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)
+2024-10-14 08:46:28,964 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-10-14T08:46:28.964725', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:28,965 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:46:28,965 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:46:28,966 - using serial LDA version on this node
+2024-10-14 08:46:28,966 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:46:28,966 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:46:28,969 - -7.990 per-word bound, 254.3 perplexity estimate based on a held-out corpus of 1 documents with 2032 words
+2024-10-14 08:46:28,969 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:46:28,971 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.006*"Merton" + 0.005*"plans" + 0.005*"needs" + 0.005*"progress" + 0.004*"family" + 0.004*"education" + 0.004*"health" + 0.004*"March"
+2024-10-14 08:46:28,971 - topic #1 (0.333): 0.016*"’" + 0.007*"Merton" + 0.007*"well" + 0.005*"needs" + 0.004*"ensure" + 0.004*"family" + 0.004*"4" + 0.004*"information" + 0.004*"good" + 0.004*"progress"
+2024-10-14 08:46:28,971 - topic #2 (0.333): 0.017*"’" + 0.009*"well" + 0.006*"needs" + 0.006*"Merton" + 0.005*"plans" + 0.004*"ensure" + 0.004*"family" + 0.004*"good" + 0.004*"across" + 0.004*"progress"
+2024-10-14 08:46:28,971 - topic diff=0.755215, rho=1.000000
+2024-10-14 08:46:28,971 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1015, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:46:28.971579', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:29,799 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:46:29,799 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:29,799 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:46:29,800 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:29,800 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:46:29,800 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:29,800 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:46:29,800 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:29,800 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:46:29,800 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:29,800 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:46:29,800 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:40,780 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:46:40,782 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)
+2024-10-14 08:46:40,782 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-10-14T08:46:40.782801', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:40,783 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:46:40,784 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:46:40,784 - using serial LDA version on this node
+2024-10-14 08:46:40,784 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:46:40,784 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:46:40,788 - -8.058 per-word bound, 266.5 perplexity estimate based on a held-out corpus of 1 documents with 2540 words
+2024-10-14 08:46:40,788 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:46:40,789 - topic #0 (0.333): 0.017*"’" + 0.008*"plans" + 0.007*"needs" + 0.007*"progress" + 0.007*"Newham" + 0.006*"practice" + 0.006*"need" + 0.005*"effective" + 0.005*"29" + 0.004*"good"
+2024-10-14 08:46:40,789 - topic #1 (0.333): 0.024*"’" + 0.010*"needs" + 0.007*"Newham" + 0.006*"practice" + 0.006*"effective" + 0.006*"need" + 0.006*"progress" + 0.005*"good" + 0.005*"plans" + 0.005*"Leaders"
+2024-10-14 08:46:40,790 - topic #2 (0.333): 0.014*"’" + 0.006*"Newham" + 0.006*"needs" + 0.006*"plans" + 0.005*"effective" + 0.005*"practice" + 0.005*"progress" + 0.005*"good" + 0.005*"need" + 0.004*"well"
+2024-10-14 08:46:40,790 - topic diff=0.780449, rho=1.000000
+2024-10-14 08:46:40,790 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1153, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:46:40.790383', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:41,764 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:46:41,764 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:41,764 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:46:41,764 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:41,765 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:46:41,765 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:41,765 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:46:41,765 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:41,765 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:46:41,765 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:41,765 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:46:41,765 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:52,116 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:46:52,121 - built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)
+2024-10-14 08:46:52,121 - Dictionary lifecycle event {'msg': "built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-10-14T08:46:52.121556', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:52,123 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:46:52,123 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:46:52,124 - using serial LDA version on this node
+2024-10-14 08:46:52,124 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:46:52,124 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:46:52,131 - -8.166 per-word bound, 287.2 perplexity estimate based on a held-out corpus of 1 documents with 2389 words
+2024-10-14 08:46:52,131 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:46:52,134 - topic #0 (0.333): 0.019*"’" + 0.007*"Redbridge" + 0.006*"practice" + 0.006*"carers" + 0.005*"supported" + 0.005*"needs" + 0.005*"10" + 0.005*"early" + 0.005*"risk" + 0.004*"leaders"
+2024-10-14 08:46:52,134 - topic #1 (0.333): 0.007*"’" + 0.006*"Redbridge" + 0.004*"needs" + 0.004*"June" + 0.004*"teams" + 0.004*"information" + 0.004*"parents" + 0.003*"protection" + 0.003*"carers" + 0.003*"supported"
+2024-10-14 08:46:52,134 - topic #2 (0.333): 0.013*"’" + 0.007*"Redbridge" + 0.005*"needs" + 0.005*"family" + 0.005*"leaders" + 0.005*"supported" + 0.005*"plans" + 0.004*"effective" + 0.004*"carers" + 0.004*"well"
+2024-10-14 08:46:52,134 - topic diff=0.770563, rho=1.000000
+2024-10-14 08:46:52,134 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1204, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:46:52.134875', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:46:53,119 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:46:53,119 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:53,120 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:46:53,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:53,120 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:46:53,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:53,120 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:46:53,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:53,120 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:46:53,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:46:53,120 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:46:53,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:01,526 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:47:01,528 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)
+2024-10-14 08:47:01,528 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-10-14T08:47:01.528656', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:01,529 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:47:01,530 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:47:01,530 - using serial LDA version on this node
+2024-10-14 08:47:01,530 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:47:01,530 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:47:01,533 - -7.987 per-word bound, 253.7 perplexity estimate based on a held-out corpus of 1 documents with 1818 words
+2024-10-14 08:47:01,533 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:47:01,535 - topic #0 (0.333): 0.018*"’" + 0.011*"well" + 0.009*"Richmond" + 0.007*"needs" + 0.006*"need" + 0.006*"good" + 0.005*"supported" + 0.005*"additional" + 0.005*"team" + 0.005*"ensure"
+2024-10-14 08:47:01,535 - topic #1 (0.333): 0.013*"’" + 0.009*"well" + 0.008*"Richmond" + 0.006*"good" + 0.006*"team" + 0.006*"needs" + 0.006*"supported" + 0.005*"ensure" + 0.004*"need" + 0.004*"4"
+2024-10-14 08:47:01,535 - topic #2 (0.333): 0.015*"’" + 0.013*"well" + 0.008*"needs" + 0.007*"Richmond" + 0.006*"supported" + 0.005*"need" + 0.005*"team" + 0.005*"strong" + 0.004*"February" + 0.004*"31"
+2024-10-14 08:47:01,535 - topic diff=0.728900, rho=1.000000
+2024-10-14 08:47:01,535 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:47:01.535852', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:02,560 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:47:02,561 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:02,561 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:47:02,561 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:02,561 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:47:02,561 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:02,562 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:47:02,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:02,562 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:47:02,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:02,562 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:47:02,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:12,027 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:47:12,029 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)
+2024-10-14 08:47:12,029 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-10-14T08:47:12.029689', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:12,030 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:47:12,030 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:47:12,030 - using serial LDA version on this node
+2024-10-14 08:47:12,031 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:47:12,031 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:47:12,034 - -7.922 per-word bound, 242.5 perplexity estimate based on a held-out corpus of 1 documents with 1878 words
+2024-10-14 08:47:12,034 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:47:12,035 - topic #0 (0.333): 0.011*"’" + 0.008*"Southwark" + 0.005*"good" + 0.005*"well" + 0.005*"needs" + 0.004*"leaders" + 0.004*"plans" + 0.004*"receive" + 0.004*"progress" + 0.004*"30"
+2024-10-14 08:47:12,035 - topic #1 (0.333): 0.015*"’" + 0.007*"Southwark" + 0.007*"good" + 0.006*"well" + 0.006*"needs" + 0.006*"progress" + 0.005*"plans" + 0.005*"Leaders" + 0.005*"effective" + 0.005*"leaders"
+2024-10-14 08:47:12,035 - topic #2 (0.333): 0.023*"’" + 0.011*"Southwark" + 0.010*"good" + 0.009*"well" + 0.009*"needs" + 0.007*"need" + 0.006*"progress" + 0.006*"strong" + 0.006*"plans" + 0.006*"effective"
+2024-10-14 08:47:12,036 - topic diff=0.763111, rho=1.000000
+2024-10-14 08:47:12,036 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=945, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:47:12.036122', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:13,203 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:47:13,204 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:13,204 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:47:13,204 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:13,204 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:47:13,204 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:13,204 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:47:13,204 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:13,205 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:47:13,205 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:13,205 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:47:13,205 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:21,225 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:47:21,227 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)
+2024-10-14 08:47:21,227 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-10-14T08:47:21.227924', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:21,228 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:47:21,228 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:47:21,229 - using serial LDA version on this node
+2024-10-14 08:47:21,229 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:47:21,229 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:47:21,232 - -7.992 per-word bound, 254.6 perplexity estimate based on a held-out corpus of 1 documents with 1847 words
+2024-10-14 08:47:21,232 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:47:21,234 - topic #0 (0.333): 0.021*"’" + 0.008*"well" + 0.007*"Sutton" + 0.006*"effective" + 0.006*"needs" + 0.006*"good" + 0.005*"progress" + 0.005*"receive" + 0.005*"6" + 0.004*"supported"
+2024-10-14 08:47:21,234 - topic #1 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"Sutton" + 0.005*"progress" + 0.005*"well" + 0.004*"need" + 0.004*"receive" + 0.004*"leaders" + 0.004*"home" + 0.004*"effective"
+2024-10-14 08:47:21,234 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.005*"needs" + 0.005*"receive" + 0.004*"Sutton" + 0.004*"good" + 0.004*"progress" + 0.004*"10" + 0.004*"6" + 0.004*"supported"
+2024-10-14 08:47:21,234 - topic diff=0.739021, rho=1.000000
+2024-10-14 08:47:21,234 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:47:21.234542', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:23,246 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:47:23,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:23,247 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:47:23,247 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:23,247 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:47:23,247 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:23,249 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:47:23,249 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:23,250 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:47:23,250 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:23,250 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:47:23,250 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:33,388 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:47:33,392 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)
+2024-10-14 08:47:33,392 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-10-14T08:47:33.392453', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:33,394 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:47:33,394 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:47:33,395 - using serial LDA version on this node
+2024-10-14 08:47:33,395 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:47:33,395 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:47:33,402 - -8.129 per-word bound, 280.0 perplexity estimate based on a held-out corpus of 1 documents with 2465 words
+2024-10-14 08:47:33,402 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:47:33,404 - topic #0 (0.333): 0.010*"’" + 0.005*"effective" + 0.005*"‘" + 0.005*"plans" + 0.005*"good" + 0.004*"need" + 0.004*"well" + 0.004*"progress" + 0.004*"practice" + 0.004*"needs"
+2024-10-14 08:47:33,405 - topic #1 (0.333): 0.019*"’" + 0.007*"good" + 0.007*"plans" + 0.006*"effective" + 0.006*"‘" + 0.006*"well" + 0.005*"early" + 0.005*"need" + 0.004*"progress" + 0.004*"practice"
+2024-10-14 08:47:33,405 - topic #2 (0.333): 0.014*"’" + 0.007*"good" + 0.006*"practice" + 0.006*"plans" + 0.006*"effective" + 0.006*"well" + 0.006*"including" + 0.006*"‘" + 0.005*"risk" + 0.005*"need"
+2024-10-14 08:47:33,405 - topic diff=0.782085, rho=1.000000
+2024-10-14 08:47:33,405 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1194, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:47:33.405605', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:34,486 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:47:34,486 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:34,487 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:47:34,487 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:34,487 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:47:34,487 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:34,487 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:47:34,487 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:34,487 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:47:34,487 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:34,488 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:47:34,488 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:45,341 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:47:45,343 - built Dictionary<1061 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2398 corpus positions)
+2024-10-14 08:47:45,344 - Dictionary lifecycle event {'msg': "built Dictionary<1061 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2398 corpus positions)", 'datetime': '2024-10-14T08:47:45.344122', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:45,345 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:47:45,345 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:47:45,345 - using serial LDA version on this node
+2024-10-14 08:47:45,345 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:47:45,345 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:47:45,349 - -7.959 per-word bound, 248.9 perplexity estimate based on a held-out corpus of 1 documents with 2398 words
+2024-10-14 08:47:45,349 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:47:45,350 - topic #0 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"plans" + 0.007*"Waltham" + 0.007*"Forest" + 0.006*"progress" + 0.005*"Leaders" + 0.004*"leaders" + 0.004*"July"
+2024-10-14 08:47:45,350 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"well" + 0.007*"plans" + 0.005*"12" + 0.005*"8" + 0.005*"Waltham" + 0.005*"leaders" + 0.005*"2024" + 0.004*"timely"
+2024-10-14 08:47:45,351 - topic #2 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"plans" + 0.006*"Forest" + 0.005*"effective" + 0.005*"Waltham" + 0.005*"leaders" + 0.005*"progress" + 0.005*"education"
+2024-10-14 08:47:45,351 - topic diff=0.785417, rho=1.000000
+2024-10-14 08:47:45,351 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1061, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:47:45.351245', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:46,323 - Inspection date 2024-07-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:47:46,323 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:46,323 - Inspection date 2024-07-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:47:46,324 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:46,324 - Inspection date 2024-07-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:47:46,324 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:46,324 - Inspection date 2024-07-08 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:47:46,324 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:46,324 - Inspection date 2024-07-08 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:47:46,324 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:46,324 - Inspection date 2024-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:47:46,325 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:54,237 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:47:54,239 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)
+2024-10-14 08:47:54,239 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-10-14T08:47:54.239563', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:54,240 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:47:54,240 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:47:54,240 - using serial LDA version on this node
+2024-10-14 08:47:54,241 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:47:54,241 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:47:54,244 - -7.852 per-word bound, 231.0 perplexity estimate based on a held-out corpus of 1 documents with 1772 words
+2024-10-14 08:47:54,244 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:47:54,245 - topic #0 (0.333): 0.008*"’" + 0.006*"progress" + 0.005*"protection" + 0.005*"well" + 0.005*"Senior" + 0.005*"effective" + 0.005*"needs" + 0.004*"supported" + 0.004*"practice" + 0.004*"Wandsworth"
+2024-10-14 08:47:54,245 - topic #1 (0.333): 0.009*"’" + 0.007*"needs" + 0.007*"well" + 0.005*"protection" + 0.005*"team" + 0.005*"quality" + 0.005*"supported" + 0.005*"ensure" + 0.005*"Senior" + 0.005*"Wandsworth"
+2024-10-14 08:47:54,245 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"practice" + 0.006*"progress" + 0.005*"7" + 0.005*"Wandsworth" + 0.005*"18" + 0.005*"effective" + 0.005*"However" + 0.005*"Senior"
+2024-10-14 08:47:54,245 - topic diff=0.757967, rho=1.000000
+2024-10-14 08:47:54,245 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=884, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:47:54.245869', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:47:55,257 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:47:55,257 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:55,257 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:47:55,257 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:55,257 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:47:55,257 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:55,257 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:47:55,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:55,258 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:47:55,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:47:55,258 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:47:55,258 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:03,567 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:48:03,569 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)
+2024-10-14 08:48:03,570 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-10-14T08:48:03.569994', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:03,571 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:48:03,571 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:48:03,571 - using serial LDA version on this node
+2024-10-14 08:48:03,571 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:48:03,571 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:48:03,575 - -8.156 per-word bound, 285.2 perplexity estimate based on a held-out corpus of 1 documents with 2101 words
+2024-10-14 08:48:03,575 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:48:03,576 - topic #0 (0.333): 0.015*"’" + 0.008*"practice" + 0.007*"needs" + 0.005*"highly" + 0.005*"well" + 0.004*"many" + 0.004*"shared" + 0.004*"number" + 0.003*"Westminster" + 0.003*"direct"
+2024-10-14 08:48:03,576 - topic #1 (0.333): 0.007*"’" + 0.005*"highly" + 0.005*"practice" + 0.004*"well" + 0.004*"needs" + 0.004*"across" + 0.004*"family" + 0.003*"direct" + 0.003*"interventions" + 0.003*"supported"
+2024-10-14 08:48:03,577 - topic #2 (0.333): 0.015*"’" + 0.007*"practice" + 0.007*"needs" + 0.006*"highly" + 0.005*"well" + 0.005*"across" + 0.004*"many" + 0.004*"family" + 0.004*"plans" + 0.004*"experiences"
+2024-10-14 08:48:03,577 - topic diff=0.697576, rho=1.000000
+2024-10-14 08:48:03,577 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1136, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:48:03.577322', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:04,745 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:48:04,745 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:04,745 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:48:04,746 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:04,746 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:48:04,746 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:04,746 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:48:04,746 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:04,747 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:48:04,747 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:04,747 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:48:04,747 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:16,263 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:48:16,265 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)
+2024-10-14 08:48:16,266 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-10-14T08:48:16.266159', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:16,267 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:48:16,267 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:48:16,267 - using serial LDA version on this node
