diff --git a/index.html b/index.html
index def80be..32eada1 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>.</p>
         <p>Disclaimer: This summary is built from scraped data direct from https://reports.ofsted.gov.uk/ and the 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 LA's*.<br/> <a href="mailto:datatoinsight.enquiries@gmail.com?subject=Ofsted-Scrape-Tool">Feedback</a> on specific problems|inaccuracies|suggestions welcomed.<br/>**LA reports with 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]</p>
-        <p><b>Last updated: 09 05 2024 08:28</b></p>
+        <p><b>Last updated: 13 05 2024 12:45</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 fb3357e..76f66ce 100644
Binary files a/ofsted_childrens_services_overview.xlsx and b/ofsted_childrens_services_overview.xlsx differ
diff --git a/output.log b/output.log
index fabf8de..d3ac45b 100644
--- a/output.log
+++ b/output.log
@@ -244760,3 +244760,4085 @@ WARNING: Using fallback font 'LiberationSans' for 'TimesNewRomanPSMT'
 2024-05-09 08:28:21,710 - Index(['judgement', 'grade'], dtype='object')
 2024-05-09 08:28:21,710 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
 2024-05-09 08:28:21,710 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:09,724 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:09,733 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)
+2024-05-13 12:38:09,738 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-05-13T12:38:09.734325', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:09,739 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:09,739 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:09,739 - using serial LDA version on this node
+2024-05-13 12:38:09,740 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:09,740 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:09,747 - -8.112 per-word bound, 276.7 perplexity estimate based on a held-out corpus of 1 documents with 2696 words
+2024-05-13 12:38:09,747 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:09,750 - topic #0 (0.333): 0.024*"’" + 0.008*"needs" + 0.007*"leaders" + 0.006*"within" + 0.006*"practice" + 0.005*"Barnsley" + 0.005*"senior" + 0.005*"2023" + 0.004*"plans" + 0.004*"family"
+2024-05-13 12:38:09,750 - topic #1 (0.333): 0.016*"’" + 0.008*"leaders" + 0.008*"needs" + 0.007*"within" + 0.006*"Barnsley" + 0.006*"practice" + 0.005*"response" + 0.005*"plans" + 0.004*"experiences" + 0.004*"quality"
+2024-05-13 12:38:09,750 - topic #2 (0.333): 0.017*"’" + 0.008*"needs" + 0.006*"leaders" + 0.006*"within" + 0.005*"Barnsley" + 0.005*"practice" + 0.005*"11" + 0.005*"15" + 0.004*"progress" + 0.004*"plans"
+2024-05-13 12:38:09,750 - topic diff=0.795439, rho=1.000000
+2024-05-13 12:38:09,751 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1216, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:09.751093', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:09,754 - Error importing jpype dependencies. Fallback to subprocess.
+2024-05-13 12:38:09,754 - No module named 'jpype'
+2024-05-13 12:38:13,159 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:13,160 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:13,160 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:13,160 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:13,160 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:13,160 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:13,161 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:13,161 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:13,161 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:13,161 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:13,161 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:13,162 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:15,182 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:15,186 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)
+2024-05-13 12:38:15,186 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-05-13T12:38:15.186545', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:15,188 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:15,188 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:15,188 - using serial LDA version on this node
+2024-05-13 12:38:15,189 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:15,189 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:15,196 - -8.019 per-word bound, 259.5 perplexity estimate based on a held-out corpus of 1 documents with 2085 words
+2024-05-13 12:38:15,196 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:15,198 - topic #0 (0.333): 0.018*"’" + 0.009*"well" + 0.005*"practice" + 0.005*"4" + 0.005*"plans" + 0.005*"impact" + 0.004*"good" + 0.004*"East" + 0.004*"‘" + 0.004*"28"
+2024-05-13 12:38:15,198 - topic #1 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"needs" + 0.005*"leaders" + 0.005*"North" + 0.005*"practice" + 0.005*"Somerset" + 0.005*"plans" + 0.004*"effective" + 0.004*"Bath"
+2024-05-13 12:38:15,199 - topic #2 (0.333): 0.020*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"practice" + 0.006*"plans" + 0.006*"leaders" + 0.005*"effective" + 0.005*"2022" + 0.005*"clear" + 0.005*"receive"
+2024-05-13 12:38:15,199 - topic diff=0.747880, rho=1.000000
+2024-05-13 12:38:15,199 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:15.199381', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:16,411 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:16,411 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:16,412 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:16,412 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:16,412 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:16,412 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:16,413 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:16,413 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:16,413 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:16,413 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:16,413 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:16,414 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:18,593 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:18,595 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)
+2024-05-13 12:38:18,596 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-05-13T12:38:18.596091', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:18,597 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:18,597 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:18,597 - using serial LDA version on this node
+2024-05-13 12:38:18,598 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:18,598 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:18,602 - -8.113 per-word bound, 276.9 perplexity estimate based on a held-out corpus of 1 documents with 2585 words
+2024-05-13 12:38:18,602 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:18,603 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"ensure" + 0.005*"plans" + 0.005*"relationships" + 0.005*"progress" + 0.004*"26" + 0.004*"Bedford" + 0.004*"family"
+2024-05-13 12:38:18,603 - topic #1 (0.333): 0.020*"’" + 0.007*"ensure" + 0.006*"needs" + 0.006*"plans" + 0.006*"Bedford" + 0.005*"good" + 0.005*"well" + 0.005*"Borough" + 0.004*"2021" + 0.004*"progress"
+2024-05-13 12:38:18,604 - topic #2 (0.333): 0.019*"’" + 0.006*"supported" + 0.006*"needs" + 0.006*"well" + 0.005*"ensure" + 0.005*"Bedford" + 0.005*"good" + 0.005*"progress" + 0.005*"education" + 0.004*"Borough"
+2024-05-13 12:38:18,604 - topic diff=0.784765, rho=1.000000
+2024-05-13 12:38:18,604 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1202, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:18.604318', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:19,661 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:19,661 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:19,661 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:19,662 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:19,662 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:19,662 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:19,662 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:19,662 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:19,662 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:19,662 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:19,663 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:19,663 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:21,259 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:21,262 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)
+2024-05-13 12:38:21,262 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-05-13T12:38:21.262461', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:21,263 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:21,263 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:21,264 - using serial LDA version on this node
+2024-05-13 12:38:21,264 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:21,264 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:21,268 - -7.966 per-word bound, 250.0 perplexity estimate based on a held-out corpus of 1 documents with 2378 words
+2024-05-13 12:38:21,268 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:21,270 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"plans" + 0.006*"effective" + 0.006*"timely" + 0.005*"Birmingham" + 0.004*"trust" + 0.004*"progress" + 0.004*"appropriate"