+2024-10-14 08:48:16,268 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:48:16,268 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:48:16,271 - -8.103 per-word bound, 274.8 perplexity estimate based on a held-out corpus of 1 documents with 2593 words
+2024-10-14 08:48:16,272 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:48:16,273 - topic #0 (0.333): 0.020*"’" + 0.007*"need" + 0.007*"Luton" + 0.006*"effective" + 0.006*"needs" + 0.006*"plans" + 0.005*"ensure" + 0.005*"impact" + 0.005*"progress" + 0.005*"good"
+2024-10-14 08:48:16,273 - topic #1 (0.333): 0.010*"’" + 0.004*"need" + 0.004*"needs" + 0.004*"plans" + 0.004*"good" + 0.003*"leaders" + 0.003*"progress" + 0.003*"quality" + 0.003*"impact" + 0.003*"well"
+2024-10-14 08:48:16,273 - topic #2 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"plans" + 0.006*"need" + 0.005*"good" + 0.005*"receive" + 0.005*"effective" + 0.005*"quality" + 0.005*"Luton" + 0.005*"progress"
+2024-10-14 08:48:16,273 - topic diff=0.826241, rho=1.000000
+2024-10-14 08:48:16,273 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1199, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:48:16.273960', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:17,132 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:48:17,132 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:17,133 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:48:17,133 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:17,133 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:48:17,133 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:17,133 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:48:17,134 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:17,134 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:48:17,134 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:17,134 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:48:17,134 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:25,101 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:48:25,103 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)
+2024-10-14 08:48:25,103 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-10-14T08:48:25.103617', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:25,104 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:48:25,104 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:48:25,104 - using serial LDA version on this node
+2024-10-14 08:48:25,105 - 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
+2024-10-14 08:48:25,105 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:48:25,108 - -7.769 per-word bound, 218.1 perplexity estimate based on a held-out corpus of 1 documents with 1938 words
+2024-10-14 08:48:25,108 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:48:25,109 - topic #0 (0.333): 0.023*"’" + 0.009*"Manchester" + 0.008*"needs" + 0.008*"well" + 0.007*"always" + 0.007*"supported" + 0.007*"plans" + 0.006*"effective" + 0.006*"education" + 0.005*"disabled"
+2024-10-14 08:48:25,109 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"Manchester" + 0.006*"always" + 0.005*"well" + 0.005*"disabled" + 0.005*"April" + 0.005*"supported" + 0.004*"protection" + 0.004*"planning"
+2024-10-14 08:48:25,109 - topic #2 (0.333): 0.022*"’" + 0.013*"Manchester" + 0.011*"needs" + 0.007*"supported" + 0.007*"well" + 0.006*"protection" + 0.006*"always" + 0.005*"family" + 0.005*"education" + 0.005*"plans"
+2024-10-14 08:48:25,109 - topic diff=0.813128, rho=1.000000
+2024-10-14 08:48:25,109 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=871, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:48:25.109833', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:26,127 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:48:26,127 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:26,127 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:48:26,127 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:26,127 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:48:26,127 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:26,128 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:48:26,128 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:26,128 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:48:26,128 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:26,128 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:48:26,128 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:34,950 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:48:34,951 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)
+2024-10-14 08:48:34,952 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-10-14T08:48:34.952129', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:34,953 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:48:34,953 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:48:34,953 - using serial LDA version on this node
+2024-10-14 08:48:34,953 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:48:34,953 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:48:34,956 - -7.883 per-word bound, 236.1 perplexity estimate based on a held-out corpus of 1 documents with 1857 words
+2024-10-14 08:48:34,956 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:48:34,958 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.008*"practice" + 0.008*"Medway" + 0.008*"quality" + 0.007*"leaders" + 0.006*"needs" + 0.006*"impact" + 0.005*"risk" + 0.005*"oversight"
+2024-10-14 08:48:34,958 - topic #1 (0.333): 0.013*"’" + 0.008*"Medway" + 0.008*"practice" + 0.007*"well" + 0.006*"quality" + 0.006*"leaders" + 0.006*"needs" + 0.005*"progress" + 0.005*"experiences" + 0.005*"oversight"
+2024-10-14 08:48:34,958 - topic #2 (0.333): 0.015*"’" + 0.011*"Medway" + 0.008*"quality" + 0.008*"practice" + 0.007*"oversight" + 0.007*"well" + 0.006*"needs" + 0.006*"impact" + 0.005*"leaders" + 0.005*"good"
+2024-10-14 08:48:34,958 - topic diff=0.758795, rho=1.000000
+2024-10-14 08:48:34,958 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=922, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:48:34.958545', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:35,842 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:48:35,842 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:35,842 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:48:35,842 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:35,842 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:48:35,842 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:35,843 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:48:35,843 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:35,843 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:48:35,843 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:35,843 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:48:35,843 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:47,333 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:48:47,335 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)
+2024-10-14 08:48:47,335 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-10-14T08:48:47.335529', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:47,336 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:48:47,336 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:48:47,336 - using serial LDA version on this node
+2024-10-14 08:48:47,337 - 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
+2024-10-14 08:48:47,337 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:48:47,343 - -8.000 per-word bound, 256.1 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
+2024-10-14 08:48:47,343 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:48:47,345 - topic #0 (0.333): 0.014*"’" + 0.007*"plans" + 0.006*"needs" + 0.006*"well" + 0.005*"effective" + 0.005*"progress" + 0.005*"Middlesbrough" + 0.004*"24" + 0.004*"13" + 0.004*"means"
+2024-10-14 08:48:47,345 - topic #1 (0.333): 0.012*"’" + 0.008*"effective" + 0.007*"Middlesbrough" + 0.007*"needs" + 0.006*"practice" + 0.006*"plans" + 0.006*"well" + 0.005*"means" + 0.005*"place" + 0.005*"progress"
+2024-10-14 08:48:47,346 - topic #2 (0.333): 0.014*"’" + 0.008*"plans" + 0.008*"Middlesbrough" + 0.007*"well" + 0.007*"effective" + 0.006*"practice" + 0.006*"progress" + 0.005*"24" + 0.005*"needs" + 0.005*"place"
+2024-10-14 08:48:47,346 - topic diff=0.780314, rho=1.000000
+2024-10-14 08:48:47,346 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1068, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:48:47.346319', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:48,220 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:48:48,221 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:48,221 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:48:48,221 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:48,221 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:48:48,221 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:48,221 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:48:48,221 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:48,222 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:48:48,222 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:48,222 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:48:48,222 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:58,536 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:48:58,538 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)
+2024-10-14 08:48:58,538 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-10-14T08:48:58.538461', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:58,539 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:48:58,539 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:48:58,539 - using serial LDA version on this node
+2024-10-14 08:48:58,540 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:48:58,540 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:48:58,543 - -8.040 per-word bound, 263.2 perplexity estimate based on a held-out corpus of 1 documents with 2328 words
+2024-10-14 08:48:58,543 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:48:58,545 - topic #0 (0.333): 0.015*"’" + 0.007*"need" + 0.006*"well" + 0.006*"Keynes" + 0.005*"Milton" + 0.005*"practice" + 0.005*"leaders" + 0.005*"good" + 0.004*"effective" + 0.004*"25"
+2024-10-14 08:48:58,545 - topic #1 (0.333): 0.014*"’" + 0.006*"Keynes" + 0.005*"need" + 0.005*"practice" + 0.005*"plans" + 0.005*"Milton" + 0.005*"well" + 0.004*"education" + 0.004*"5" + 0.004*"team"
+2024-10-14 08:48:58,545 - topic #2 (0.333): 0.015*"’" + 0.007*"Milton" + 0.006*"well" + 0.006*"Keynes" + 0.005*"leaders" + 0.005*"25" + 0.005*"good" + 0.005*"October" + 0.005*"plans" + 0.005*"5"
+2024-10-14 08:48:58,545 - topic diff=0.778561, rho=1.000000
+2024-10-14 08:48:58,545 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1101, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:48:58.545730', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:48:59,467 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:48:59,467 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:59,468 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:48:59,468 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:59,468 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:48:59,468 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:59,468 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:48:59,468 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:59,468 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:48:59,468 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:48:59,468 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:48:59,469 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:09,059 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:49:09,061 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)
+2024-10-14 08:49:09,061 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-10-14T08:49:09.061963', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:09,062 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:49:09,063 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:49:09,063 - using serial LDA version on this node
+2024-10-14 08:49:09,063 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:49:09,063 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:49:09,066 - -7.875 per-word bound, 234.7 perplexity estimate based on a held-out corpus of 1 documents with 2076 words
+2024-10-14 08:49:09,066 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:49:09,068 - topic #0 (0.333): 0.017*"’" + 0.011*"plans" + 0.009*"needs" + 0.008*"Newcastle" + 0.007*"good" + 0.007*"management" + 0.006*"well" + 0.006*"protection" + 0.006*"making" + 0.006*"need"
+2024-10-14 08:49:09,068 - topic #1 (0.333): 0.014*"’" + 0.008*"plans" + 0.008*"good" + 0.007*"protection" + 0.007*"needs" + 0.006*"well" + 0.006*"ensure" + 0.006*"Newcastle" + 0.005*"progress" + 0.005*"making"
+2024-10-14 08:49:09,068 - topic #2 (0.333): 0.016*"’" + 0.011*"plans" + 0.007*"Newcastle" + 0.007*"well" + 0.007*"protection" + 0.007*"needs" + 0.006*"progress" + 0.006*"response" + 0.006*"ensure" + 0.005*"good"
+2024-10-14 08:49:09,068 - topic diff=0.781758, rho=1.000000
+2024-10-14 08:49:09,068 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=956, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:49:09.068489', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:10,006 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:49:10,006 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:10,006 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:49:10,006 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:10,007 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:49:10,007 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:10,007 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:49:10,007 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:10,007 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:49:10,007 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:10,007 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:49:10,008 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:21,161 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:49:21,166 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)
+2024-10-14 08:49:21,166 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-10-14T08:49:21.166428', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:21,167 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:49:21,167 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:49:21,168 - using serial LDA version on this node
+2024-10-14 08:49:21,168 - 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
+2024-10-14 08:49:21,168 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:49:21,172 - -8.123 per-word bound, 278.8 perplexity estimate based on a held-out corpus of 1 documents with 2655 words
+2024-10-14 08:49:21,172 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:49:21,173 - topic #0 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"Norfolk" + 0.007*"practice" + 0.006*"needs" + 0.006*"carers" + 0.005*"supported" + 0.005*"leaders" + 0.004*"plans" + 0.004*"7"
+2024-10-14 08:49:21,173 - topic #1 (0.333): 0.021*"’" + 0.008*"well" + 0.007*"Norfolk" + 0.007*"carers" + 0.006*"needs" + 0.006*"range" + 0.005*"supported" + 0.005*"plans" + 0.004*"effective" + 0.004*"practice"
+2024-10-14 08:49:21,173 - topic #2 (0.333): 0.013*"’" + 0.008*"Norfolk" + 0.006*"well" + 0.005*"practice" + 0.005*"carers" + 0.005*"supported" + 0.004*"including" + 0.004*"18" + 0.004*"leaders" + 0.004*"plans"
+2024-10-14 08:49:21,174 - topic diff=0.786128, rho=1.000000
+2024-10-14 08:49:21,174 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1221, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:49:21.174180', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:22,086 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:49:22,086 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:22,086 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:49:22,086 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:22,087 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:49:22,087 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:22,087 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:49:22,087 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:22,087 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:49:22,087 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:22,087 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:49:22,087 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:31,688 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:49:31,690 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)
+2024-10-14 08:49:31,690 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-10-14T08:49:31.690568', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:31,691 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:49:31,691 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:49:31,691 - using serial LDA version on this node
+2024-10-14 08:49:31,692 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:49:31,692 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:49:31,695 - -7.889 per-word bound, 237.1 perplexity estimate based on a held-out corpus of 1 documents with 2045 words
+2024-10-14 08:49:31,695 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:49:31,696 - topic #0 (0.333): 0.006*"’" + 0.006*"risk" + 0.005*"leaders" + 0.005*"practice" + 0.004*"need" + 0.004*"plans" + 0.004*"Lincolnshire" + 0.004*"planning" + 0.004*"making" + 0.003*"delay"
+2024-10-14 08:49:31,696 - topic #1 (0.333): 0.019*"’" + 0.009*"practice" + 0.009*"risk" + 0.007*"planning" + 0.007*"needs" + 0.006*"leaders" + 0.006*"need" + 0.005*"North" + 0.005*"2021" + 0.005*"oversight"
+2024-10-14 08:49:31,697 - topic #2 (0.333): 0.011*"’" + 0.007*"practice" + 0.007*"leaders" + 0.006*"needs" + 0.006*"many" + 0.005*"planning" + 0.005*"October" + 0.005*"East" + 0.005*"quality" + 0.005*"need"
+2024-10-14 08:49:31,697 - topic diff=0.801638, rho=1.000000
+2024-10-14 08:49:31,697 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=958, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:49:31.697228', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:32,633 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:49:32,633 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:32,633 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:49:32,634 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:32,634 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:49:32,634 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:32,634 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:49:32,634 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:32,634 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:49:32,634 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:32,634 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:49:32,634 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:41,568 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:49:41,570 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)
+2024-10-14 08:49:41,570 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-10-14T08:49:41.570884', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:41,571 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:49:41,572 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:49:41,572 - using serial LDA version on this node
+2024-10-14 08:49:41,572 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:49:41,572 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:49:41,576 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2174 words
+2024-10-14 08:49:41,576 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:49:41,577 - topic #0 (0.333): 0.021*"’" + 0.009*"‘" + 0.007*"family" + 0.006*"Lincolnshire" + 0.006*"10" + 0.005*"approach" + 0.005*"October" + 0.005*"need" + 0.005*"well" + 0.005*"North"
+2024-10-14 08:49:41,577 - topic #1 (0.333): 0.017*"’" + 0.006*"‘" + 0.005*"North" + 0.005*"family" + 0.004*"need" + 0.004*"well" + 0.004*"2022" + 0.004*"council" + 0.004*"leaders" + 0.004*"Lincolnshire"
+2024-10-14 08:49:41,577 - topic #2 (0.333): 0.021*"’" + 0.006*"leaders" + 0.005*"approach" + 0.005*"North" + 0.005*"well" + 0.005*"‘" + 0.005*"Lincolnshire" + 0.005*"family" + 0.005*"14" + 0.004*"practice"
+2024-10-14 08:49:41,577 - topic diff=0.762484, rho=1.000000
+2024-10-14 08:49:41,577 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:49:41.577880', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:42,463 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:49:42,463 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:42,463 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:49:42,463 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:42,463 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:49:42,464 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:42,464 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:49:42,464 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:42,464 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:49:42,464 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:42,464 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:49:42,464 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:51,753 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:49:51,755 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)
+2024-10-14 08:49:51,756 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-10-14T08:49:51.756067', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:51,757 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:49:51,757 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:49:51,757 - using serial LDA version on this node
+2024-10-14 08:49:51,757 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:49:51,757 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:49:51,761 - -8.030 per-word bound, 261.3 perplexity estimate based on a held-out corpus of 1 documents with 2204 words
+2024-10-14 08:49:51,761 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:49:51,762 - topic #0 (0.333): 0.021*"’" + 0.008*"Northamptonshire" + 0.008*"North" + 0.007*"well" + 0.006*"quality" + 0.006*"practice" + 0.005*"impact" + 0.005*"NCT" + 0.005*"Leaders" + 0.005*"3"
+2024-10-14 08:49:51,762 - topic #1 (0.333): 0.014*"’" + 0.007*"Northamptonshire" + 0.006*"North" + 0.006*"quality" + 0.006*"well" + 0.005*"NCT" + 0.005*"needs" + 0.005*"practice" + 0.005*"3" + 0.004*"Leaders"
+2024-10-14 08:49:51,762 - topic #2 (0.333): 0.014*"’" + 0.009*"Northamptonshire" + 0.005*"well" + 0.005*"plans" + 0.005*"needs" + 0.005*"need" + 0.005*"Leaders" + 0.004*"impact" + 0.004*"North" + 0.004*"quality"
+2024-10-14 08:49:51,763 - topic diff=0.745852, rho=1.000000
+2024-10-14 08:49:51,763 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:49:51.763195', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:49:52,647 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:49:52,648 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:52,648 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:49:52,648 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:52,648 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:49:52,648 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:52,648 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:49:52,648 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:52,648 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:49:52,649 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:49:52,649 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:49:52,649 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:04,023 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:50:04,025 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)
+2024-10-14 08:50:04,025 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-10-14T08:50:04.025682', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:04,026 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:50:04,027 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:50:04,027 - using serial LDA version on this node
+2024-10-14 08:50:04,027 - 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
+2024-10-14 08:50:04,027 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:50:04,031 - -8.063 per-word bound, 267.4 perplexity estimate based on a held-out corpus of 1 documents with 2902 words
+2024-10-14 08:50:04,031 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:50:04,032 - topic #0 (0.333): 0.012*"’" + 0.007*"needs" + 0.006*"quality" + 0.006*"always" + 0.006*"practice" + 0.006*"Somerset" + 0.006*"progress" + 0.005*"North" + 0.005*"number" + 0.005*"24"
+2024-10-14 08:50:04,033 - topic #1 (0.333): 0.019*"’" + 0.008*"quality" + 0.007*"needs" + 0.006*"risk" + 0.006*"number" + 0.006*"Somerset" + 0.006*"North" + 0.006*"plans" + 0.005*"always" + 0.005*"practice"