+2024-05-13 12:38:21,270 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"effective" + 0.006*"Birmingham" + 0.005*"3" + 0.005*"plans" + 0.005*"appropriate" + 0.005*"risk" + 0.005*"progress" + 0.005*"response"
+2024-05-13 12:38:21,270 - topic #2 (0.333): 0.015*"’" + 0.010*"needs" + 0.007*"well" + 0.007*"trust" + 0.006*"progress" + 0.006*"effective" + 0.005*"Birmingham" + 0.005*"3" + 0.005*"plans" + 0.005*"practice"
+2024-05-13 12:38:21,270 - topic diff=0.786390, rho=1.000000
+2024-05-13 12:38:21,271 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1065, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:21.271019', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:22,289 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:22,289 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:22,290 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:22,290 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:22,290 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:22,290 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:22,290 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:22,290 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:22,291 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:22,291 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:22,291 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:22,291 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:23,799 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:23,801 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)
+2024-05-13 12:38:23,801 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-05-13T12:38:23.801610', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:23,802 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:23,802 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:23,803 - using serial LDA version on this node
+2024-05-13 12:38:23,803 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:23,803 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:23,807 - -7.966 per-word bound, 250.0 perplexity estimate based on a held-out corpus of 1 documents with 2353 words
+2024-05-13 12:38:23,807 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:23,808 - topic #0 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"Darwen" + 0.007*"practice" + 0.006*"quality" + 0.005*"well" + 0.005*"impact" + 0.005*"Blackburn" + 0.005*"need" + 0.005*"4"
+2024-05-13 12:38:23,808 - topic #1 (0.333): 0.011*"’" + 0.008*"Blackburn" + 0.007*"needs" + 0.007*"quality" + 0.007*"practice" + 0.007*"well" + 0.006*"impact" + 0.006*"planning" + 0.005*"Darwen" + 0.005*"means"
+2024-05-13 12:38:23,808 - topic #2 (0.333): 0.012*"’" + 0.008*"practice" + 0.007*"quality" + 0.007*"needs" + 0.007*"Darwen" + 0.006*"Blackburn" + 0.006*"impact" + 0.005*"well" + 0.005*"result" + 0.005*"4"
+2024-05-13 12:38:23,808 - topic diff=0.814794, rho=1.000000
+2024-05-13 12:38:23,809 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1055, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:23.809109', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:24,975 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:24,975 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:24,976 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:24,976 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:24,976 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:24,976 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:24,977 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:24,977 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:24,977 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:24,977 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:24,977 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:24,977 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:26,889 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:26,892 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)
+2024-05-13 12:38:26,892 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-05-13T12:38:26.892450', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:26,893 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:26,893 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:26,893 - using serial LDA version on this node
+2024-05-13 12:38:26,894 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:26,894 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:26,897 - -7.924 per-word bound, 242.8 perplexity estimate based on a held-out corpus of 1 documents with 2392 words
+2024-05-13 12:38:26,897 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:26,899 - topic #0 (0.333): 0.017*"’" + 0.010*"needs" + 0.010*"well" + 0.007*"Blackpool" + 0.006*"plans" + 0.005*"effective" + 0.005*"16" + 0.005*"carers" + 0.005*"supported" + 0.005*"good"
+2024-05-13 12:38:26,899 - topic #1 (0.333): 0.018*"’" + 0.011*"well" + 0.009*"needs" + 0.008*"Blackpool" + 0.005*"effective" + 0.005*"quality" + 0.005*"progress" + 0.005*"practice" + 0.005*"16" + 0.005*"team"
+2024-05-13 12:38:26,899 - topic #2 (0.333): 0.015*"’" + 0.011*"needs" + 0.007*"Blackpool" + 0.006*"supported" + 0.006*"well" + 0.006*"effective" + 0.006*"practice" + 0.005*"experiences" + 0.004*"plans" + 0.004*"timely"
+2024-05-13 12:38:26,899 - topic diff=0.825911, rho=1.000000
+2024-05-13 12:38:26,899 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1037, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:26.899933', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:27,928 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:27,928 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:27,929 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:27,929 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:27,929 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:27,929 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:27,929 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:27,929 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:27,929 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:27,929 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:27,930 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:27,930 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:29,466 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:29,469 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)
+2024-05-13 12:38:29,469 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-05-13T12:38:29.469304', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:29,470 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:29,470 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:29,470 - using serial LDA version on this node
+2024-05-13 12:38:29,471 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:29,471 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:29,474 - -7.913 per-word bound, 240.9 perplexity estimate based on a held-out corpus of 1 documents with 2055 words
+2024-05-13 12:38:29,474 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:29,476 - topic #0 (0.333): 0.013*"’" + 0.009*"plans" + 0.008*"needs" + 0.006*"well" + 0.006*"Bolton" + 0.006*"need" + 0.006*"supported" + 0.004*"response" + 0.004*"effective" + 0.004*"strong"
+2024-05-13 12:38:29,476 - topic #1 (0.333): 0.019*"’" + 0.010*"needs" + 0.008*"well" + 0.008*"Bolton" + 0.007*"plans" + 0.006*"11" + 0.005*"supported" + 0.005*"planning" + 0.005*"response" + 0.005*"appropriate"
+2024-05-13 12:38:29,476 - topic #2 (0.333): 0.023*"’" + 0.010*"needs" + 0.010*"Bolton" + 0.009*"well" + 0.006*"plans" + 0.006*"planning" + 0.005*"supported" + 0.005*"strong" + 0.005*"September" + 0.005*"timely"
+2024-05-13 12:38:29,476 - topic diff=0.778573, rho=1.000000
+2024-05-13 12:38:29,476 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:29.476734', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:30,593 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:30,593 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:30,593 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:30,593 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:30,593 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:30,593 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:30,594 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:30,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:30,594 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:30,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:30,594 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:30,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:32,214 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:32,217 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)
+2024-05-13 12:38:32,217 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-05-13T12:38:32.217218', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:32,218 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:32,218 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:32,218 - using serial LDA version on this node
+2024-05-13 12:38:32,218 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:32,219 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:32,222 - -8.033 per-word bound, 261.9 perplexity estimate based on a held-out corpus of 1 documents with 2004 words
+2024-05-13 12:38:32,222 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:32,223 - topic #0 (0.333): 0.019*"’" + 0.006*"quality" + 0.006*"progress" + 0.005*"Christchurch" + 0.005*"Bournemouth" + 0.005*"practice" + 0.005*"time" + 0.004*"needs" + 0.004*"impact" + 0.004*"well"
+2024-05-13 12:38:32,224 - topic #1 (0.333): 0.018*"’" + 0.006*"practice" + 0.006*"quality" + 0.005*"6" + 0.005*"risk" + 0.005*"17" + 0.005*"impact" + 0.005*"Poole" + 0.005*"However" + 0.004*"number"
+2024-05-13 12:38:32,224 - topic #2 (0.333): 0.016*"’" + 0.006*"quality" + 0.006*"practice" + 0.005*"progress" + 0.005*"well" + 0.004*"Poole" + 0.004*"17" + 0.004*"risk" + 0.004*"time" + 0.004*"Bournemouth"
+2024-05-13 12:38:32,224 - topic diff=0.751827, rho=1.000000
+2024-05-13 12:38:32,224 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1035, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:32.224504', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:34,561 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:34,561 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:34,561 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:34,561 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:34,561 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:34,561 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:34,562 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:34,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:34,562 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:34,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:34,562 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:34,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:36,094 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:36,096 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)
+2024-05-13 12:38:36,096 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-05-13T12:38:36.096780', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:36,097 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:36,097 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:36,098 - using serial LDA version on this node
+2024-05-13 12:38:36,098 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:36,098 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:36,101 - -7.854 per-word bound, 231.3 perplexity estimate based on a held-out corpus of 1 documents with 1846 words
+2024-05-13 12:38:36,101 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:36,103 - topic #0 (0.333): 0.018*"’" + 0.007*"needs" + 0.007*"risk" + 0.006*"provided" + 0.006*"good" + 0.006*"Bracknell" + 0.006*"effective" + 0.006*"need" + 0.006*"quality" + 0.006*"impact"
+2024-05-13 12:38:36,103 - topic #1 (0.333): 0.015*"’" + 0.008*"Forest" + 0.008*"Bracknell" + 0.006*"risk" + 0.006*"quality" + 0.006*"leaders" + 0.006*"needs" + 0.005*"plans" + 0.005*"effective" + 0.005*"good"
+2024-05-13 12:38:36,103 - topic #2 (0.333): 0.016*"’" + 0.007*"Forest" + 0.007*"needs" + 0.006*"good" + 0.006*"quality" + 0.006*"progress" + 0.006*"well" + 0.006*"risk" + 0.006*"effective" + 0.006*"need"
+2024-05-13 12:38:36,103 - topic diff=0.760511, rho=1.000000
+2024-05-13 12:38:36,103 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=900, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:36.103911', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:37,255 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:37,255 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:37,255 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:37,256 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:37,256 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:37,256 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:37,256 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:37,256 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:37,256 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:37,257 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:37,257 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:37,257 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:38,643 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:38,646 - built Dictionary<902 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 1873 corpus positions)
+2024-05-13 12:38:38,646 - Dictionary lifecycle event {'msg': 'built Dictionary<902 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 1873 corpus positions)', 'datetime': '2024-05-13T12:38:38.646664', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:38,648 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:38,648 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:38,648 - using serial LDA version on this node
+2024-05-13 12:38:38,649 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:38,649 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:38,655 - -7.847 per-word bound, 230.2 perplexity estimate based on a held-out corpus of 1 documents with 1873 words
+2024-05-13 12:38:38,655 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:38,657 - topic #0 (0.333): 0.009*"’" + 0.009*"good" + 0.007*"needs" + 0.006*"well" + 0.005*"recording" + 0.005*"leaders" + 0.005*"ensure" + 0.005*"Hove" + 0.004*"plans" + 0.004*"improve"
+2024-05-13 12:38:38,657 - topic #1 (0.333): 0.016*"’" + 0.010*"needs" + 0.009*"good" + 0.007*"recording" + 0.005*"plans" + 0.005*"well" + 0.005*"leaders" + 0.005*"However" + 0.005*"need" + 0.005*"Brighton"
+2024-05-13 12:38:38,658 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"good" + 0.006*"leaders" + 0.005*"well" + 0.005*"recording" + 0.005*"need" + 0.005*"supported" + 0.005*"Senior" + 0.005*"quality"
+2024-05-13 12:38:38,658 - topic diff=0.756131, rho=1.000000
+2024-05-13 12:38:38,658 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=902, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:38.658313', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:39,637 - Inspection date 2018-07-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:39,638 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:39,638 - Inspection date 2018-07-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:39,638 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:39,638 - Inspection date 2018-07-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:39,638 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:39,639 - Inspection date 2018-07-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:39,639 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:39,639 - Inspection date 2018-07-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:39,639 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:39,639 - Inspection date 2018-07-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:39,639 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:40,975 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:40,977 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)
+2024-05-13 12:38:40,978 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-05-13T12:38:40.977975', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:40,979 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:40,979 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:40,979 - using serial LDA version on this node
+2024-05-13 12:38:40,980 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:40,980 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:40,983 - -8.026 per-word bound, 260.7 perplexity estimate based on a held-out corpus of 1 documents with 2647 words
+2024-05-13 12:38:40,984 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:40,985 - topic #0 (0.333): 0.019*"’" + 0.010*"well" + 0.008*"good" + 0.008*"Bristol" + 0.006*"progress" + 0.006*"needs" + 0.005*"always" + 0.005*"health" + 0.005*"16" + 0.005*"need"
+2024-05-13 12:38:40,985 - topic #1 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"good" + 0.006*"Bristol" + 0.006*"needs" + 0.005*"need" + 0.005*"health" + 0.005*"leaders" + 0.004*"risk" + 0.004*"plans"
+2024-05-13 12:38:40,985 - topic #2 (0.333): 0.019*"’" + 0.010*"needs" + 0.008*"well" + 0.008*"good" + 0.008*"Bristol" + 0.005*"health" + 0.005*"leaders" + 0.005*"information" + 0.004*"plans" + 0.004*"progress"
+2024-05-13 12:38:40,986 - topic diff=0.816315, rho=1.000000
+2024-05-13 12:38:40,986 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1151, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:40.986177', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:41,931 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:41,932 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:41,932 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:41,932 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:41,932 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:41,933 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:41,933 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:41,933 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:41,933 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:41,933 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:41,933 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:41,934 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:43,880 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:43,883 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)