+2024-10-14 08:50:04,033 - topic #2 (0.333): 0.019*"’" + 0.007*"quality" + 0.006*"always" + 0.006*"needs" + 0.006*"North" + 0.006*"Somerset" + 0.005*"need" + 0.005*"experienced" + 0.005*"effective" + 0.005*"well"
+2024-10-14 08:50:04,033 - topic diff=0.829794, rho=1.000000
+2024-10-14 08:50:04,033 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1219, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:50:04.033450', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:05,813 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:50:05,814 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:05,814 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:50:05,814 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:05,814 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:50:05,815 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:05,815 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:50:05,815 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:05,815 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:50:05,815 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:05,815 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:50:05,815 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:16,511 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:50:16,513 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)
+2024-10-14 08:50:16,513 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-10-14T08:50:16.513850', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:16,515 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:50:16,515 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:50:16,515 - using serial LDA version on this node
+2024-10-14 08:50:16,515 - 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
+2024-10-14 08:50:16,515 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:50:16,519 - -8.223 per-word bound, 298.8 perplexity estimate based on a held-out corpus of 1 documents with 2518 words
+2024-10-14 08:50:16,519 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:50:16,521 - topic #0 (0.333): 0.013*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"quality" + 0.004*"progress" + 0.004*"make" + 0.004*"need" + 0.004*"leaders" + 0.004*"understand" + 0.004*"impact"
+2024-10-14 08:50:16,521 - topic #1 (0.333): 0.014*"’" + 0.005*"well" + 0.005*"leaders" + 0.005*"make" + 0.004*"need" + 0.004*"quality" + 0.003*"early" + 0.003*"good" + 0.003*"family" + 0.003*"needs"
+2024-10-14 08:50:16,521 - topic #2 (0.333): 0.020*"’" + 0.008*"well" + 0.006*"leaders" + 0.006*"need" + 0.005*"impact" + 0.005*"quality" + 0.005*"make" + 0.004*"early" + 0.004*"needs" + 0.004*"protection"
+2024-10-14 08:50:16,521 - topic diff=0.740340, rho=1.000000
+2024-10-14 08:50:16,522 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1273, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:50:16.521997', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:17,461 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:50:17,461 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:17,461 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:50:17,461 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:17,462 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:50:17,462 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:17,462 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:50:17,462 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:17,462 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:50:17,462 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:17,462 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:50:17,462 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:28,773 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:50:28,776 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)
+2024-10-14 08:50:28,776 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-10-14T08:50:28.776261', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:28,777 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:50:28,777 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:50:28,777 - using serial LDA version on this node
+2024-10-14 08:50:28,778 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:50:28,778 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:50:28,782 - -8.145 per-word bound, 283.1 perplexity estimate based on a held-out corpus of 1 documents with 2759 words
+2024-10-14 08:50:28,782 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:50:28,783 - topic #0 (0.333): 0.013*"’" + 0.007*"practice" + 0.006*"well" + 0.005*"North" + 0.004*"family" + 0.004*"3" + 0.004*"Yorkshire" + 0.004*"needs" + 0.004*"carers" + 0.004*"Leaders"
+2024-10-14 08:50:28,783 - topic #1 (0.333): 0.023*"’" + 0.010*"well" + 0.009*"Yorkshire" + 0.007*"needs" + 0.007*"family" + 0.007*"North" + 0.006*"practice" + 0.005*"3" + 0.005*"2023" + 0.005*"‘"
+2024-10-14 08:50:28,783 - topic #2 (0.333): 0.023*"’" + 0.007*"well" + 0.006*"North" + 0.006*"‘" + 0.005*"practice" + 0.005*"needs" + 0.004*"family" + 0.004*"7" + 0.004*"July" + 0.004*"supported"
+2024-10-14 08:50:28,784 - topic diff=0.817309, rho=1.000000
+2024-10-14 08:50:28,784 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1259, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:50:28.784180', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:29,664 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:50:29,664 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:29,665 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:50:29,665 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:29,665 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:50:29,665 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:29,665 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:50:29,665 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:29,665 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:50:29,665 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:29,665 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:50:29,666 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:42,096 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:50:42,099 - built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)
+2024-10-14 08:50:42,099 - Dictionary lifecycle event {'msg': "built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)", 'datetime': '2024-10-14T08:50:42.099486', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:42,100 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:50:42,100 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:50:42,101 - using serial LDA version on this node
+2024-10-14 08:50:42,101 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:50:42,101 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:50:42,105 - -8.067 per-word bound, 268.1 perplexity estimate based on a held-out corpus of 1 documents with 2884 words
+2024-10-14 08:50:42,105 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:50:42,106 - topic #0 (0.333): 0.017*"’" + 0.008*"family" + 0.007*"leaders" + 0.006*"experiences" + 0.006*"needs" + 0.005*"progress" + 0.005*"strong" + 0.005*"well" + 0.005*"within" + 0.005*"practice"
+2024-10-14 08:50:42,107 - topic #1 (0.333): 0.011*"’" + 0.006*"family" + 0.005*"needs" + 0.005*"strong" + 0.005*"leaders" + 0.005*"well" + 0.004*"experiences" + 0.004*"effective" + 0.004*"Northumberland" + 0.004*"24"
+2024-10-14 08:50:42,107 - topic #2 (0.333): 0.023*"’" + 0.008*"family" + 0.007*"needs" + 0.007*"strong" + 0.007*"experiences" + 0.007*"leaders" + 0.006*"Northumberland" + 0.006*"well" + 0.005*"effective" + 0.005*"receive"
+2024-10-14 08:50:42,107 - topic diff=0.853199, rho=1.000000
+2024-10-14 08:50:42,107 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1218, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:50:42.107519', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:43,303 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:50:43,303 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:43,304 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:50:43,304 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:43,304 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:50:43,304 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:43,304 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:50:43,304 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:43,304 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:50:43,304 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:43,304 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:50:43,305 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:54,334 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:50:54,336 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
+2024-10-14 08:50:54,336 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-10-14T08:50:54.336909', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:54,337 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:50:54,338 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:50:54,338 - using serial LDA version on this node
+2024-10-14 08:50:54,338 - 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
+2024-10-14 08:50:54,338 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:50:54,342 - -8.025 per-word bound, 260.5 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
+2024-10-14 08:50:54,342 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:50:54,343 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.006*"Nottingham" + 0.005*"effective" + 0.005*"plans" + 0.005*"oversight" + 0.005*"2022" + 0.005*"impact" + 0.004*"practice" + 0.004*"protection"
+2024-10-14 08:50:54,343 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.006*"plans" + 0.005*"effective" + 0.005*"Nottingham" + 0.004*"However" + 0.004*"practice" + 0.004*"risk" + 0.004*"City" + 0.004*"oversight"
+2024-10-14 08:50:54,344 - topic #2 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"Nottingham" + 0.005*"impact" + 0.005*"11" + 0.005*"effective" + 0.005*"plans" + 0.005*"City" + 0.005*"July" + 0.004*"risk"
+2024-10-14 08:50:54,344 - topic diff=0.764233, rho=1.000000
+2024-10-14 08:50:54,344 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:50:54.344323', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:50:55,245 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:50:55,245 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:55,245 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:50:55,245 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:55,245 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:50:55,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:55,246 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:50:55,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:55,246 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:50:55,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:50:55,246 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:50:55,246 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:05,628 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:51:05,630 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)
+2024-10-14 08:51:05,630 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)", 'datetime': '2024-10-14T08:51:05.630713', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:05,631 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:51:05,631 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:51:05,632 - using serial LDA version on this node
+2024-10-14 08:51:05,632 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:51:05,632 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:51:05,635 - -8.005 per-word bound, 256.9 perplexity estimate based on a held-out corpus of 1 documents with 2129 words
+2024-10-14 08:51:05,635 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:51:05,637 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"Nottinghamshire" + 0.005*"effective" + 0.005*"plans" + 0.004*"practice" + 0.004*"20" + 0.004*"risks" + 0.004*"leaders"
+2024-10-14 08:51:05,637 - topic #1 (0.333): 0.020*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"plans" + 0.006*"Nottinghamshire" + 0.006*"24" + 0.005*"leaders" + 0.005*"Leaders" + 0.005*"ensure" + 0.004*"provide"
+2024-10-14 08:51:05,637 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"Nottinghamshire" + 0.005*"Leaders" + 0.005*"plans" + 0.005*"effective" + 0.005*"practice" + 0.005*"20" + 0.004*"2024"
+2024-10-14 08:51:05,637 - topic diff=0.758152, rho=1.000000
+2024-10-14 08:51:05,637 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:51:05.637775', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:06,561 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:51:06,561 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:06,562 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:51:06,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:06,562 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:51:06,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:06,562 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:51:06,562 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:06,562 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:51:06,563 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:06,563 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:51:06,563 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:18,027 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:51:18,029 - built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)
+2024-10-14 08:51:18,029 - Dictionary lifecycle event {'msg': "built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)", 'datetime': '2024-10-14T08:51:18.029903', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:18,031 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:51:18,031 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:51:18,031 - using serial LDA version on this node
+2024-10-14 08:51:18,031 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:51:18,031 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:51:18,035 - -8.077 per-word bound, 269.9 perplexity estimate based on a held-out corpus of 1 documents with 2441 words
+2024-10-14 08:51:18,035 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:51:18,037 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.006*"needs" + 0.006*"Oldham" + 0.006*"plans" + 0.005*"PAs" + 0.005*"progress" + 0.005*"practice" + 0.005*"leaders" + 0.005*"quality"
+2024-10-14 08:51:18,037 - topic #1 (0.333): 0.017*"’" + 0.010*"plans" + 0.009*"well" + 0.007*"Oldham" + 0.006*"needs" + 0.006*"leaders" + 0.006*"practice" + 0.006*"PAs" + 0.005*"effective" + 0.005*"timely"
+2024-10-14 08:51:18,037 - topic #2 (0.333): 0.009*"’" + 0.007*"plans" + 0.006*"well" + 0.006*"practice" + 0.006*"PAs" + 0.006*"needs" + 0.005*"leaders" + 0.005*"progress" + 0.005*"quality" + 0.005*"Oldham"
+2024-10-14 08:51:18,037 - topic diff=0.783030, rho=1.000000
+2024-10-14 08:51:18,037 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1152, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:51:18.037693', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:18,868 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:51:18,868 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:18,868 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:51:18,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:18,869 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:51:18,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:18,869 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:51:18,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:18,869 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:51:18,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:18,869 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:51:18,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:29,623 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:51:29,625 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)
+2024-10-14 08:51:29,625 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-10-14T08:51:29.625549', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:29,626 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:51:29,626 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:51:29,626 - using serial LDA version on this node
+2024-10-14 08:51:29,627 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:51:29,627 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:51:29,630 - -7.996 per-word bound, 255.2 perplexity estimate based on a held-out corpus of 1 documents with 2294 words
+2024-10-14 08:51:29,630 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:51:29,632 - topic #0 (0.333): 0.022*"’" + 0.008*"needs" + 0.008*"Oxfordshire" + 0.008*"good" + 0.007*"well" + 0.006*"quality" + 0.005*"risk" + 0.005*"supported" + 0.005*"progress" + 0.005*"receive"
+2024-10-14 08:51:29,632 - topic #1 (0.333): 0.022*"’" + 0.011*"needs" + 0.008*"Oxfordshire" + 0.007*"well" + 0.007*"risk" + 0.005*"practice" + 0.005*"12" + 0.005*"supported" + 0.005*"education" + 0.005*"receive"
+2024-10-14 08:51:29,632 - topic #2 (0.333): 0.012*"’" + 0.010*"needs" + 0.006*"supported" + 0.006*"well" + 0.004*"23" + 0.004*"12" + 0.004*"risk" + 0.004*"good" + 0.004*"2024" + 0.004*"arrangements"
+2024-10-14 08:51:29,632 - topic diff=0.786134, rho=1.000000
+2024-10-14 08:51:29,632 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1066, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:51:29.632685', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:30,519 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:51:30,519 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:30,519 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:51:30,519 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:30,519 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:51:30,519 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:30,520 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:51:30,520 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:30,520 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:51:30,520 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:30,520 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:51:30,520 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:39,296 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:51:39,298 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)
+2024-10-14 08:51:39,298 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-10-14T08:51:39.298904', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:39,299 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:51:39,299 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:51:39,300 - using serial LDA version on this node
+2024-10-14 08:51:39,300 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:51:39,300 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:51:39,303 - -7.878 per-word bound, 235.2 perplexity estimate based on a held-out corpus of 1 documents with 1737 words
+2024-10-14 08:51:39,303 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:51:39,304 - topic #0 (0.333): 0.013*"needs" + 0.013*"’" + 0.007*"need" + 0.006*"Peterborough" + 0.006*"plans" + 0.006*"well" + 0.005*"2023" + 0.005*"8" + 0.005*"progress" + 0.005*"27"
+2024-10-14 08:51:39,305 - topic #1 (0.333): 0.016*"’" + 0.016*"needs" + 0.008*"Peterborough" + 0.006*"need" + 0.006*"2023" + 0.006*"well" + 0.006*"progress" + 0.005*"good" + 0.005*"supported" + 0.005*"27"
+2024-10-14 08:51:39,305 - topic #2 (0.333): 0.014*"’" + 0.011*"needs" + 0.008*"need" + 0.007*"Peterborough" + 0.007*"2023" + 0.006*"well" + 0.006*"progress" + 0.006*"8" + 0.005*"receive" + 0.005*"supported"
+2024-10-14 08:51:39,305 - topic diff=0.730058, rho=1.000000
+2024-10-14 08:51:39,305 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=893, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:51:39.305448', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:40,281 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:51:40,281 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:40,281 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:51:40,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:40,282 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:51:40,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:40,282 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:51:40,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:40,282 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:51:40,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:40,282 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:51:40,282 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:53,362 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:51:53,365 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
+2024-10-14 08:51:53,365 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-10-14T08:51:53.365490', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:53,366 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:51:53,366 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:51:53,367 - using serial LDA version on this node
+2024-10-14 08:51:53,367 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:51:53,367 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:51:53,371 - -8.082 per-word bound, 271.0 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
+2024-10-14 08:51:53,371 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:51:53,372 - topic #0 (0.333): 0.014*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"Plymouth" + 0.007*"practice" + 0.006*"appropriate" + 0.005*"22" + 0.005*"education" + 0.005*"2024" + 0.005*"January"
+2024-10-14 08:51:53,372 - topic #1 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"Plymouth" + 0.005*"plans" + 0.005*"City" + 0.005*"quality" + 0.004*"education" + 0.004*"effective" + 0.004*"2024"
+2024-10-14 08:51:53,373 - topic #2 (0.333): 0.011*"’" + 0.008*"needs" + 0.006*"Plymouth" + 0.006*"well" + 0.006*"2" + 0.005*"22" + 0.005*"plans" + 0.004*"City" + 0.004*"practice" + 0.004*"timely"
+2024-10-14 08:51:53,373 - topic diff=0.836126, rho=1.000000
+2024-10-14 08:51:53,373 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1232, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:51:53.373318', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:51:54,314 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:51:54,314 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:54,314 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:51:54,314 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:54,314 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:51:54,315 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:54,315 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:51:54,315 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:54,315 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:51:54,315 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:51:54,315 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:51:54,315 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:06,465 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:52:06,468 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)
+2024-10-14 08:52:06,468 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-10-14T08:52:06.468175', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:06,469 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:52:06,469 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:52:06,469 - using serial LDA version on this node
+2024-10-14 08:52:06,470 - 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
+2024-10-14 08:52:06,470 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:52:06,473 - -8.107 per-word bound, 275.7 perplexity estimate based on a held-out corpus of 1 documents with 2738 words
+2024-10-14 08:52:06,473 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:52:06,475 - topic #0 (0.333): 0.020*"’" + 0.009*"care-experienced" + 0.008*"Portsmouth" + 0.007*"well" + 0.007*"needs" + 0.006*"health" + 0.006*"practice" + 0.005*"plans" + 0.005*"foster" + 0.005*"family"
+2024-10-14 08:52:06,475 - topic #1 (0.333): 0.010*"’" + 0.005*"care-experienced" + 0.004*"well" + 0.004*"health" + 0.004*"needs" + 0.004*"family" + 0.004*"carers" + 0.003*"supported" + 0.003*"19" + 0.003*"offer"
+2024-10-14 08:52:06,475 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.008*"care-experienced" + 0.007*"needs" + 0.007*"family" + 0.006*"Portsmouth" + 0.006*"plans" + 0.005*"leaders" + 0.005*"receive" + 0.005*"risk"
+2024-10-14 08:52:06,475 - topic diff=0.826362, rho=1.000000