+2024-05-13 12:38:43,883 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-05-13T12:38:43.883360', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:43,884 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:43,884 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:43,884 - using serial LDA version on this node
+2024-05-13 12:38:43,885 - 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
+2024-05-13 12:38:43,885 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:43,890 - -8.239 per-word bound, 302.2 perplexity estimate based on a held-out corpus of 1 documents with 2404 words
+2024-05-13 12:38:43,890 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:43,891 - topic #0 (0.333): 0.010*"’" + 0.004*"plans" + 0.004*"many" + 0.004*"number" + 0.004*"Buckinghamshire" + 0.004*"17" + 0.003*"6" + 0.003*"teams" + 0.003*"progress" + 0.003*"delays"
+2024-05-13 12:38:43,891 - topic #1 (0.333): 0.015*"’" + 0.005*"number" + 0.005*"plans" + 0.004*"Buckinghamshire" + 0.004*"protection" + 0.004*"practice" + 0.004*"December" + 0.004*"17" + 0.004*"well" + 0.004*"small"
+2024-05-13 12:38:43,892 - topic #2 (0.333): 0.014*"’" + 0.005*"plans" + 0.005*"17" + 0.005*"Buckinghamshire" + 0.004*"6" + 0.004*"number" + 0.004*"2021" + 0.004*"progress" + 0.004*"protection" + 0.004*"many"
+2024-05-13 12:38:43,892 - topic diff=0.732361, rho=1.000000
+2024-05-13 12:38:43,892 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1263, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:43.892376', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:44,968 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:44,968 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:44,969 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:44,969 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:44,969 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:44,970 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:44,970 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:44,970 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:44,970 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:44,971 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:44,971 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:44,971 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:47,191 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:47,194 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)
+2024-05-13 12:38:47,194 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-05-13T12:38:47.194172', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:47,195 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:47,195 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:47,195 - using serial LDA version on this node
+2024-05-13 12:38:47,196 - 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
+2024-05-13 12:38:47,196 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:47,199 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 2427 words
+2024-05-13 12:38:47,199 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:47,201 - topic #0 (0.333): 0.012*"’" + 0.009*"protection" + 0.007*"2021" + 0.005*"needs" + 0.005*"team" + 0.005*"practice" + 0.005*"need" + 0.004*"quality" + 0.004*"drift" + 0.004*"progress"
+2024-05-13 12:38:47,201 - topic #1 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"2021" + 0.006*"team" + 0.005*"protection" + 0.005*"impact" + 0.005*"practice" + 0.005*"need" + 0.005*"risk" + 0.004*"quality"
+2024-05-13 12:38:47,201 - topic #2 (0.333): 0.010*"’" + 0.007*"needs" + 0.006*"2021" + 0.006*"Bury" + 0.006*"practice" + 0.005*"impact" + 0.005*"team" + 0.005*"risk" + 0.005*"need" + 0.005*"quality"
+2024-05-13 12:38:47,201 - topic diff=0.803517, rho=1.000000
+2024-05-13 12:38:47,201 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:47.201846', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:48,481 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:48,481 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:48,481 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:48,482 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:48,482 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:48,482 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:48,482 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:48,482 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:48,482 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:48,482 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:48,483 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:48,483 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:49,903 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:49,907 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2497 corpus positions)
+2024-05-13 12:38:49,907 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2497 corpus positions)", 'datetime': '2024-05-13T12:38:49.907403', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:49,908 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:49,909 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:49,909 - using serial LDA version on this node
+2024-05-13 12:38:49,909 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:49,909 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:49,913 - -8.136 per-word bound, 281.2 perplexity estimate based on a held-out corpus of 1 documents with 2497 words
+2024-05-13 12:38:49,913 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:49,915 - topic #0 (0.333): 0.012*"’" + 0.006*"well" + 0.006*"Calderdale" + 0.005*"effective" + 0.005*"practice" + 0.005*"good" + 0.005*"protection" + 0.004*"education" + 0.004*"‘" + 0.004*"inform"
+2024-05-13 12:38:49,915 - topic #1 (0.333): 0.016*"’" + 0.009*"well" + 0.006*"practice" + 0.005*"Calderdale" + 0.005*"‘" + 0.004*"good" + 0.004*"protection" + 0.004*"inform" + 0.004*"making" + 0.004*"risk"
+2024-05-13 12:38:49,915 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"good" + 0.005*"practice" + 0.005*"effective" + 0.005*"protection" + 0.005*"carers" + 0.005*"need" + 0.004*"Calderdale" + 0.004*"education"
+2024-05-13 12:38:49,915 - topic diff=0.762214, rho=1.000000
+2024-05-13 12:38:49,915 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1202, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:49.915816', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:51,003 - Inspection date 2018-11-12 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:51,004 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:51,004 - Inspection date 2018-11-12 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:51,004 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:51,004 - Inspection date 2018-11-12 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:51,004 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:51,005 - Inspection date 2018-11-12 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:51,005 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:51,005 - Inspection date 2018-11-12 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:51,005 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:51,005 - Inspection date 2018-11-12 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:51,005 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:52,433 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:52,437 - built Dictionary<966 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1985 corpus positions)
+2024-05-13 12:38:52,437 - Dictionary lifecycle event {'msg': "built Dictionary<966 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1985 corpus positions)", 'datetime': '2024-05-13T12:38:52.437847', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:52,439 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:52,444 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:52,444 - using serial LDA version on this node
+2024-05-13 12:38:52,445 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:52,445 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:52,450 - -7.929 per-word bound, 243.7 perplexity estimate based on a held-out corpus of 1 documents with 1985 words
+2024-05-13 12:38:52,450 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:52,453 - topic #0 (0.333): 0.014*"’" + 0.011*"well" + 0.007*"impact" + 0.007*"good" + 0.007*"quality" + 0.006*"need" + 0.006*"needs" + 0.005*"progress" + 0.005*"effective" + 0.005*"teams"
+2024-05-13 12:38:52,454 - topic #1 (0.333): 0.014*"’" + 0.010*"well" + 0.010*"good" + 0.009*"plans" + 0.008*"teams" + 0.006*"needs" + 0.006*"impact" + 0.006*"need" + 0.006*"However" + 0.005*"quality"
+2024-05-13 12:38:52,454 - topic #2 (0.333): 0.014*"’" + 0.009*"needs" + 0.009*"need" + 0.009*"good" + 0.008*"well" + 0.007*"plans" + 0.007*"teams" + 0.007*"impact" + 0.006*"However" + 0.006*"quality"
+2024-05-13 12:38:52,454 - topic diff=0.758873, rho=1.000000
+2024-05-13 12:38:52,454 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=966, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:52.454750', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:53,492 - Inspection date 2019-01-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:53,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:53,493 - Inspection date 2019-01-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:53,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:53,493 - Inspection date 2019-01-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:53,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:53,493 - Inspection date 2019-01-14 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:53,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:53,494 - Inspection date 2019-01-14 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:53,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:53,494 - Inspection date 2019-01-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:53,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:55,025 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:55,029 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