+2024-10-14 08:52:06,475 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:52:06.475845', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:07,598 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:52:07,598 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:07,599 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:52:07,599 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:07,599 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:52:07,599 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:07,599 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:52:07,599 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:07,600 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:52:07,600 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:07,600 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:52:07,600 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:18,352 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:52:18,354 - built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)
+2024-10-14 08:52:18,354 - Dictionary lifecycle event {'msg': "built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)", 'datetime': '2024-10-14T08:52:18.354926', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:18,356 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:52:18,356 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:52:18,356 - using serial LDA version on this node
+2024-10-14 08:52:18,356 - 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
+2024-10-14 08:52:18,356 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:52:18,360 - -8.159 per-word bound, 285.8 perplexity estimate based on a held-out corpus of 1 documents with 2562 words
+2024-10-14 08:52:18,360 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:52:18,362 - topic #0 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"Reading" + 0.006*"plans" + 0.006*"PAs" + 0.005*"well" + 0.005*"clear" + 0.004*"3" + 0.004*"effective" + 0.004*"22"
+2024-10-14 08:52:18,362 - topic #1 (0.333): 0.012*"’" + 0.008*"needs" + 0.005*"progress" + 0.005*"plans" + 0.004*"2024" + 0.004*"well" + 0.004*"PAs" + 0.004*"Reading" + 0.004*"risk" + 0.004*"clear"
+2024-10-14 08:52:18,362 - topic #2 (0.333): 0.014*"’" + 0.006*"needs" + 0.006*"progress" + 0.006*"PAs" + 0.005*"arrangements" + 0.005*"timely" + 0.004*"well" + 0.004*"3" + 0.004*"risk" + 0.004*"plans"
+2024-10-14 08:52:18,362 - topic diff=0.762826, rho=1.000000
+2024-10-14 08:52:18,362 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1231, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:52:18.362750', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:19,329 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:52:19,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:19,330 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:52:19,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:19,330 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:52:19,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:19,330 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:52:19,330 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:19,331 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:52:19,331 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:19,331 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:52:19,331 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:29,965 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:52:29,968 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)
+2024-10-14 08:52:29,968 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-10-14T08:52:29.968213', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:29,969 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:52:29,969 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:52:29,969 - using serial LDA version on this node
+2024-10-14 08:52:29,970 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:52:29,970 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:52:29,973 - -8.004 per-word bound, 256.8 perplexity estimate based on a held-out corpus of 1 documents with 2515 words
+2024-10-14 08:52:29,973 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:52:29,975 - topic #0 (0.333): 0.017*"’" + 0.007*"leaders" + 0.006*"However" + 0.006*"consistently" + 0.005*"needs" + 0.005*"carers" + 0.005*"plans" + 0.005*"20" + 0.004*"response" + 0.004*"2022"
+2024-10-14 08:52:29,975 - topic #1 (0.333): 0.017*"’" + 0.006*"plans" + 0.006*"leaders" + 0.006*"needs" + 0.005*"However" + 0.005*"practice" + 0.005*"2022" + 0.005*"risk" + 0.005*"Redcar" + 0.005*"20"
+2024-10-14 08:52:29,975 - topic #2 (0.333): 0.018*"’" + 0.006*"consistently" + 0.005*"needs" + 0.005*"leaders" + 0.005*"However" + 0.005*"plans" + 0.005*"practice" + 0.005*"risk" + 0.005*"20" + 0.005*"1"
+2024-10-14 08:52:29,975 - topic diff=0.799354, rho=1.000000
+2024-10-14 08:52:29,975 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:52:29.975647', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:30,882 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:52:30,883 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:30,883 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:52:30,883 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:30,883 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:52:30,883 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:30,883 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:52:30,884 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:30,884 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:52:30,884 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:30,884 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:52:30,884 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:42,600 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:52:42,602 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)
+2024-10-14 08:52:42,602 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-10-14T08:52:42.602875', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:42,604 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:52:42,604 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:52:42,604 - using serial LDA version on this node
+2024-10-14 08:52:42,604 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:52:42,604 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:52:42,608 - -8.025 per-word bound, 260.4 perplexity estimate based on a held-out corpus of 1 documents with 2656 words
+2024-10-14 08:52:42,608 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:52:42,609 - topic #0 (0.333): 0.020*"’" + 0.012*"experienced" + 0.010*"needs" + 0.008*"practice" + 0.006*"plans" + 0.006*"response" + 0.006*"3" + 0.005*"need" + 0.005*"quality" + 0.005*"consistently"
+2024-10-14 08:52:42,609 - topic #1 (0.333): 0.020*"’" + 0.008*"experienced" + 0.008*"practice" + 0.006*"response" + 0.006*"needs" + 0.006*"good" + 0.006*"plans" + 0.005*"PAs" + 0.005*"quality" + 0.005*"consistently"
+2024-10-14 08:52:42,610 - topic #2 (0.333): 0.020*"’" + 0.009*"experienced" + 0.007*"practice" + 0.007*"needs" + 0.006*"consistently" + 0.006*"plans" + 0.005*"response" + 0.005*"Rochdale" + 0.005*"quality" + 0.005*"good"
+2024-10-14 08:52:42,610 - topic diff=0.815381, rho=1.000000
+2024-10-14 08:52:42,610 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1150, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:52:42.610183', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:43,632 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:52:43,632 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:43,632 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:52:43,633 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:43,633 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:52:43,633 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:43,633 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:52:43,633 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:43,633 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:52:43,633 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:43,633 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:52:43,633 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:54,595 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:52:54,597 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)
+2024-10-14 08:52:54,597 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-10-14T08:52:54.597733', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:54,598 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:52:54,598 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:52:54,599 - using serial LDA version on this node
+2024-10-14 08:52:54,599 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:52:54,599 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:52:54,603 - -8.064 per-word bound, 267.6 perplexity estimate based on a held-out corpus of 1 documents with 2366 words
+2024-10-14 08:52:54,603 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:52:54,604 - topic #0 (0.333): 0.013*"’" + 0.010*"Rotherham" + 0.007*"needs" + 0.006*"well" + 0.005*"good" + 0.005*"ensure" + 0.004*"Metropolitan" + 0.004*"clear" + 0.004*"plans" + 0.004*"1"
+2024-10-14 08:52:54,604 - topic #1 (0.333): 0.016*"’" + 0.008*"Rotherham" + 0.006*"needs" + 0.005*"well" + 0.005*"However" + 0.004*"good" + 0.004*"ensure" + 0.004*"Council" + 0.004*"Borough" + 0.004*"27"
+2024-10-14 08:52:54,604 - topic #2 (0.333): 0.015*"’" + 0.008*"Rotherham" + 0.006*"needs" + 0.006*"plans" + 0.005*"Council" + 0.005*"good" + 0.005*"well" + 0.005*"ensure" + 0.005*"However" + 0.004*"Metropolitan"
+2024-10-14 08:52:54,604 - topic diff=0.770536, rho=1.000000
+2024-10-14 08:52:54,604 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1127, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:52:54.604922', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:52:55,451 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:52:55,451 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:55,452 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:52:55,452 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:55,452 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:52:55,452 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:55,452 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:52:55,452 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:55,452 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:52:55,452 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:52:55,452 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:52:55,452 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:05,293 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:53:05,296 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)
+2024-10-14 08:53:05,296 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-10-14T08:53:05.296151', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:05,297 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:53:05,297 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:53:05,297 - using serial LDA version on this node
+2024-10-14 08:53:05,297 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:53:05,297 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:53:05,301 - -8.052 per-word bound, 265.3 perplexity estimate based on a held-out corpus of 1 documents with 2380 words
+2024-10-14 08:53:05,301 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:53:05,302 - topic #0 (0.333): 0.014*"well" + 0.010*"practice" + 0.009*"’" + 0.006*"needs" + 0.006*"strong" + 0.005*"highly" + 0.005*"effective" + 0.004*"leaders" + 0.004*"ensure" + 0.004*"high"
+2024-10-14 08:53:05,302 - topic #1 (0.333): 0.011*"’" + 0.010*"well" + 0.009*"practice" + 0.007*"highly" + 0.005*"strong" + 0.005*"high" + 0.005*"leaders" + 0.004*"needs" + 0.004*"effective" + 0.004*"range"
+2024-10-14 08:53:05,303 - topic #2 (0.333): 0.015*"well" + 0.014*"’" + 0.012*"practice" + 0.009*"highly" + 0.007*"strong" + 0.006*"effective" + 0.005*"needs" + 0.005*"leaders" + 0.005*"progress" + 0.004*"risk"
+2024-10-14 08:53:05,303 - topic diff=0.776705, rho=1.000000
+2024-10-14 08:53:05,303 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:53:05.303282', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:06,332 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:53:06,332 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:06,332 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:53:06,332 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:06,333 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:53:06,333 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:06,333 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:53:06,333 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:06,333 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:53:06,333 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:06,333 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:53:06,333 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:16,074 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:53:16,076 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)
+2024-10-14 08:53:16,076 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-10-14T08:53:16.076652', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:16,077 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:53:16,077 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:53:16,078 - using serial LDA version on this node
+2024-10-14 08:53:16,078 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:53:16,078 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:53:16,081 - -8.064 per-word bound, 267.7 perplexity estimate based on a held-out corpus of 1 documents with 2257 words
+2024-10-14 08:53:16,081 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:53:16,083 - topic #0 (0.333): 0.009*"’" + 0.008*"well" + 0.006*"needs" + 0.005*"plans" + 0.004*"good" + 0.004*"risk" + 0.004*"information" + 0.003*"effective" + 0.003*"supported" + 0.003*"appropriate"
+2024-10-14 08:53:16,083 - topic #1 (0.333): 0.016*"’" + 0.011*"well" + 0.008*"needs" + 0.008*"plans" + 0.006*"good" + 0.005*"effective" + 0.005*"clear" + 0.005*"need" + 0.004*"practice" + 0.004*"progress"
+2024-10-14 08:53:16,083 - topic #2 (0.333): 0.013*"’" + 0.009*"plans" + 0.008*"needs" + 0.007*"well" + 0.005*"parents" + 0.005*"good" + 0.005*"practice" + 0.004*"supported" + 0.004*"effective" + 0.004*"clear"
+2024-10-14 08:53:16,083 - topic diff=0.761399, rho=1.000000
+2024-10-14 08:53:16,083 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1107, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:53:16.083755', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:17,172 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:53:17,173 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:17,173 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:53:17,173 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:17,173 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:53:17,173 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:17,173 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:53:17,173 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:17,174 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:53:17,174 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:17,174 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:53:17,174 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:27,052 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:53:27,054 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)
+2024-10-14 08:53:27,054 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-10-14T08:53:27.054867', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:27,055 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:53:27,056 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:53:27,056 - using serial LDA version on this node
+2024-10-14 08:53:27,056 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:53:27,056 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:53:27,060 - -8.119 per-word bound, 278.0 perplexity estimate based on a held-out corpus of 1 documents with 2088 words
+2024-10-14 08:53:27,060 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:53:27,061 - topic #0 (0.333): 0.010*"’" + 0.005*"needs" + 0.005*"effective" + 0.005*"well" + 0.004*"information" + 0.004*"health" + 0.004*"use" + 0.004*"quality" + 0.004*"informed" + 0.004*"plans"
+2024-10-14 08:53:27,061 - topic #1 (0.333): 0.015*"’" + 0.005*"well" + 0.005*"quality" + 0.004*"plans" + 0.004*"needs" + 0.004*"benefit" + 0.004*"use" + 0.004*"information" + 0.004*"management" + 0.004*"always"
+2024-10-14 08:53:27,061 - topic #2 (0.333): 0.009*"’" + 0.006*"well" + 0.005*"quality" + 0.005*"plans" + 0.005*"needs" + 0.004*"actions" + 0.004*"benefit" + 0.004*"timely" + 0.004*"effective" + 0.003*"use"
+2024-10-14 08:53:27,062 - topic diff=0.715731, rho=1.000000
+2024-10-14 08:53:27,062 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:53:27.062145', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:28,183 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:53:28,184 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:28,184 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:53:28,184 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:28,184 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:53:28,184 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:28,184 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:53:28,184 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:28,185 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:53:28,185 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:28,185 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:53:28,185 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:39,027 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:53:39,029 - built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)
+2024-10-14 08:53:39,029 - Dictionary lifecycle event {'msg': "built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)", 'datetime': '2024-10-14T08:53:39.029371', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:39,030 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:53:39,030 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:53:39,030 - using serial LDA version on this node
+2024-10-14 08:53:39,031 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:53:39,031 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:53:39,034 - -8.050 per-word bound, 265.1 perplexity estimate based on a held-out corpus of 1 documents with 2211 words
+2024-10-14 08:53:39,034 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:53:39,036 - topic #0 (0.333): 0.021*"’" + 0.009*"Rutland" + 0.006*"needs" + 0.006*"effective" + 0.005*"impact" + 0.005*"need" + 0.005*"positive" + 0.004*"15" + 0.004*"plans" + 0.004*"ensure"
+2024-10-14 08:53:39,036 - topic #1 (0.333): 0.017*"’" + 0.009*"Rutland" + 0.008*"needs" + 0.007*"effective" + 0.006*"impact" + 0.006*"need" + 0.006*"positive" + 0.006*"plans" + 0.006*"good" + 0.005*"practitioners"
+2024-10-14 08:53:39,036 - topic #2 (0.333): 0.018*"’" + 0.009*"Rutland" + 0.008*"needs" + 0.007*"impact" + 0.006*"effective" + 0.006*"positive" + 0.005*"plans" + 0.005*"26" + 0.005*"need" + 0.005*"well"
+2024-10-14 08:53:39,036 - topic diff=0.763896, rho=1.000000
+2024-10-14 08:53:39,036 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1089, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:53:39.036670', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:39,896 - Inspection date 2024-04-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:53:39,897 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:39,897 - Inspection date 2024-04-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:53:39,897 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:39,897 - Inspection date 2024-04-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:53:39,897 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:39,897 - Inspection date 2024-04-15 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:53:39,898 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:39,898 - Inspection date 2024-04-15 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:53:39,898 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:39,898 - Inspection date 2024-04-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:53:39,898 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:50,187 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:53:50,189 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)
+2024-10-14 08:53:50,189 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-10-14T08:53:50.189428', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:50,190 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:53:50,190 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:53:50,190 - using serial LDA version on this node
+2024-10-14 08:53:50,191 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:53:50,191 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:53:50,194 - -8.008 per-word bound, 257.4 perplexity estimate based on a held-out corpus of 1 documents with 2253 words
+2024-10-14 08:53:50,194 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:53:50,195 - topic #0 (0.333): 0.014*"’" + 0.006*"well" + 0.006*"effective" + 0.006*"plans" + 0.005*"Salford" + 0.005*"experiences" + 0.004*"needs" + 0.004*"practice" + 0.004*"6" + 0.004*"10"
+2024-10-14 08:53:50,196 - topic #1 (0.333): 0.011*"’" + 0.009*"well" + 0.009*"needs" + 0.008*"plans" + 0.007*"effective" + 0.006*"Salford" + 0.005*"planning" + 0.005*"progress" + 0.004*"6" + 0.004*"strong"
+2024-10-14 08:53:50,196 - topic #2 (0.333): 0.016*"’" + 0.008*"plans" + 0.008*"needs" + 0.006*"effective" + 0.006*"Salford" + 0.006*"practice" + 0.005*"well" + 0.005*"leaders" + 0.005*"planning" + 0.005*"quality"
+2024-10-14 08:53:50,196 - topic diff=0.790512, rho=1.000000
+2024-10-14 08:53:50,196 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:53:50.196487', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:53:51,094 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:53:51,094 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:51,094 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:53:51,094 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:51,094 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:53:51,095 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:51,095 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:53:51,095 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:51,095 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:53:51,095 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:53:51,095 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:53:51,095 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:00,287 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:54:00,289 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)
+2024-10-14 08:54:00,290 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-10-14T08:54:00.290143', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:00,291 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:54:00,291 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:54:00,291 - using serial LDA version on this node
+2024-10-14 08:54:00,291 - 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
+2024-10-14 08:54:00,291 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:54:00,295 - -7.942 per-word bound, 245.9 perplexity estimate based on a held-out corpus of 1 documents with 2066 words
+2024-10-14 08:54:00,295 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:54:00,296 - topic #0 (0.333): 0.016*"’" + 0.010*"needs" + 0.009*"Sandwell" + 0.007*"plans" + 0.007*"well" + 0.006*"quality" + 0.005*"9" + 0.005*"20" + 0.004*"Trust" + 0.004*"progress"
+2024-10-14 08:54:00,296 - topic #1 (0.333): 0.012*"’" + 0.008*"plans" + 0.008*"needs" + 0.007*"Sandwell" + 0.006*"well" + 0.006*"quality" + 0.006*"number" + 0.005*"Trust" + 0.005*"education" + 0.005*"progress"
+2024-10-14 08:54:00,296 - topic #2 (0.333): 0.013*"’" + 0.006*"well" + 0.006*"plans" + 0.005*"needs" + 0.005*"quality" + 0.005*"Sandwell" + 0.004*"Trust" + 0.004*"20" + 0.004*"receive" + 0.004*"number"
+2024-10-14 08:54:00,296 - topic diff=0.764491, rho=1.000000
+2024-10-14 08:54:00,297 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=995, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:54:00.296982', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:01,191 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:54:01,191 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:01,192 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:54:01,192 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:01,192 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:54:01,192 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:01,192 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:54:01,192 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:01,192 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:54:01,192 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:01,192 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:54:01,193 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:11,396 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:54:11,398 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)