+2024-05-13 12:38:55,029 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-05-13T12:38:55.029626', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:55,030 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:55,030 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:55,031 - using serial LDA version on this node
+2024-05-13 12:38:55,031 - 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
+2024-05-13 12:38:55,031 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:55,034 - -7.963 per-word bound, 249.6 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
+2024-05-13 12:38:55,035 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:55,036 - topic #0 (0.333): 0.013*"’" + 0.009*"well" + 0.006*"need" + 0.006*"needs" + 0.006*"carers" + 0.005*"good" + 0.005*"effective" + 0.005*"plans" + 0.005*"Central" + 0.004*"progress"
+2024-05-13 12:38:55,036 - topic #1 (0.333): 0.017*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"plans" + 0.006*"need" + 0.006*"good" + 0.005*"Bedfordshire" + 0.005*"carers" + 0.005*"supported" + 0.005*"progress"
+2024-05-13 12:38:55,036 - topic #2 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"carers" + 0.007*"good" + 0.007*"progress" + 0.006*"need" + 0.005*"plans" + 0.005*"2022" + 0.005*"education"
+2024-05-13 12:38:55,036 - topic diff=0.779791, rho=1.000000
+2024-05-13 12:38:55,036 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1030, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:55.036912', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:56,068 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:56,069 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:56,069 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:56,069 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:56,069 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:56,069 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:56,070 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:56,070 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:56,070 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:56,070 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:56,070 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:56,070 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:57,522 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:38:57,524 - built Dictionary<926 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)
+2024-05-13 12:38:57,524 - Dictionary lifecycle event {'msg': "built Dictionary<926 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-05-13T12:38:57.524477', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:57,526 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:38:57,526 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:38:57,526 - using serial LDA version on this node
+2024-05-13 12:38:57,527 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:38:57,527 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:38:57,531 - -7.891 per-word bound, 237.3 perplexity estimate based on a held-out corpus of 1 documents with 1878 words
+2024-05-13 12:38:57,531 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:38:57,533 - topic #0 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"good" + 0.006*"well" + 0.005*"However" + 0.005*"supported" + 0.005*"plans" + 0.005*"practice" + 0.005*"timely" + 0.004*"always"
+2024-05-13 12:38:57,533 - topic #1 (0.333): 0.011*"’" + 0.010*"good" + 0.008*"well" + 0.007*"needs" + 0.007*"need" + 0.006*"always" + 0.006*"supported" + 0.006*"plans" + 0.006*"practice" + 0.005*"quality"
+2024-05-13 12:38:57,533 - topic #2 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"plans" + 0.007*"practice" + 0.006*"ensure" + 0.006*"good" + 0.006*"always" + 0.005*"carers" + 0.005*"risk"
+2024-05-13 12:38:57,533 - topic diff=0.772968, rho=1.000000
+2024-05-13 12:38:57,533 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=926, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:38:57.533904', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:38:58,838 - Inspection date 2019-11-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:38:58,838 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:58,838 - Inspection date 2019-11-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:38:58,838 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:58,838 - Inspection date 2019-11-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:38:58,839 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:58,839 - Inspection date 2019-11-18 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:38:58,839 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:58,839 - Inspection date 2019-11-18 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:38:58,839 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:38:58,839 - Inspection date 2019-11-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:38:58,839 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:00,503 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:00,507 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)
+2024-05-13 12:39:00,507 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)", 'datetime': '2024-05-13T12:39:00.507546', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:00,509 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:00,509 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:00,510 - using serial LDA version on this node
+2024-05-13 12:39:00,510 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:00,510 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:00,517 - -8.001 per-word bound, 256.2 perplexity estimate based on a held-out corpus of 1 documents with 2186 words
+2024-05-13 12:39:00,517 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:00,520 - topic #0 (0.333): 0.023*"’" + 0.008*"well" + 0.008*"needs" + 0.005*"practice" + 0.005*"impact" + 0.005*"timely" + 0.004*"order" + 0.004*"effective" + 0.004*"progress" + 0.004*"plans"
+2024-05-13 12:39:00,520 - topic #1 (0.333): 0.024*"’" + 0.005*"needs" + 0.005*"well" + 0.004*"effective" + 0.004*"learning" + 0.004*"plans" + 0.004*"effectively" + 0.004*"always" + 0.004*"practice" + 0.004*"use"
+2024-05-13 12:39:00,520 - topic #2 (0.333): 0.017*"’" + 0.007*"well" + 0.007*"needs" + 0.004*"receive" + 0.004*"practice" + 0.004*"order" + 0.004*"effectively" + 0.004*"learning" + 0.004*"always" + 0.004*"However"
+2024-05-13 12:39:00,520 - topic diff=0.770563, rho=1.000000
+2024-05-13 12:39:00,521 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:00.521218', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:01,493 - Inspection date 2019-03-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:01,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:01,493 - Inspection date 2019-03-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:01,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:01,494 - Inspection date 2019-03-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:01,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:01,494 - Inspection date 2019-03-18 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:01,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:01,494 - Inspection date 2019-03-18 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:01,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:01,494 - Inspection date 2019-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:01,495 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:03,262 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:03,264 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)
+2024-05-13 12:39:03,264 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-05-13T12:39:03.264949', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:03,266 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:03,266 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:03,266 - using serial LDA version on this node
+2024-05-13 12:39:03,266 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:03,267 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:03,270 - -8.047 per-word bound, 264.6 perplexity estimate based on a held-out corpus of 1 documents with 2639 words
+2024-05-13 12:39:03,270 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:03,272 - topic #0 (0.333): 0.019*"’" + 0.007*"plans" + 0.005*"2022" + 0.005*"Bradford" + 0.005*"However" + 0.005*"quality" + 0.005*"needs" + 0.004*"21" + 0.004*"progress" + 0.004*"risk"
+2024-05-13 12:39:03,272 - topic #1 (0.333): 0.022*"’" + 0.007*"plans" + 0.005*"needs" + 0.005*"impact" + 0.005*"Bradford" + 0.005*"2" + 0.005*"◼" + 0.004*"senior" + 0.004*"Council" + 0.004*"need"
+2024-05-13 12:39:03,272 - topic #2 (0.333): 0.021*"’" + 0.006*"plans" + 0.004*"risk" + 0.004*"2" + 0.004*"Metropolitan" + 0.004*"Borough" + 0.004*"needs" + 0.004*"Bradford" + 0.004*"November" + 0.004*"practice"