+2024-10-14 08:54:11,398 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-10-14T08:54:11.398812', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:11,399 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:54:11,399 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:54:11,400 - using serial LDA version on this node
+2024-10-14 08:54:11,400 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:54:11,400 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:54:11,403 - -7.928 per-word bound, 243.6 perplexity estimate based on a held-out corpus of 1 documents with 2300 words
+2024-10-14 08:54:11,403 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:54:11,405 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.005*"including" + 0.005*"practice" + 0.005*"Sefton" + 0.005*"oversight" + 0.005*"management" + 0.005*"protection" + 0.004*"always" + 0.004*"identified"
+2024-10-14 08:54:11,405 - topic #1 (0.333): 0.017*"’" + 0.008*"needs" + 0.006*"oversight" + 0.006*"practice" + 0.006*"◼" + 0.005*"response" + 0.005*"many" + 0.005*"timely" + 0.005*"protection" + 0.005*"management"
+2024-10-14 08:54:11,405 - topic #2 (0.333): 0.014*"’" + 0.010*"needs" + 0.007*"practice" + 0.006*"lack" + 0.005*"4" + 0.005*"many" + 0.005*"oversight" + 0.005*"including" + 0.005*"protection" + 0.005*"always"
+2024-10-14 08:54:11,405 - topic diff=0.788327, rho=1.000000
+2024-10-14 08:54:11,405 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:54:11.405734', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:12,279 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:54:12,279 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:12,280 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:54:12,280 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:12,280 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:54:12,280 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:12,280 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:54:12,280 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:12,280 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:54:12,281 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:12,281 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:54:12,281 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:22,994 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:54:22,996 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)
+2024-10-14 08:54:22,996 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-10-14T08:54:22.996631', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:22,997 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:54:22,997 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:54:22,998 - using serial LDA version on this node
+2024-10-14 08:54:22,998 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:54:22,998 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:54:23,002 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2327 words
+2024-10-14 08:54:23,002 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:54:23,003 - topic #0 (0.333): 0.018*"’" + 0.011*"Sheffield" + 0.007*"needs" + 0.006*"leaders" + 0.006*"practice" + 0.006*"well" + 0.005*"quality" + 0.004*"experiences" + 0.004*"ensure" + 0.004*"health"
+2024-10-14 08:54:23,003 - topic #1 (0.333): 0.026*"’" + 0.012*"Sheffield" + 0.010*"needs" + 0.008*"well" + 0.007*"health" + 0.006*"practice" + 0.005*"leaders" + 0.005*"mental" + 0.005*"good" + 0.005*"adviser"
+2024-10-14 08:54:23,003 - topic #2 (0.333): 0.012*"’" + 0.008*"Sheffield" + 0.006*"needs" + 0.005*"leaders" + 0.005*"well" + 0.004*"plans" + 0.004*"health" + 0.004*"2023" + 0.004*"quality" + 0.004*"experiences"
+2024-10-14 08:54:23,003 - topic diff=0.788800, rho=1.000000
+2024-10-14 08:54:23,004 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:54:23.004131', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:23,869 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:54:23,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:23,869 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:54:23,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:23,869 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:54:23,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:23,870 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:54:23,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:23,870 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:54:23,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:23,870 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:54:23,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:31,851 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:54:31,853 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)
+2024-10-14 08:54:31,853 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-10-14T08:54:31.853223', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:31,854 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:54:31,854 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:54:31,854 - using serial LDA version on this node
+2024-10-14 08:54:31,854 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:54:31,854 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:54:31,857 - -7.958 per-word bound, 248.7 perplexity estimate based on a held-out corpus of 1 documents with 1749 words
+2024-10-14 08:54:31,858 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:54:31,859 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"Shropshire" + 0.007*"plans" + 0.006*"2022" + 0.005*"progress" + 0.005*"need" + 0.005*"making" + 0.005*"practice"
+2024-10-14 08:54:31,859 - topic #1 (0.333): 0.013*"’" + 0.008*"needs" + 0.006*"Shropshire" + 0.006*"progress" + 0.005*"making" + 0.005*"well" + 0.005*"plans" + 0.004*"training" + 0.004*"practice" + 0.004*"11"
+2024-10-14 08:54:31,859 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"Shropshire" + 0.006*"well" + 0.006*"progress" + 0.005*"2022" + 0.005*"7" + 0.005*"making" + 0.004*"effective" + 0.004*"plans"
+2024-10-14 08:54:31,859 - topic diff=0.716166, rho=1.000000
+2024-10-14 08:54:31,859 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=939, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:54:31.859773', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:32,766 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:54:32,766 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:32,767 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:54:32,767 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:32,767 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:54:32,767 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:32,767 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:54:32,768 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:32,768 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:54:32,768 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:32,768 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:54:32,768 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:43,849 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:54:43,851 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)
+2024-10-14 08:54:43,851 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-10-14T08:54:43.851686', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:43,852 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:54:43,852 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:54:43,853 - using serial LDA version on this node
+2024-10-14 08:54:43,853 - 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
+2024-10-14 08:54:43,853 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:54:43,857 - -8.043 per-word bound, 263.7 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
+2024-10-14 08:54:43,857 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:54:43,858 - topic #0 (0.333): 0.015*"’" + 0.009*"Slough" + 0.008*"quality" + 0.006*"plans" + 0.006*"needs" + 0.005*"practice" + 0.005*"impact" + 0.005*"3" + 0.005*"However" + 0.005*"supported"
+2024-10-14 08:54:43,858 - topic #1 (0.333): 0.018*"’" + 0.008*"plans" + 0.007*"Slough" + 0.006*"practice" + 0.006*"needs" + 0.005*"quality" + 0.005*"3" + 0.005*"leaders" + 0.005*"PAs" + 0.005*"impact"
+2024-10-14 08:54:43,858 - topic #2 (0.333): 0.014*"’" + 0.007*"Slough" + 0.007*"needs" + 0.004*"leaders" + 0.004*"practice" + 0.004*"need" + 0.004*"23" + 0.004*"senior" + 0.004*"plans" + 0.004*"supported"
+2024-10-14 08:54:43,858 - topic diff=0.786141, rho=1.000000
+2024-10-14 08:54:43,859 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1113, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:54:43.859004', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:44,649 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:54:44,649 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:44,649 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:54:44,649 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:44,650 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:54:44,650 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:44,650 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:54:44,650 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:44,650 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:54:44,650 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:44,650 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:54:44,650 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:54,783 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:54:54,785 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)
+2024-10-14 08:54:54,785 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-10-14T08:54:54.785711', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:54,786 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:54:54,786 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:54:54,787 - using serial LDA version on this node
+2024-10-14 08:54:54,787 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:54:54,787 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:54:54,790 - -7.919 per-word bound, 242.0 perplexity estimate based on a held-out corpus of 1 documents with 2163 words
+2024-10-14 08:54:54,790 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:54:54,792 - topic #0 (0.333): 0.015*"’" + 0.011*"lack" + 0.009*"2022" + 0.007*"need" + 0.007*"Solihull" + 0.006*"risk" + 0.005*"effective" + 0.005*"practice" + 0.005*"quality" + 0.005*"significant"
+2024-10-14 08:54:54,792 - topic #1 (0.333): 0.014*"’" + 0.011*"lack" + 0.009*"2022" + 0.006*"quality" + 0.006*"risk" + 0.005*"delay" + 0.005*"Solihull" + 0.005*"worker" + 0.005*"significant" + 0.005*"means"
+2024-10-14 08:54:54,792 - topic #2 (0.333): 0.016*"’" + 0.009*"lack" + 0.006*"2022" + 0.006*"experiences" + 0.006*"practice" + 0.006*"Solihull" + 0.006*"need" + 0.005*"quality" + 0.005*"risk" + 0.005*"significant"
+2024-10-14 08:54:54,792 - topic diff=0.788260, rho=1.000000
+2024-10-14 08:54:54,792 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=996, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:54:54.792764', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:54:55,681 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:54:55,681 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:55,682 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:54:55,682 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:55,682 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:54:55,682 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:55,682 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:54:55,682 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:55,683 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:54:55,683 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:54:55,683 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:54:55,683 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:05,470 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:55:05,472 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)
+2024-10-14 08:55:05,472 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-10-14T08:55:05.472866', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:05,474 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:55:05,474 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:55:05,474 - using serial LDA version on this node
+2024-10-14 08:55:05,474 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:55:05,474 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:55:05,478 - -7.928 per-word bound, 243.5 perplexity estimate based on a held-out corpus of 1 documents with 2181 words
+2024-10-14 08:55:05,478 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:55:05,479 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.008*"Somerset" + 0.007*"plans" + 0.006*"good" + 0.006*"leaders" + 0.006*"well" + 0.005*"including" + 0.005*"effective" + 0.005*"need"
+2024-10-14 08:55:05,479 - topic #1 (0.333): 0.019*"’" + 0.012*"well" + 0.008*"needs" + 0.007*"Somerset" + 0.006*"plans" + 0.006*"leaders" + 0.006*"supported" + 0.005*"need" + 0.005*"practice" + 0.005*"including"
+2024-10-14 08:55:05,479 - topic #2 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"good" + 0.005*"supported" + 0.005*"18" + 0.005*"Somerset" + 0.005*"number" + 0.005*"practice" + 0.005*"progress"
+2024-10-14 08:55:05,479 - topic diff=0.806895, rho=1.000000
+2024-10-14 08:55:05,479 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:55:05.479941', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:06,382 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:55:06,383 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:06,383 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:55:06,383 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:06,383 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:55:06,383 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:06,383 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:55:06,383 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:06,384 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:55:06,384 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:06,384 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:55:06,384 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:17,750 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:55:17,753 - built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)
+2024-10-14 08:55:17,753 - Dictionary lifecycle event {'msg': "built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)", 'datetime': '2024-10-14T08:55:17.753459', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:17,754 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:55:17,754 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:55:17,754 - using serial LDA version on this node
+2024-10-14 08:55:17,755 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:55:17,755 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:55:17,759 - -8.055 per-word bound, 266.0 perplexity estimate based on a held-out corpus of 1 documents with 2751 words
+2024-10-14 08:55:17,759 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:55:17,760 - topic #0 (0.333): 0.023*"’" + 0.010*"needs" + 0.007*"leaders" + 0.006*"2024" + 0.006*"well" + 0.006*"June" + 0.005*"ensure" + 0.005*"strong" + 0.004*"South" + 0.004*"3"
+2024-10-14 08:55:17,760 - topic #1 (0.333): 0.016*"’" + 0.010*"needs" + 0.008*"June" + 0.007*"2024" + 0.006*"leaders" + 0.006*"understand" + 0.006*"effective" + 0.006*"well" + 0.006*"progress" + 0.006*"ensure"
+2024-10-14 08:55:17,760 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.006*"leaders" + 0.005*"plans" + 0.005*"June" + 0.005*"2024" + 0.005*"effective" + 0.004*"ensure" + 0.004*"quality" + 0.004*"progress"
+2024-10-14 08:55:17,760 - topic diff=0.840963, rho=1.000000
+2024-10-14 08:55:17,760 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1188, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:55:17.760932', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:18,679 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:55:18,679 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:18,680 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:55:18,680 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:18,680 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:55:18,680 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:18,680 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:55:18,680 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:18,680 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:55:18,680 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:18,681 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:55:18,681 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:28,058 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:55:28,060 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions)
+2024-10-14 08:55:28,060 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-10-14T08:55:28.060155', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:28,061 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:55:28,061 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:55:28,061 - using serial LDA version on this node
+2024-10-14 08:55:28,061 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:55:28,061 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:55:28,064 - -7.887 per-word bound, 236.7 perplexity estimate based on a held-out corpus of 1 documents with 2189 words
+2024-10-14 08:55:28,065 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:55:28,066 - topic #0 (0.333): 0.023*"’" + 0.012*"needs" + 0.008*"Tyneside" + 0.008*"South" + 0.006*"oversight" + 0.005*"9" + 0.005*"2022" + 0.005*"effective" + 0.005*"management" + 0.005*"15"
+2024-10-14 08:55:28,066 - topic #1 (0.333): 0.026*"’" + 0.008*"needs" + 0.008*"South" + 0.007*"Tyneside" + 0.006*"However" + 0.005*"management" + 0.005*"5" + 0.005*"plans" + 0.005*"oversight" + 0.005*"carers"
+2024-10-14 08:55:28,066 - topic #2 (0.333): 0.022*"’" + 0.006*"needs" + 0.005*"South" + 0.005*"Tyneside" + 0.005*"carers" + 0.004*"effective" + 0.004*"risk" + 0.004*"2023" + 0.004*"practice" + 0.004*"oversight"
+2024-10-14 08:55:28,066 - topic diff=0.799860, rho=1.000000
+2024-10-14 08:55:28,066 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=981, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:55:28.066731', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:29,015 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:55:29,016 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:29,016 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:55:29,016 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:29,016 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:55:29,016 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:29,016 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:55:29,017 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:29,017 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:55:29,017 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:29,017 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:55:29,017 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:39,568 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:55:39,570 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)
+2024-10-14 08:55:39,571 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-10-14T08:55:39.570987', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:39,572 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:55:39,572 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:55:39,572 - using serial LDA version on this node
+2024-10-14 08:55:39,572 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:55:39,572 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:55:39,576 - -8.151 per-word bound, 284.2 perplexity estimate based on a held-out corpus of 1 documents with 2318 words
+2024-10-14 08:55:39,576 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:55:39,578 - topic #0 (0.333): 0.011*"’" + 0.005*"improve" + 0.005*"Southampton" + 0.005*"5" + 0.005*"needs" + 0.005*"provide" + 0.005*"plans" + 0.004*"16" + 0.004*"2023" + 0.004*"experiences"
+2024-10-14 08:55:39,578 - topic #1 (0.333): 0.021*"’" + 0.007*"plans" + 0.006*"Southampton" + 0.006*"including" + 0.005*"progress" + 0.005*"needs" + 0.005*"experiences" + 0.004*"improve" + 0.004*"good" + 0.004*"June"
+2024-10-14 08:55:39,578 - topic #2 (0.333): 0.013*"’" + 0.005*"plans" + 0.005*"progress" + 0.005*"Southampton" + 0.005*"5" + 0.005*"leaders" + 0.004*"2023" + 0.004*"improve" + 0.004*"June" + 0.004*"including"
+2024-10-14 08:55:39,578 - topic diff=0.750112, rho=1.000000
+2024-10-14 08:55:39,578 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1178, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:55:39.578530', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:40,366 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:55:40,367 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:40,367 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:55:40,367 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:40,367 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:55:40,367 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:40,368 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:55:40,368 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:40,368 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:55:40,368 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:40,368 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:55:40,368 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:50,075 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:55:50,078 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)
+2024-10-14 08:55:50,078 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-10-14T08:55:50.078211', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:50,079 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:55:50,079 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:55:50,079 - using serial LDA version on this node
+2024-10-14 08:55:50,079 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:55:50,079 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:55:50,083 - -7.952 per-word bound, 247.6 perplexity estimate based on a held-out corpus of 1 documents with 2086 words
+2024-10-14 08:55:50,083 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:55:50,084 - topic #0 (0.333): 0.015*"’" + 0.009*"planning" + 0.008*"quality" + 0.006*"practice" + 0.006*"within" + 0.006*"effective" + 0.006*"always" + 0.006*"protection" + 0.005*"number" + 0.005*"risk"
+2024-10-14 08:55:50,084 - topic #1 (0.333): 0.014*"’" + 0.007*"planning" + 0.007*"practice" + 0.007*"leaders" + 0.006*"quality" + 0.005*"number" + 0.005*"needs" + 0.005*"protection" + 0.005*"well" + 0.004*"risks"
+2024-10-14 08:55:50,084 - topic #2 (0.333): 0.011*"’" + 0.007*"practice" + 0.007*"leaders" + 0.007*"planning" + 0.005*"good" + 0.005*"protection" + 0.005*"quality" + 0.005*"number" + 0.005*"need" + 0.004*"progress"
+2024-10-14 08:55:50,084 - topic diff=0.773334, rho=1.000000
+2024-10-14 08:55:50,085 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:55:50.085077', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:55:52,034 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:55:52,034 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:52,035 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:55:52,035 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:52,035 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:55:52,035 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:52,035 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:55:52,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:52,036 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:55:52,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:55:52,036 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:55:52,036 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:03,967 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:56:03,969 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)
+2024-10-14 08:56:03,970 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-10-14T08:56:03.970056', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:03,971 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:56:03,971 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:56:03,971 - using serial LDA version on this node
+2024-10-14 08:56:03,971 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:56:03,971 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:56:03,975 - -8.056 per-word bound, 266.1 perplexity estimate based on a held-out corpus of 1 documents with 2218 words
+2024-10-14 08:56:03,975 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:56:03,976 - topic #0 (0.333): 0.015*"’" + 0.009*"needs" + 0.008*"St" + 0.007*"well" + 0.007*"Helens" + 0.006*"progress" + 0.005*"receive" + 0.005*"need" + 0.005*"10" + 0.004*"risk"
+2024-10-14 08:56:03,977 - topic #1 (0.333): 0.012*"’" + 0.007*"St" + 0.007*"needs" + 0.006*"Helens" + 0.006*"receive" + 0.006*"well" + 0.006*"progress" + 0.005*"21" + 0.005*"good" + 0.005*"10"
+2024-10-14 08:56:03,977 - topic #2 (0.333): 0.019*"’" + 0.009*"Helens" + 0.008*"St" + 0.006*"well" + 0.006*"progress" + 0.006*"need" + 0.006*"good" + 0.006*"21" + 0.006*"10" + 0.006*"risk"
+2024-10-14 08:56:03,977 - topic diff=0.774092, rho=1.000000
+2024-10-14 08:56:03,977 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:56:03.977357', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:04,994 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:56:04,995 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:04,995 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:56:04,995 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:04,995 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:56:04,995 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:04,995 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:56:04,996 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:04,996 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:56:04,996 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:04,996 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:56:04,996 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:15,492 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:56:15,494 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)
+2024-10-14 08:56:15,495 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-10-14T08:56:15.495111', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:15,496 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:56:15,496 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:56:15,496 - using serial LDA version on this node
+2024-10-14 08:56:15,496 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:56:15,496 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:56:15,500 - -8.002 per-word bound, 256.4 perplexity estimate based on a held-out corpus of 1 documents with 2334 words
+2024-10-14 08:56:15,500 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:56:15,501 - topic #0 (0.333): 0.017*"’" + 0.012*"needs" + 0.007*"Staffordshire" + 0.006*"practice" + 0.005*"health" + 0.005*"ensure" + 0.005*"oversight" + 0.005*"progress" + 0.005*"well" + 0.004*"impact"
+2024-10-14 08:56:15,501 - topic #1 (0.333): 0.011*"’" + 0.009*"needs" + 0.007*"quality" + 0.006*"ensure" + 0.006*"practice" + 0.005*"health" + 0.005*"plans" + 0.005*"oversight" + 0.005*"Staffordshire" + 0.004*"progress"
+2024-10-14 08:56:15,501 - topic #2 (0.333): 0.022*"’" + 0.012*"needs" + 0.007*"progress" + 0.006*"oversight" + 0.006*"quality" + 0.005*"health" + 0.005*"6" + 0.005*"practice" + 0.005*"ensure" + 0.005*"plans"
+2024-10-14 08:56:15,502 - topic diff=0.800137, rho=1.000000
+2024-10-14 08:56:15,502 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:56:15.502156', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:16,357 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:56:16,358 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:16,358 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:56:16,358 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:16,358 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:56:16,358 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:16,359 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:56:16,359 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:16,359 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:56:16,359 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:16,360 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:56:16,360 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:25,717 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:56:25,719 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
+2024-10-14 08:56:25,719 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-10-14T08:56:25.719443', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:25,720 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:56:25,720 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:56:25,720 - using serial LDA version on this node
+2024-10-14 08:56:25,721 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:56:25,721 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:56:25,724 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
+2024-10-14 08:56:25,724 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:56:25,726 - topic #0 (0.333): 0.010*"’" + 0.010*"well" + 0.006*"Stockport" + 0.006*"needs" + 0.006*"practice" + 0.006*"strong" + 0.006*"plans" + 0.005*"quality" + 0.005*"leaders" + 0.005*"risk"
+2024-10-14 08:56:25,726 - topic #1 (0.333): 0.011*"’" + 0.008*"practice" + 0.007*"well" + 0.006*"Stockport" + 0.006*"needs" + 0.005*"strong" + 0.005*"ensure" + 0.005*"team" + 0.005*"risk" + 0.005*"plans"
+2024-10-14 08:56:25,726 - topic #2 (0.333): 0.012*"’" + 0.008*"well" + 0.007*"Stockport" + 0.007*"practice" + 0.005*"needs" + 0.005*"strong" + 0.004*"plans" + 0.004*"risk" + 0.004*"28" + 0.004*"range"
+2024-10-14 08:56:25,726 - topic diff=0.791638, rho=1.000000
+2024-10-14 08:56:25,726 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1060, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:56:25.726585', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:26,676 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:56:26,676 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:26,677 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:56:26,677 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:26,677 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:56:26,677 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:26,677 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:56:26,677 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:26,677 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:56:26,677 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:26,678 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:56:26,678 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:36,870 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:56:36,872 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)
+2024-10-14 08:56:36,872 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-10-14T08:56:36.872564', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:36,873 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:56:36,873 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:56:36,873 - using serial LDA version on this node
+2024-10-14 08:56:36,874 - 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
+2024-10-14 08:56:36,874 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:56:36,877 - -7.966 per-word bound, 250.0 perplexity estimate based on a held-out corpus of 1 documents with 2269 words
+2024-10-14 08:56:36,877 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:56:36,879 - topic #0 (0.333): 0.022*"’" + 0.009*"leaders" + 0.008*"plans" + 0.007*"quality" + 0.006*"well" + 0.006*"on-Tees" + 0.006*"needs" + 0.006*"Stockton" + 0.005*"senior" + 0.005*"carers"
+2024-10-14 08:56:36,879 - topic #1 (0.333): 0.016*"’" + 0.008*"plans" + 0.007*"leaders" + 0.007*"good" + 0.007*"needs" + 0.007*"well" + 0.006*"Stockton" + 0.006*"on-Tees" + 0.006*"quality" + 0.004*"17"
+2024-10-14 08:56:36,879 - topic #2 (0.333): 0.019*"’" + 0.009*"leaders" + 0.009*"plans" + 0.007*"needs" + 0.006*"well" + 0.005*"good" + 0.005*"Stockton" + 0.005*"on-Tees" + 0.005*"senior" + 0.005*"quality"
+2024-10-14 08:56:36,879 - topic diff=0.772602, rho=1.000000
+2024-10-14 08:56:36,879 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1044, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:56:36.879512', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:37,808 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:56:37,808 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:37,808 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:56:37,808 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:37,809 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:56:37,809 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:37,809 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:56:37,809 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:37,809 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:56:37,809 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:37,809 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:56:37,809 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:48,031 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:56:48,033 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)
+2024-10-14 08:56:48,033 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-10-14T08:56:48.033392', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:48,034 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:56:48,034 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:56:48,034 - using serial LDA version on this node
+2024-10-14 08:56:48,035 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:56:48,035 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:56:48,038 - -7.903 per-word bound, 239.4 perplexity estimate based on a held-out corpus of 1 documents with 2165 words
+2024-10-14 08:56:48,038 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:56:48,039 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"protection" + 0.007*"well" + 0.007*"However" + 0.007*"on-Trent" + 0.006*"plans" + 0.006*"ensure" + 0.005*"Stoke" + 0.005*"14"
+2024-10-14 08:56:48,039 - topic #1 (0.333): 0.016*"’" + 0.007*"Stoke" + 0.007*"on-Trent" + 0.007*"plans" + 0.006*"needs" + 0.006*"well" + 0.006*"However" + 0.005*"progress" + 0.005*"protection" + 0.005*"ensure"
+2024-10-14 08:56:48,039 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"Stoke" + 0.007*"well" + 0.007*"on-Trent" + 0.006*"plans" + 0.006*"However" + 0.005*"ensure" + 0.005*"3" + 0.005*"quality"
+2024-10-14 08:56:48,039 - topic diff=0.779175, rho=1.000000
+2024-10-14 08:56:48,040 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=986, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:56:48.040045', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:56:48,916 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:56:48,916 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:48,916 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:56:48,916 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:48,916 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:56:48,916 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:48,917 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:56:48,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:48,917 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:56:48,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:56:48,917 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:56:48,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:01,161 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:57:01,163 - built Dictionary<1126 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2544 corpus positions)
+2024-10-14 08:57:01,163 - Dictionary lifecycle event {'msg': 'built Dictionary<1126 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2544 corpus positions)', 'datetime': '2024-10-14T08:57:01.163799', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:01,164 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:57:01,164 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:57:01,165 - using serial LDA version on this node
+2024-10-14 08:57:01,165 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:57:01,165 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:57:01,169 - -8.023 per-word bound, 260.1 perplexity estimate based on a held-out corpus of 1 documents with 2544 words
+2024-10-14 08:57:01,169 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:57:01,170 - topic #0 (0.333): 0.018*"’" + 0.012*"Suffolk" + 0.010*"needs" + 0.009*"well" + 0.005*"protection" + 0.005*"3" + 0.005*"practice" + 0.005*"Council" + 0.004*"County" + 0.004*"plans"
+2024-10-14 08:57:01,170 - topic #1 (0.333): 0.020*"’" + 0.009*"well" + 0.008*"Suffolk" + 0.008*"needs" + 0.005*"leaders" + 0.004*"County" + 0.004*"2024" + 0.004*"practice" + 0.004*"7" + 0.004*"June"
+2024-10-14 08:57:01,170 - topic #2 (0.333): 0.023*"’" + 0.012*"needs" + 0.009*"Suffolk" + 0.006*"well" + 0.005*"practice" + 0.005*"Council" + 0.005*"parents" + 0.005*"plans" + 0.005*"risks" + 0.005*"protection"
+2024-10-14 08:57:01,170 - topic diff=0.813485, rho=1.000000
+2024-10-14 08:57:01,171 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1126, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:57:01.171005', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:03,541 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:57:03,541 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:03,541 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:57:03,541 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:03,541 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:57:03,541 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:03,541 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:57:03,541 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:03,542 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:57:03,542 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:03,542 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:57:03,542 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:14,125 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:57:14,127 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)
+2024-10-14 08:57:14,128 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-10-14T08:57:14.128149', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:14,129 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:57:14,129 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:57:14,129 - using serial LDA version on this node
+2024-10-14 08:57:14,129 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:57:14,130 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:57:14,133 - -8.049 per-word bound, 264.8 perplexity estimate based on a held-out corpus of 1 documents with 2409 words
+2024-10-14 08:57:14,133 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:57:14,134 - topic #0 (0.333): 0.012*"’" + 0.007*"well" + 0.005*"needs" + 0.005*"quality" + 0.005*"Sunderland" + 0.005*"good" + 0.004*"practice" + 0.004*"council" + 0.004*"protection" + 0.004*"parents"
+2024-10-14 08:57:14,135 - topic #1 (0.333): 0.020*"’" + 0.008*"quality" + 0.008*"well" + 0.007*"needs" + 0.007*"Sunderland" + 0.006*"experienced" + 0.006*"TfC" + 0.005*"practice" + 0.005*"robust" + 0.005*"parents"
+2024-10-14 08:57:14,135 - topic #2 (0.333): 0.011*"’" + 0.005*"well" + 0.005*"needs" + 0.005*"quality" + 0.004*"Sunderland" + 0.004*"highly" + 0.004*"protection" + 0.004*"risk" + 0.004*"experienced" + 0.003*"result"
+2024-10-14 08:57:14,135 - topic diff=0.805220, rho=1.000000
+2024-10-14 08:57:14,135 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1128, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:57:14.135563', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:15,350 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:57:15,354 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:15,354 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:57:15,355 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:15,355 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:57:15,355 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:15,355 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:57:15,355 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:15,356 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:57:15,356 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:15,356 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:57:15,356 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:24,830 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:57:24,832 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)
+2024-10-14 08:57:24,832 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-10-14T08:57:24.832480', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:24,833 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:57:24,833 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:57:24,833 - using serial LDA version on this node
+2024-10-14 08:57:24,834 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:57:24,834 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:57:24,837 - -7.968 per-word bound, 250.3 perplexity estimate based on a held-out corpus of 1 documents with 2111 words
+2024-10-14 08:57:24,837 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:57:24,838 - topic #0 (0.333): 0.011*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"progress" + 0.006*"carers" + 0.005*"quality" + 0.005*"effective" + 0.005*"practice" + 0.005*"17" + 0.005*"plans"
+2024-10-14 08:57:24,838 - topic #1 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"well" + 0.006*"practice" + 0.005*"plans" + 0.005*"progress" + 0.004*"However" + 0.004*"effective" + 0.004*"good" + 0.004*"quality"
+2024-10-14 08:57:24,839 - topic #2 (0.333): 0.013*"’" + 0.011*"needs" + 0.011*"well" + 0.009*"practice" + 0.008*"progress" + 0.005*"plans" + 0.005*"good" + 0.005*"17" + 0.005*"carers" + 0.005*"quality"
+2024-10-14 08:57:24,839 - topic diff=0.761882, rho=1.000000
+2024-10-14 08:57:24,839 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1016, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:57:24.839352', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:25,818 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:57:25,818 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:25,818 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:57:25,818 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:25,818 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:57:25,819 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:25,819 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:57:25,819 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:25,819 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:57:25,819 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:25,819 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:57:25,819 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:35,604 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:57:35,606 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)
+2024-10-14 08:57:35,606 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-10-14T08:57:35.606931', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:35,607 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:57:35,608 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:57:35,608 - using serial LDA version on this node
+2024-10-14 08:57:35,608 - 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
+2024-10-14 08:57:35,608 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:57:35,611 - -7.825 per-word bound, 226.8 perplexity estimate based on a held-out corpus of 1 documents with 2229 words
+2024-10-14 08:57:35,611 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:57:35,613 - topic #0 (0.333): 0.025*"’" + 0.013*"needs" + 0.010*"Swindon" + 0.008*"need" + 0.007*"well" + 0.006*"impact" + 0.006*"plans" + 0.006*"many" + 0.005*"lack" + 0.005*"always"
+2024-10-14 08:57:35,613 - topic #1 (0.333): 0.014*"’" + 0.010*"needs" + 0.009*"well" + 0.008*"Swindon" + 0.007*"need" + 0.006*"impact" + 0.006*"effective" + 0.005*"Borough" + 0.005*"health" + 0.005*"always"
+2024-10-14 08:57:35,613 - topic #2 (0.333): 0.025*"’" + 0.015*"needs" + 0.009*"Swindon" + 0.009*"need" + 0.008*"well" + 0.008*"always" + 0.008*"plans" + 0.006*"health" + 0.005*"Council" + 0.005*"practice"
+2024-10-14 08:57:35,613 - topic diff=0.826250, rho=1.000000
+2024-10-14 08:57:35,613 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=951, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-10-14T08:57:35.613530', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:36,588 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:57:36,588 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:36,588 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:57:36,588 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:36,588 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:57:36,589 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:36,589 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:57:36,589 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:36,589 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:57:36,589 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:36,589 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:57:36,589 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:47,687 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:57:47,690 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)
+2024-10-14 08:57:47,690 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-10-14T08:57:47.690339', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:47,691 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:57:47,691 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:57:47,691 - using serial LDA version on this node
+2024-10-14 08:57:47,692 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:57:47,692 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:57:47,696 - -7.947 per-word bound, 246.8 perplexity estimate based on a held-out corpus of 1 documents with 2491 words
+2024-10-14 08:57:47,696 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:57:47,697 - topic #0 (0.333): 0.015*"’" + 0.011*"needs" + 0.007*"impact" + 0.006*"risk" + 0.005*"practice" + 0.005*"December" + 0.005*"planning" + 0.005*"experienced" + 0.005*"response" + 0.005*"Tameside"
+2024-10-14 08:57:47,697 - topic #1 (0.333): 0.016*"’" + 0.007*"risk" + 0.006*"needs" + 0.006*"quality" + 0.006*"impact" + 0.006*"practice" + 0.006*"2023" + 0.005*"4" + 0.004*"need" + 0.004*"experienced"
+2024-10-14 08:57:47,697 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.006*"experienced" + 0.006*"quality" + 0.006*"response" + 0.005*"impact" + 0.005*"risk" + 0.005*"understand" + 0.005*"2023" + 0.005*"4"
+2024-10-14 08:57:47,697 - topic diff=0.821978, rho=1.000000
+2024-10-14 08:57:47,698 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:57:47.698049', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:57:48,673 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:57:48,674 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:48,674 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:57:48,674 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:48,674 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:57:48,674 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:48,674 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:57:48,674 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:48,675 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:57:48,675 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:57:48,675 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:57:48,675 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:00,296 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:58:00,298 - built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)
+2024-10-14 08:58:00,299 - Dictionary lifecycle event {'msg': "built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)", 'datetime': '2024-10-14T08:58:00.298999', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:00,300 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:58:00,300 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:58:00,300 - using serial LDA version on this node
+2024-10-14 08:58:00,300 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:58:00,300 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:58:00,304 - -7.973 per-word bound, 251.2 perplexity estimate based on a held-out corpus of 1 documents with 2452 words
+2024-10-14 08:58:00,304 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:58:00,305 - topic #0 (0.333): 0.023*"’" + 0.011*"needs" + 0.008*"Wrekin" + 0.008*"Telford" + 0.007*"effective" + 0.006*"benefit" + 0.006*"Family" + 0.005*"well" + 0.005*"plans" + 0.004*"3"
+2024-10-14 08:58:00,305 - topic #1 (0.333): 0.022*"’" + 0.012*"needs" + 0.009*"Telford" + 0.008*"Wrekin" + 0.007*"benefit" + 0.006*"well" + 0.006*"plans" + 0.005*"3" + 0.005*"live" + 0.005*"PAs"
+2024-10-14 08:58:00,305 - topic #2 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"Wrekin" + 0.006*"Telford" + 0.005*"well" + 0.005*"Family" + 0.005*"plans" + 0.005*"effective" + 0.005*"benefit" + 0.005*"leaders"
+2024-10-14 08:58:00,305 - topic diff=0.822039, rho=1.000000