+2024-05-13 12:39:03,272 - topic diff=0.806681, rho=1.000000
+2024-05-13 12:39:03,273 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1164, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:03.273110', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:04,300 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:04,300 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:04,301 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:04,301 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:04,301 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:04,301 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:04,301 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:04,301 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:04,302 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:04,302 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:04,302 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:04,302 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:06,017 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:06,019 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)
+2024-05-13 12:39:06,020 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-05-13T12:39:06.020058', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:06,021 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:06,021 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:06,021 - using serial LDA version on this node
+2024-05-13 12:39:06,021 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:06,021 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:06,024 - -7.839 per-word bound, 229.0 perplexity estimate based on a held-out corpus of 1 documents with 1767 words
+2024-05-13 12:39:06,025 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:06,026 - topic #0 (0.333): 0.013*"needs" + 0.012*"’" + 0.010*"well" + 0.010*"ensure" + 0.007*"effective" + 0.006*"progress" + 0.006*"plans" + 0.006*"good" + 0.006*"clear" + 0.005*"practice"
+2024-05-13 12:39:06,026 - topic #1 (0.333): 0.012*"’" + 0.011*"needs" + 0.011*"well" + 0.008*"ensure" + 0.007*"effective" + 0.006*"clear" + 0.006*"good" + 0.005*"plans" + 0.005*"supported" + 0.005*"progress"
+2024-05-13 12:39:06,026 - topic #2 (0.333): 0.012*"’" + 0.010*"needs" + 0.009*"well" + 0.008*"ensure" + 0.007*"clear" + 0.006*"progress" + 0.005*"individual" + 0.004*"practice" + 0.004*"within" + 0.004*"effective"
+2024-05-13 12:39:06,026 - topic diff=0.745113, rho=1.000000
+2024-05-13 12:39:06,026 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=876, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:06.026967', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:07,229 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:07,229 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:07,229 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:07,230 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:07,230 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:07,230 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:07,230 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:07,231 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:07,231 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:07,231 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:07,231 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:07,232 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:08,779 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:08,782 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)
+2024-05-13 12:39:08,782 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-05-13T12:39:08.782344', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:08,783 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:08,783 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:08,783 - using serial LDA version on this node
+2024-05-13 12:39:08,784 - 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
+2024-05-13 12:39:08,784 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:08,787 - -7.905 per-word bound, 239.6 perplexity estimate based on a held-out corpus of 1 documents with 2281 words
+2024-05-13 12:39:08,787 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:08,789 - topic #0 (0.333): 0.021*"’" + 0.008*"quality" + 0.007*"Wakefield" + 0.007*"November" + 0.006*"leaders" + 0.006*"effective" + 0.006*"good" + 0.006*"well" + 0.006*"plans" + 0.005*"progress"
+2024-05-13 12:39:08,789 - topic #1 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"Wakefield" + 0.008*"leaders" + 0.007*"good" + 0.007*"quality" + 0.006*"November" + 0.006*"effective" + 0.006*"needs" + 0.006*"practice"
+2024-05-13 12:39:08,789 - topic #2 (0.333): 0.014*"’" + 0.008*"November" + 0.007*"Wakefield" + 0.007*"well" + 0.007*"effective" + 0.007*"quality" + 0.007*"leaders" + 0.007*"plans" + 0.006*"good" + 0.005*"progress"
+2024-05-13 12:39:08,789 - topic diff=0.799084, rho=1.000000
+2024-05-13 12:39:08,789 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1007, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:08.789907', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:09,768 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:09,768 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:09,769 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:09,769 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:09,769 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:09,770 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:09,770 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:09,770 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:09,770 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:09,770 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:09,771 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:09,771 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:11,470 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:11,471 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)
+2024-05-13 12:39:11,472 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-05-13T12:39:11.472138', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:11,473 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:11,473 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:11,473 - using serial LDA version on this node
+2024-05-13 12:39:11,473 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:11,474 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:11,477 - -7.872 per-word bound, 234.3 perplexity estimate based on a held-out corpus of 1 documents with 1855 words
+2024-05-13 12:39:11,477 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:11,478 - topic #0 (0.333): 0.014*"’" + 0.009*"March" + 0.006*"needs" + 0.006*"effective" + 0.006*"However" + 0.006*"well" + 0.005*"quality" + 0.005*"plans" + 0.005*"York" + 0.005*"good"
+2024-05-13 12:39:11,478 - topic #1 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"quality" + 0.006*"effective" + 0.006*"March" + 0.006*"plans" + 0.005*"York" + 0.005*"ensure" + 0.005*"7" + 0.005*"However"
+2024-05-13 12:39:11,478 - topic #2 (0.333): 0.017*"’" + 0.008*"needs" + 0.007*"quality" + 0.006*"March" + 0.005*"ensure" + 0.005*"effective" + 0.005*"education" + 0.005*"training" + 0.005*"practice" + 0.005*"supported"
+2024-05-13 12:39:11,479 - topic diff=0.765947, rho=1.000000
+2024-05-13 12:39:11,479 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=909, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:11.479264', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:12,396 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:12,397 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:12,397 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:12,397 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:12,397 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:12,398 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:12,398 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:12,398 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:12,398 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:12,398 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:12,398 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:12,398 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:13,891 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:13,893 - built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)
+2024-05-13 12:39:13,893 - Dictionary lifecycle event {'msg': "built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)", 'datetime': '2024-05-13T12:39:13.893615', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:13,894 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:13,894 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:13,895 - using serial LDA version on this node
+2024-05-13 12:39:13,895 - 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
+2024-05-13 12:39:13,895 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:13,900 - -7.950 per-word bound, 247.3 perplexity estimate based on a held-out corpus of 1 documents with 2157 words
+2024-05-13 12:39:13,900 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:13,903 - topic #0 (0.333): 0.014*"well" + 0.011*"’" + 0.010*"quality" + 0.009*"effective" + 0.008*"leaders" + 0.006*"good" + 0.006*"arrangements" + 0.006*"plans" + 0.006*"timely" + 0.005*"Senior"