+2024-10-14 08:58:00,306 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1077, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:58:00.306095', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:01,541 - Inspection date 2024-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:58:01,541 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:01,542 - Inspection date 2024-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:58:01,542 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:01,542 - Inspection date 2024-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:58:01,542 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:01,542 - Inspection date 2024-04-29 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:58:01,542 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:01,542 - Inspection date 2024-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:58:01,542 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:01,543 - Inspection date 2024-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:58:01,543 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:11,475 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:58:11,479 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)
+2024-10-14 08:58:11,480 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-10-14T08:58:11.479992', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:11,482 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:58:11,482 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:58:11,482 - using serial LDA version on this node
+2024-10-14 08:58:11,483 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:58:11,483 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:58:11,489 - -8.140 per-word bound, 282.1 perplexity estimate based on a held-out corpus of 1 documents with 2160 words
+2024-10-14 08:58:11,489 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:58:11,491 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.005*"carers" + 0.005*"need" + 0.004*"practice" + 0.004*"impact" + 0.004*"effective" + 0.004*"needs" + 0.004*"ensure" + 0.003*"leaders"
+2024-10-14 08:58:11,492 - topic #1 (0.333): 0.011*"’" + 0.008*"well" + 0.005*"carers" + 0.004*"needs" + 0.004*"need" + 0.004*"ensure" + 0.004*"practice" + 0.004*"Thurrock" + 0.004*"plans" + 0.004*"protection"
+2024-10-14 08:58:11,492 - topic #2 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"carers" + 0.005*"need" + 0.005*"needs" + 0.004*"effective" + 0.004*"leaders" + 0.004*"ensure" + 0.004*"Thurrock" + 0.004*"practice"
+2024-10-14 08:58:11,492 - topic diff=0.730410, rho=1.000000
+2024-10-14 08:58:11,492 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1138, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:58:11.492726', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:13,388 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:58:13,389 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:13,389 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:58:13,389 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:13,389 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:58:13,389 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:13,389 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:58:13,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:13,390 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:58:13,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:13,390 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:58:13,390 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:22,473 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:58:22,477 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)
+2024-10-14 08:58:22,477 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-10-14T08:58:22.477520', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:22,479 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:58:22,479 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:58:22,480 - using serial LDA version on this node
+2024-10-14 08:58:22,480 - 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
+2024-10-14 08:58:22,480 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:58:22,486 - -8.039 per-word bound, 262.9 perplexity estimate based on a held-out corpus of 1 documents with 2065 words
+2024-10-14 08:58:22,486 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:58:22,489 - topic #0 (0.333): 0.016*"’" + 0.011*"well" + 0.007*"Torbay" + 0.007*"good" + 0.006*"needs" + 0.005*"progress" + 0.005*"timely" + 0.005*"effective" + 0.005*"plans" + 0.004*"21"
+2024-10-14 08:58:22,489 - topic #1 (0.333): 0.021*"’" + 0.008*"well" + 0.008*"Torbay" + 0.006*"good" + 0.006*"effective" + 0.005*"needs" + 0.005*"team" + 0.004*"21" + 0.004*"2022" + 0.004*"1"
+2024-10-14 08:58:22,489 - topic #2 (0.333): 0.010*"’" + 0.008*"well" + 0.007*"Torbay" + 0.006*"needs" + 0.004*"good" + 0.004*"education" + 0.004*"plans" + 0.004*"effective" + 0.004*"ensure" + 0.004*"April"
+2024-10-14 08:58:22,489 - topic diff=0.754652, rho=1.000000
+2024-10-14 08:58:22,490 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1054, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:58:22.490108', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:23,552 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:58:23,552 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:23,553 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:58:23,553 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:23,553 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:58:23,553 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:23,553 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:58:23,553 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:23,553 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:58:23,553 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:23,554 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:58:23,554 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:35,303 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:58:35,305 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)
+2024-10-14 08:58:35,305 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-10-14T08:58:35.305620', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:35,306 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:58:35,306 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:58:35,306 - using serial LDA version on this node
+2024-10-14 08:58:35,307 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:58:35,307 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:58:35,310 - -7.913 per-word bound, 241.1 perplexity estimate based on a held-out corpus of 1 documents with 2448 words
+2024-10-14 08:58:35,310 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:58:35,312 - topic #0 (0.333): 0.014*"’" + 0.010*"needs" + 0.007*"Trafford" + 0.006*"quality" + 0.006*"well" + 0.006*"plans" + 0.005*"ensure" + 0.005*"placed" + 0.005*"2" + 0.004*"family"
+2024-10-14 08:58:35,312 - topic #1 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"Trafford" + 0.006*"well" + 0.005*"quality" + 0.005*"plans" + 0.005*"worker" + 0.005*"placed" + 0.005*"leaders" + 0.004*"practice"
+2024-10-14 08:58:35,312 - topic #2 (0.333): 0.018*"’" + 0.009*"needs" + 0.009*"Trafford" + 0.009*"plans" + 0.008*"well" + 0.007*"leaders" + 0.007*"quality" + 0.006*"practice" + 0.006*"team" + 0.005*"impact"
+2024-10-14 08:58:35,312 - topic diff=0.831038, rho=1.000000
+2024-10-14 08:58:35,312 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:58:35.312564', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:36,228 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:58:36,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:36,229 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:58:36,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:36,229 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:58:36,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:36,229 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:58:36,229 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:36,230 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:58:36,230 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:36,230 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:58:36,230 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:47,545 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:58:47,547 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions)
+2024-10-14 08:58:47,547 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-10-14T08:58:47.547418', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:47,548 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:58:47,548 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:58:47,548 - using serial LDA version on this node
+2024-10-14 08:58:47,549 - 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
+2024-10-14 08:58:47,549 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:58:47,552 - -8.047 per-word bound, 264.5 perplexity estimate based on a held-out corpus of 1 documents with 2626 words
+2024-10-14 08:58:47,553 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:58:47,554 - topic #0 (0.333): 0.024*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"leaders" + 0.006*"Walsall" + 0.005*"Senior" + 0.005*"information" + 0.005*"oversight" + 0.005*"4" + 0.004*"positive"
+2024-10-14 08:58:47,554 - topic #1 (0.333): 0.016*"’" + 0.006*"leaders" + 0.005*"4" + 0.005*"needs" + 0.004*"Walsall" + 0.004*"well" + 0.004*"oversight" + 0.003*"information" + 0.003*"Senior" + 0.003*"plans"
+2024-10-14 08:58:47,554 - topic #2 (0.333): 0.022*"’" + 0.008*"leaders" + 0.006*"needs" + 0.005*"Walsall" + 0.005*"well" + 0.005*"good" + 0.004*"information" + 0.004*"supported" + 0.004*"2021" + 0.004*"oversight"
+2024-10-14 08:58:47,554 - topic diff=0.820071, rho=1.000000
+2024-10-14 08:58:47,554 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1162, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:58:47.554880', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:58:48,573 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:58:48,574 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:48,574 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:58:48,574 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:48,574 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:58:48,574 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:48,574 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:58:48,574 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:48,575 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:58:48,575 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:58:48,575 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:58:48,575 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:01,904 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:59:01,906 - built Dictionary<1158 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2700 corpus positions)
+2024-10-14 08:59:01,906 - Dictionary lifecycle event {'msg': 'built Dictionary<1158 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2700 corpus positions)', 'datetime': '2024-10-14T08:59:01.906737', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:01,907 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:59:01,908 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:59:01,908 - using serial LDA version on this node
+2024-10-14 08:59:01,908 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:59:01,908 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:59:01,912 - -8.030 per-word bound, 261.4 perplexity estimate based on a held-out corpus of 1 documents with 2700 words
+2024-10-14 08:59:01,912 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:59:01,914 - topic #0 (0.333): 0.025*"’" + 0.008*"Warrington" + 0.007*"effective" + 0.007*"needs" + 0.007*"experiences" + 0.007*"well" + 0.006*"leaders" + 0.006*"plans" + 0.006*"carers" + 0.005*"10"
+2024-10-14 08:59:01,914 - topic #1 (0.333): 0.014*"’" + 0.007*"needs" + 0.006*"experiences" + 0.006*"Warrington" + 0.005*"June" + 0.005*"well" + 0.005*"effective" + 0.005*"2024" + 0.005*"leaders" + 0.004*"supported"
+2024-10-14 08:59:01,914 - topic #2 (0.333): 0.014*"’" + 0.007*"needs" + 0.006*"Warrington" + 0.006*"experiences" + 0.006*"14" + 0.006*"leaders" + 0.005*"practice" + 0.005*"effective" + 0.005*"protection" + 0.004*"supported"
+2024-10-14 08:59:01,914 - topic diff=0.817386, rho=1.000000
+2024-10-14 08:59:01,914 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1158, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:59:01.914569', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:02,868 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:59:02,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:02,869 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:59:02,869 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:02,870 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:59:02,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:02,870 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:59:02,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:02,870 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:59:02,870 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:02,871 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:59:02,871 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:12,240 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:59:12,242 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)
+2024-10-14 08:59:12,242 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-10-14T08:59:12.242455', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:12,243 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:59:12,243 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:59:12,243 - using serial LDA version on this node
+2024-10-14 08:59:12,244 - 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
+2024-10-14 08:59:12,244 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:59:12,247 - -7.998 per-word bound, 255.7 perplexity estimate based on a held-out corpus of 1 documents with 2113 words
+2024-10-14 08:59:12,247 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:59:12,248 - topic #0 (0.333): 0.013*"’" + 0.007*"well" + 0.007*"Warwickshire" + 0.006*"plans" + 0.005*"needs" + 0.005*"practice" + 0.005*"December" + 0.004*"clear" + 0.004*"effective" + 0.004*"3"
+2024-10-14 08:59:12,248 - topic #1 (0.333): 0.011*"’" + 0.007*"needs" + 0.007*"plans" + 0.007*"well" + 0.006*"Warwickshire" + 0.005*"practice" + 0.005*"good" + 0.005*"22" + 0.005*"carers" + 0.005*"progress"
+2024-10-14 08:59:12,249 - topic #2 (0.333): 0.010*"’" + 0.007*"needs" + 0.005*"well" + 0.005*"carers" + 0.005*"plans" + 0.005*"3" + 0.004*"Warwickshire" + 0.004*"good" + 0.004*"Senior" + 0.004*"practice"
+2024-10-14 08:59:12,249 - topic diff=0.758290, rho=1.000000
+2024-10-14 08:59:12,249 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1040, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:59:12.249306', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:13,119 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:59:13,119 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:13,119 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:59:13,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:13,120 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:59:13,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:13,120 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:59:13,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:13,120 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:59:13,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:13,120 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:59:13,120 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:22,178 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:59:22,180 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)
+2024-10-14 08:59:22,180 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-10-14T08:59:22.180525', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:22,181 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:59:22,181 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:59:22,181 - using serial LDA version on this node
+2024-10-14 08:59:22,182 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:59:22,182 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:59:22,185 - -8.109 per-word bound, 276.1 perplexity estimate based on a held-out corpus of 1 documents with 2146 words
+2024-10-14 08:59:22,185 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:59:22,187 - topic #0 (0.333): 0.013*"’" + 0.006*"West" + 0.006*"Berkshire" + 0.004*"well" + 0.004*"plans" + 0.004*"early" + 0.004*"need" + 0.004*"needs" + 0.003*"progress" + 0.003*"quality"
+2024-10-14 08:59:22,187 - topic #1 (0.333): 0.012*"’" + 0.007*"well" + 0.007*"West" + 0.005*"Berkshire" + 0.004*"plans" + 0.004*"need" + 0.004*"practice" + 0.004*"needs" + 0.004*"working" + 0.004*"agency"
+2024-10-14 08:59:22,187 - topic #2 (0.333): 0.018*"’" + 0.007*"Berkshire" + 0.006*"West" + 0.006*"well" + 0.004*"14" + 0.004*"needs" + 0.004*"need" + 0.004*"18" + 0.004*"2022" + 0.004*"working"
+2024-10-14 08:59:22,187 - topic diff=0.716684, rho=1.000000
+2024-10-14 08:59:22,187 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:59:22.187826', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:23,057 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:59:23,057 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:23,057 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:59:23,057 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:23,058 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:59:23,058 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:23,058 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:59:23,058 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:23,058 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:59:23,058 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:23,058 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:59:23,058 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:32,876 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:59:32,878 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)
+2024-10-14 08:59:32,878 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-10-14T08:59:32.878705', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:32,879 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:59:32,880 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:59:32,880 - using serial LDA version on this node
+2024-10-14 08:59:32,880 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:59:32,880 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:59:32,884 - -8.045 per-word bound, 264.1 perplexity estimate based on a held-out corpus of 1 documents with 2224 words
+2024-10-14 08:59:32,884 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:59:32,885 - topic #0 (0.333): 0.019*"’" + 0.011*"Northamptonshire" + 0.007*"West" + 0.007*"quality" + 0.006*"needs" + 0.006*"well" + 0.005*"practice" + 0.005*"experiences" + 0.005*"plans" + 0.004*"3"
+2024-10-14 08:59:32,885 - topic #1 (0.333): 0.018*"’" + 0.007*"Northamptonshire" + 0.007*"well" + 0.006*"West" + 0.006*"quality" + 0.005*"impact" + 0.005*"practice" + 0.005*"needs" + 0.005*"14" + 0.004*"NCT"
+2024-10-14 08:59:32,886 - topic #2 (0.333): 0.014*"’" + 0.007*"quality" + 0.006*"West" + 0.006*"well" + 0.005*"practice" + 0.005*"Northamptonshire" + 0.005*"NCT" + 0.005*"3" + 0.004*"plans" + 0.004*"need"
+2024-10-14 08:59:32,886 - topic diff=0.758614, rho=1.000000
+2024-10-14 08:59:32,886 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1087, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:59:32.886215', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:33,743 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:59:33,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:33,743 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:59:33,743 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:33,744 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:59:33,744 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:33,744 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:59:33,744 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:33,744 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:59:33,744 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:33,744 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:59:33,744 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:45,577 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:59:45,580 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
+2024-10-14 08:59:45,580 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-10-14T08:59:45.580378', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:45,581 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:59:45,581 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:59:45,581 - using serial LDA version on this node
+2024-10-14 08:59:45,582 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:59:45,582 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:59:45,586 - -8.121 per-word bound, 278.4 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
+2024-10-14 08:59:45,586 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:59:45,587 - topic #0 (0.333): 0.011*"’" + 0.005*"needs" + 0.005*"well" + 0.004*"plans" + 0.004*"supported" + 0.004*"practice" + 0.004*"Sussex" + 0.004*"education" + 0.004*"24" + 0.003*"13"
+2024-10-14 08:59:45,587 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"plans" + 0.006*"West" + 0.006*"Sussex" + 0.006*"needs" + 0.005*"quality" + 0.005*"number" + 0.005*"13" + 0.005*"health"
+2024-10-14 08:59:45,587 - topic #2 (0.333): 0.013*"’" + 0.006*"plans" + 0.006*"needs" + 0.005*"well" + 0.005*"13" + 0.004*"Sussex" + 0.004*"West" + 0.004*"number" + 0.004*"clear" + 0.004*"planning"
+2024-10-14 08:59:45,588 - topic diff=0.813420, rho=1.000000
+2024-10-14 08:59:45,588 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1233, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:59:45.588187', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:46,456 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:59:46,456 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:46,457 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:59:46,457 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:46,457 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:59:46,457 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:46,457 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:59:46,457 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:46,457 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:59:46,458 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:46,458 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:59:46,458 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:58,648 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 08:59:58,653 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)
+2024-10-14 08:59:58,653 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)", 'datetime': '2024-10-14T08:59:58.653496', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:58,655 - using symmetric alpha at 0.3333333333333333
+2024-10-14 08:59:58,655 - using symmetric eta at 0.3333333333333333
+2024-10-14 08:59:58,655 - using serial LDA version on this node
+2024-10-14 08:59:58,656 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 08:59:58,656 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 08:59:58,662 - -7.970 per-word bound, 250.7 perplexity estimate based on a held-out corpus of 1 documents with 2451 words
+2024-10-14 08:59:58,662 - PROGRESS: pass 0, at document #1/1
+2024-10-14 08:59:58,664 - topic #0 (0.333): 0.013*"’" + 0.008*"plans" + 0.007*"needs" + 0.006*"Furness" + 0.006*"Westmorland" + 0.006*"appropriate" + 0.006*"need" + 0.005*"protection" + 0.005*"well" + 0.004*"3"
+2024-10-14 08:59:58,664 - topic #1 (0.333): 0.011*"’" + 0.008*"plans" + 0.007*"Westmorland" + 0.007*"needs" + 0.006*"Furness" + 0.006*"need" + 0.006*"appropriate" + 0.006*"protection" + 0.006*"quality" + 0.005*"progress"
+2024-10-14 08:59:58,666 - topic #2 (0.333): 0.014*"’" + 0.007*"plans" + 0.006*"Furness" + 0.005*"appropriate" + 0.005*"Westmorland" + 0.005*"need" + 0.005*"needs" + 0.005*"quality" + 0.005*"April" + 0.005*"well"
+2024-10-14 08:59:58,666 - topic diff=0.800839, rho=1.000000
+2024-10-14 08:59:58,666 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T08:59:58.666557', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 08:59:59,824 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 08:59:59,824 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:59,824 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 08:59:59,824 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:59,825 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 08:59:59,825 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:59,825 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame.