+2024-05-13 12:39:13,903 - topic #1 (0.333): 0.013*"’" + 0.013*"well" + 0.008*"quality" + 0.007*"leaders" + 0.007*"effective" + 0.006*"good" + 0.006*"timely" + 0.005*"plans" + 0.005*"arrangements" + 0.004*"highly"
+2024-05-13 12:39:13,903 - topic #2 (0.333): 0.017*"well" + 0.012*"’" + 0.011*"quality" + 0.009*"leaders" + 0.009*"effective" + 0.006*"plans" + 0.005*"arrangements" + 0.005*"good" + 0.005*"timely" + 0.005*"highly"
+2024-05-13 12:39:13,903 - topic diff=0.780289, rho=1.000000
+2024-05-13 12:39:13,903 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1014, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:13.903870', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:15,098 - Inspection date 2019-10-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:15,099 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:15,099 - Inspection date 2019-10-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:15,099 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:15,099 - Inspection date 2019-10-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:15,099 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:15,100 - Inspection date 2019-10-14 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:15,100 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:15,100 - Inspection date 2019-10-14 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:15,100 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:15,101 - Inspection date 2019-10-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:15,101 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:16,308 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:16,309 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)
+2024-05-13 12:39:16,309 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-05-13T12:39:16.309962', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:16,310 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:16,310 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:16,311 - using serial LDA version on this node
+2024-05-13 12:39:16,311 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:16,311 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:16,314 - -7.682 per-word bound, 205.4 perplexity estimate based on a held-out corpus of 1 documents with 1521 words
+2024-05-13 12:39:16,314 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:16,315 - topic #0 (0.333): 0.024*"’" + 0.013*"Scilly" + 0.012*"Isles" + 0.009*"practice" + 0.009*"need" + 0.007*"information" + 0.007*"needs" + 0.007*"protection" + 0.006*"quality" + 0.006*"place"
+2024-05-13 12:39:16,315 - topic #1 (0.333): 0.018*"’" + 0.013*"Isles" + 0.011*"Scilly" + 0.011*"information" + 0.008*"practice" + 0.007*"need" + 0.007*"needs" + 0.006*"protection" + 0.006*"quality" + 0.006*"13"
+2024-05-13 12:39:16,315 - topic #2 (0.333): 0.020*"’" + 0.011*"Scilly" + 0.010*"Isles" + 0.008*"information" + 0.007*"need" + 0.007*"practice" + 0.006*"protection" + 0.006*"needs" + 0.006*"risks" + 0.006*"11"
+2024-05-13 12:39:16,316 - topic diff=0.747071, rho=1.000000
+2024-05-13 12:39:16,316 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=754, num_topics=3, decay=0.5, chunksize=2000> in 0.00s', 'datetime': '2024-05-13T12:39:16.316222', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:17,192 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:17,192 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:17,192 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:17,192 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:17,193 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:17,193 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:17,193 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:17,193 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:17,193 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:17,193 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:17,193 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:17,193 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:18,800 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:18,802 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)
+2024-05-13 12:39:18,802 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-05-13T12:39:18.802644', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:18,803 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:18,803 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:18,804 - using serial LDA version on this node
+2024-05-13 12:39:18,804 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:18,804 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:18,807 - -7.850 per-word bound, 230.7 perplexity estimate based on a held-out corpus of 1 documents with 2074 words
+2024-05-13 12:39:18,808 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:18,809 - topic #0 (0.333): 0.013*"’" + 0.007*"Coventry" + 0.006*"plans" + 0.006*"well" + 0.006*"supported" + 0.006*"need" + 0.005*"family" + 0.005*"strong" + 0.004*"needs" + 0.004*"1"
+2024-05-13 12:39:18,809 - topic #1 (0.333): 0.021*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"supported" + 0.007*"plans" + 0.006*"family" + 0.005*"strong" + 0.005*"Coventry" + 0.005*"need" + 0.005*"understand"
+2024-05-13 12:39:18,809 - topic #2 (0.333): 0.022*"’" + 0.011*"Coventry" + 0.008*"needs" + 0.008*"well" + 0.007*"supported" + 0.006*"plans" + 0.006*"family" + 0.005*"strong" + 0.005*"need" + 0.004*"training"
+2024-05-13 12:39:18,809 - topic diff=0.807106, rho=1.000000
+2024-05-13 12:39:18,810 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=938, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:18.810002', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:19,794 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:19,794 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:19,794 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:19,794 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:19,794 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:19,794 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:19,795 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:19,795 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:19,795 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:19,795 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:19,795 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:19,795 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:22,095 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:22,098 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)
+2024-05-13 12:39:22,098 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-05-13T12:39:22.098221', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:22,099 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:22,099 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:22,099 - using serial LDA version on this node
+2024-05-13 12:39:22,100 - 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
+2024-05-13 12:39:22,100 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:22,104 - -8.084 per-word bound, 271.4 perplexity estimate based on a held-out corpus of 1 documents with 2653 words
+2024-05-13 12:39:22,104 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:22,105 - topic #0 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"practice" + 0.006*"leaders" + 0.006*"supported" + 0.005*"Darlington" + 0.005*"effective" + 0.005*"October" + 0.004*"need"
+2024-05-13 12:39:22,106 - topic #1 (0.333): 0.021*"’" + 0.008*"well" + 0.008*"leaders" + 0.008*"October" + 0.006*"needs" + 0.006*"Darlington" + 0.006*"practice" + 0.005*"quality" + 0.004*"family" + 0.004*"effective"
+2024-05-13 12:39:22,106 - topic #2 (0.333): 0.016*"’" + 0.007*"October" + 0.006*"Darlington" + 0.006*"leaders" + 0.005*"needs" + 0.005*"well" + 0.005*"practice" + 0.005*"education" + 0.005*"effective" + 0.004*"quality"
+2024-05-13 12:39:22,106 - topic diff=0.795962, rho=1.000000
+2024-05-13 12:39:22,106 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1195, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:22.106553', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:23,011 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:23,011 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:23,011 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:23,011 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:23,011 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:23,012 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:23,012 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:23,012 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:23,012 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:23,012 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:23,012 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:23,013 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:24,982 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:24,984 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)
+2024-05-13 12:39:24,984 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-05-13T12:39:24.984811', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:24,985 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:24,986 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:24,986 - using serial LDA version on this node