+2024-10-14 08:59:59,825 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:59,825 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 08:59:59,825 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 08:59:59,825 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 08:59:59,825 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:10,303 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 09:00:10,307 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)
+2024-10-14 09:00:10,307 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-10-14T09:00:10.307717', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:10,309 - using symmetric alpha at 0.3333333333333333
+2024-10-14 09:00:10,309 - using symmetric eta at 0.3333333333333333
+2024-10-14 09:00:10,310 - using serial LDA version on this node
+2024-10-14 09:00:10,310 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 09:00:10,310 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 09:00:10,316 - -7.962 per-word bound, 249.3 perplexity estimate based on a held-out corpus of 1 documents with 2416 words
+2024-10-14 09:00:10,317 - PROGRESS: pass 0, at document #1/1
+2024-10-14 09:00:10,319 - topic #0 (0.333): 0.014*"’" + 0.008*"May" + 0.007*"practice" + 0.007*"plans" + 0.006*"Wigan" + 0.006*"needs" + 0.006*"leaders" + 0.005*"appropriate" + 0.005*"quality" + 0.004*"9"
+2024-10-14 09:00:10,319 - topic #1 (0.333): 0.014*"’" + 0.008*"May" + 0.006*"plans" + 0.006*"quality" + 0.006*"appropriate" + 0.006*"practice" + 0.006*"Wigan" + 0.005*"needs" + 0.005*"focused" + 0.005*"9"
+2024-10-14 09:00:10,319 - topic #2 (0.333): 0.008*"’" + 0.007*"plans" + 0.007*"needs" + 0.006*"practice" + 0.006*"quality" + 0.005*"Wigan" + 0.005*"May" + 0.005*"timely" + 0.004*"2022" + 0.004*"appropriate"
+2024-10-14 09:00:10,319 - topic diff=0.795072, rho=1.000000
+2024-10-14 09:00:10,320 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T09:00:10.320037', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:11,462 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 09:00:11,462 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:11,463 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 09:00:11,463 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:11,463 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 09:00:11,463 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:11,463 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-10-14 09:00:11,463 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:11,463 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 09:00:11,463 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:11,463 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 09:00:11,464 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:21,565 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 09:00:21,570 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)
+2024-10-14 09:00:21,570 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-10-14T09:00:21.570354', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:21,572 - using symmetric alpha at 0.3333333333333333
+2024-10-14 09:00:21,572 - using symmetric eta at 0.3333333333333333
+2024-10-14 09:00:21,573 - using serial LDA version on this node
+2024-10-14 09:00:21,573 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 09:00:21,573 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 09:00:21,579 - -7.954 per-word bound, 248.0 perplexity estimate based on a held-out corpus of 1 documents with 2600 words
+2024-10-14 09:00:21,580 - PROGRESS: pass 0, at document #1/1
+2024-10-14 09:00:21,582 - topic #0 (0.333): 0.018*"’" + 0.010*"well" + 0.009*"needs" + 0.007*"need" + 0.007*"Wiltshire" + 0.006*"progress" + 0.006*"plans" + 0.006*"including" + 0.006*"ensure" + 0.006*"parents"
+2024-10-14 09:00:21,582 - topic #1 (0.333): 0.016*"’" + 0.014*"well" + 0.007*"need" + 0.006*"risk" + 0.006*"progress" + 0.006*"parents" + 0.006*"needs" + 0.006*"supported" + 0.006*"Wiltshire" + 0.006*"including"
+2024-10-14 09:00:21,582 - topic #2 (0.333): 0.007*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"risk" + 0.004*"supported" + 0.004*"including" + 0.004*"need" + 0.004*"plans" + 0.004*"leaders" + 0.003*"parents"
+2024-10-14 09:00:21,582 - topic diff=0.860314, rho=1.000000
+2024-10-14 09:00:21,583 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1090, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T09:00:21.582987', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:22,537 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 09:00:22,537 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:22,537 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 09:00:22,537 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:22,538 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 09:00:22,538 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:22,538 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame.
+2024-10-14 09:00:22,538 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:22,538 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 09:00:22,538 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:22,538 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 09:00:22,538 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:33,580 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 09:00:33,582 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
+2024-10-14 09:00:33,582 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-10-14T09:00:33.582548', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:33,583 - using symmetric alpha at 0.3333333333333333
+2024-10-14 09:00:33,583 - using symmetric eta at 0.3333333333333333
+2024-10-14 09:00:33,584 - using serial LDA version on this node
+2024-10-14 09:00:33,584 - 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
+2024-10-14 09:00:33,584 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 09:00:33,587 - -7.906 per-word bound, 239.9 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
+2024-10-14 09:00:33,587 - PROGRESS: pass 0, at document #1/1
+2024-10-14 09:00:33,589 - topic #0 (0.333): 0.007*"’" + 0.007*"needs" + 0.005*"Wirral" + 0.005*"practice" + 0.004*"well" + 0.004*"ensure" + 0.004*"small" + 0.004*"appropriate" + 0.004*"effective" + 0.004*"plans"
+2024-10-14 09:00:33,589 - topic #1 (0.333): 0.013*"’" + 0.010*"needs" + 0.009*"plans" + 0.009*"ensure" + 0.008*"Wirral" + 0.007*"practice" + 0.006*"well" + 0.006*"good" + 0.005*"response" + 0.005*"2023"
+2024-10-14 09:00:33,589 - topic #2 (0.333): 0.010*"’" + 0.010*"needs" + 0.007*"Wirral" + 0.006*"ensure" + 0.006*"practice" + 0.005*"number" + 0.005*"well" + 0.005*"PAs" + 0.004*"response" + 0.004*"18"
+2024-10-14 09:00:33,589 - topic diff=0.829671, rho=1.000000
+2024-10-14 09:00:33,589 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T09:00:33.589682', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:34,511 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 09:00:34,511 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:34,511 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 09:00:34,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:34,512 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 09:00:34,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:34,512 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame.
+2024-10-14 09:00:34,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:34,512 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 09:00:34,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:34,512 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 09:00:34,512 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:45,069 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 09:00:45,071 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)
+2024-10-14 09:00:45,071 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-10-14T09:00:45.071538', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:45,072 - using symmetric alpha at 0.3333333333333333
+2024-10-14 09:00:45,072 - using symmetric eta at 0.3333333333333333
+2024-10-14 09:00:45,072 - using serial LDA version on this node
+2024-10-14 09:00:45,073 - 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
+2024-10-14 09:00:45,073 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 09:00:45,076 - -8.058 per-word bound, 266.5 perplexity estimate based on a held-out corpus of 1 documents with 2214 words
+2024-10-14 09:00:45,076 - PROGRESS: pass 0, at document #1/1
+2024-10-14 09:00:45,078 - topic #0 (0.333): 0.014*"’" + 0.008*"plans" + 0.006*"well" + 0.006*"impact" + 0.005*"17" + 0.005*"quality" + 0.005*"progress" + 0.005*"effective" + 0.005*"needs" + 0.005*"experiences"
+2024-10-14 09:00:45,078 - topic #1 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"effective" + 0.006*"plans" + 0.004*"provided" + 0.004*"progress" + 0.004*"oversight" + 0.004*"17" + 0.004*"Borough" + 0.004*"6"
+2024-10-14 09:00:45,078 - topic #2 (0.333): 0.012*"’" + 0.007*"effective" + 0.007*"provided" + 0.006*"progress" + 0.006*"plans" + 0.006*"needs" + 0.006*"well" + 0.005*"experiences" + 0.005*"good" + 0.005*"Wokingham"
+2024-10-14 09:00:45,078 - topic diff=0.757473, rho=1.000000
+2024-10-14 09:00:45,078 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1096, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T09:00:45.078660', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:45,916 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 09:00:45,916 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:45,916 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 09:00:45,916 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:45,917 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 09:00:45,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:45,917 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
+2024-10-14 09:00:45,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:45,917 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 09:00:45,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:45,917 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 09:00:45,917 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:55,644 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 09:00:55,646 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
+2024-10-14 09:00:55,647 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-10-14T09:00:55.646973', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:55,648 - using symmetric alpha at 0.3333333333333333
+2024-10-14 09:00:55,648 - using symmetric eta at 0.3333333333333333
+2024-10-14 09:00:55,648 - using serial LDA version on this node
+2024-10-14 09:00:55,648 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-10-14 09:00:55,648 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 09:00:55,652 - -8.057 per-word bound, 266.3 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
+2024-10-14 09:00:55,652 - PROGRESS: pass 0, at document #1/1
+2024-10-14 09:00:55,653 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.005*"effective" + 0.005*"Wolverhampton" + 0.005*"risks" + 0.004*"receive" + 0.004*"leaders" + 0.004*"quality" + 0.004*"foster" + 0.004*"practice"
+2024-10-14 09:00:55,653 - topic #1 (0.333): 0.014*"’" + 0.008*"needs" + 0.006*"Wolverhampton" + 0.006*"effective" + 0.006*"supported" + 0.005*"risks" + 0.005*"plans" + 0.004*"strong" + 0.004*"practice" + 0.004*"leaders"
+2024-10-14 09:00:55,653 - topic #2 (0.333): 0.013*"’" + 0.008*"needs" + 0.006*"effective" + 0.005*"plans" + 0.005*"quality" + 0.005*"receive" + 0.005*"Wolverhampton" + 0.005*"risk" + 0.005*"education" + 0.005*"leaders"
+2024-10-14 09:00:55,654 - topic diff=0.737994, rho=1.000000
+2024-10-14 09:00:55,654 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1095, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T09:00:55.654185', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:00:56,558 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 09:00:56,558 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:56,558 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 09:00:56,558 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:56,558 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 09:00:56,558 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:56,559 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
+2024-10-14 09:00:56,559 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:56,559 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 09:00:56,559 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:00:56,559 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 09:00:56,559 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:01:07,804 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-10-14 09:01:07,806 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)
+2024-10-14 09:01:07,806 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-10-14T09:01:07.806781', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:01:07,807 - using symmetric alpha at 0.3333333333333333
+2024-10-14 09:01:07,807 - using symmetric eta at 0.3333333333333333
+2024-10-14 09:01:07,808 - using serial LDA version on this node
+2024-10-14 09:01:07,808 - 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
+2024-10-14 09:01:07,808 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-10-14 09:01:07,811 - -7.940 per-word bound, 245.6 perplexity estimate based on a held-out corpus of 1 documents with 2343 words
+2024-10-14 09:01:07,812 - PROGRESS: pass 0, at document #1/1
+2024-10-14 09:01:07,813 - topic #0 (0.333): 0.024*"’" + 0.010*"well" + 0.008*"Worcestershire" + 0.008*"needs" + 0.007*"plans" + 0.007*"ensure" + 0.006*"leaders" + 0.006*"progress" + 0.005*"living" + 0.005*"appropriate"
+2024-10-14 09:01:07,813 - topic #1 (0.333): 0.018*"’" + 0.009*"needs" + 0.008*"plans" + 0.008*"leaders" + 0.007*"progress" + 0.007*"well" + 0.006*"appropriate" + 0.005*"ensure" + 0.005*"Worcestershire" + 0.005*"However"
+2024-10-14 09:01:07,813 - topic #2 (0.333): 0.012*"’" + 0.008*"plans" + 0.007*"Worcestershire" + 0.007*"well" + 0.006*"progress" + 0.005*"leaders" + 0.005*"Senior" + 0.005*"needs" + 0.005*"15" + 0.005*"PAs"
+2024-10-14 09:01:07,813 - topic diff=0.804421, rho=1.000000
+2024-10-14 09:01:07,813 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1041, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-10-14T09:01:07.813839', 'gensim': '4.3.3', 'python': '3.10.13 (main, Jul 11 2024, 16:23:02) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1025-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-10-14 09:01:08,814 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-10-14 09:01:08,815 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:01:08,815 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-10-14 09:01:08,815 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:01:08,815 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-10-14 09:01:08,816 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:01:08,816 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
+2024-10-14 09:01:08,816 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:01:08,816 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
+2024-10-14 09:01:08,816 - Index(['judgement', 'grade'], dtype='object')
+2024-10-14 09:01:08,816 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-10-14 09:01:08,816 - Index(['judgement', 'grade'], dtype='object')