+2024-05-13 12:39:24,986 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:24,986 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:24,990 - -8.048 per-word bound, 264.7 perplexity estimate based on a held-out corpus of 1 documents with 2396 words
+2024-05-13 12:39:24,990 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:24,992 - topic #0 (0.333): 0.014*"’" + 0.011*"needs" + 0.006*"quality" + 0.006*"Derby" + 0.006*"receive" + 0.005*"need" + 0.005*"progress" + 0.005*"appropriate" + 0.005*"good" + 0.004*"well"
+2024-05-13 12:39:24,992 - topic #1 (0.333): 0.021*"’" + 0.009*"needs" + 0.009*"Derby" + 0.007*"quality" + 0.006*"leaders" + 0.006*"plans" + 0.006*"receive" + 0.005*"well" + 0.005*"good" + 0.005*"appropriate"
+2024-05-13 12:39:24,992 - topic #2 (0.333): 0.026*"’" + 0.008*"needs" + 0.006*"receive" + 0.006*"Derby" + 0.006*"quality" + 0.006*"progress" + 0.006*"plans" + 0.005*"appropriate" + 0.005*"well" + 0.005*"leaders"
+2024-05-13 12:39:24,992 - topic diff=0.773881, rho=1.000000
+2024-05-13 12:39:24,992 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1121, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:24.992662', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:25,870 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:25,870 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:25,870 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:25,871 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:25,871 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:25,871 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:25,871 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:25,871 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:25,871 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:25,872 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:25,872 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:25,872 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:27,253 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:27,256 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)
+2024-05-13 12:39:27,256 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-05-13T12:39:27.256541', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:27,257 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:27,257 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:27,258 - using serial LDA version on this node
+2024-05-13 12:39:27,258 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:27,258 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:27,262 - -8.035 per-word bound, 262.2 perplexity estimate based on a held-out corpus of 1 documents with 2035 words
+2024-05-13 12:39:27,262 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:27,264 - topic #0 (0.333): 0.014*"’" + 0.009*"well" + 0.007*"Derbyshire" + 0.005*"needs" + 0.005*"effective" + 0.005*"leaders" + 0.005*"plans" + 0.005*"10" + 0.005*"need" + 0.004*"health"
+2024-05-13 12:39:27,264 - topic #1 (0.333): 0.009*"’" + 0.005*"well" + 0.004*"Derbyshire" + 0.004*"plans" + 0.003*"November" + 0.003*"practice" + 0.003*"needs" + 0.003*"2023" + 0.003*"meetings" + 0.003*"positive"
+2024-05-13 12:39:27,264 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.007*"Derbyshire" + 0.006*"plans" + 0.005*"positive" + 0.005*"education" + 0.005*"health" + 0.005*"needs" + 0.005*"30" + 0.005*"good"
+2024-05-13 12:39:27,264 - topic diff=0.768982, rho=1.000000
+2024-05-13 12:39:27,265 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:27.265035', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:28,304 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:28,304 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:28,304 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:28,304 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:28,305 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:28,305 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:28,305 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:28,305 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:28,305 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:28,305 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:28,305 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:28,306 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:30,026 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:30,028 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)
+2024-05-13 12:39:30,029 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-05-13T12:39:30.029059', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:30,030 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:30,030 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:30,030 - using serial LDA version on this node
+2024-05-13 12:39:30,031 - 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
+2024-05-13 12:39:30,031 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:30,035 - -8.150 per-word bound, 284.0 perplexity estimate based on a held-out corpus of 1 documents with 2313 words
+2024-05-13 12:39:30,035 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:30,036 - topic #0 (0.333): 0.010*"’" + 0.005*"well" + 0.005*"risk" + 0.005*"progress" + 0.004*"leaders" + 0.004*"Devon" + 0.004*"case" + 0.004*"quality" + 0.004*"health" + 0.004*"practice"
+2024-05-13 12:39:30,036 - topic #1 (0.333): 0.009*"’" + 0.007*"well" + 0.005*"leaders" + 0.005*"health" + 0.004*"risk" + 0.004*"time" + 0.004*"progress" + 0.004*"need" + 0.004*"protection" + 0.004*"areas"
+2024-05-13 12:39:30,036 - topic #2 (0.333): 0.008*"’" + 0.005*"well" + 0.005*"health" + 0.005*"risk" + 0.005*"leaders" + 0.004*"progress" + 0.004*"risks" + 0.004*"case" + 0.004*"living" + 0.004*"protection"
+2024-05-13 12:39:30,037 - topic diff=0.735570, rho=1.000000
+2024-05-13 12:39:30,037 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:30.037215', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:31,057 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:31,057 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:31,057 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:31,058 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:31,058 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:31,058 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:31,058 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:31,058 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:31,058 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:31,058 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:31,059 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:31,059 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:32,643 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:32,647 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)
+2024-05-13 12:39:32,648 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-05-13T12:39:32.647970', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:32,649 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:32,649 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:32,649 - using serial LDA version on this node
+2024-05-13 12:39:32,650 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:32,650 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:32,654 - -8.115 per-word bound, 277.3 perplexity estimate based on a held-out corpus of 1 documents with 2429 words
+2024-05-13 12:39:32,654 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:32,656 - topic #0 (0.333): 0.019*"’" + 0.006*"well" + 0.006*"Doncaster" + 0.005*"records" + 0.005*"progress" + 0.005*"many" + 0.005*"leaders" + 0.005*"quality" + 0.004*"made" + 0.004*"Trust"
+2024-05-13 12:39:32,656 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"Doncaster" + 0.005*"plans" + 0.005*"many" + 0.005*"leaders" + 0.005*"information" + 0.005*"oversight" + 0.005*"25" + 0.004*"effective"
+2024-05-13 12:39:32,656 - topic #2 (0.333): 0.021*"’" + 0.006*"well" + 0.005*"Doncaster" + 0.005*"progress" + 0.005*"records" + 0.005*"arrangements" + 0.005*"quality" + 0.005*"14" + 0.005*"oversight" + 0.005*"leaders"
+2024-05-13 12:39:32,656 - topic diff=0.769976, rho=1.000000
+2024-05-13 12:39:32,656 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1175, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:32.656965', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:34,620 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:34,621 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:34,621 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:34,621 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:34,621 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:34,621 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:34,621 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:34,621 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:34,622 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:34,622 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:34,622 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:34,622 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:36,076 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:36,078 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)
+2024-05-13 12:39:36,078 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-05-13T12:39:36.078876', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:36,079 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:36,080 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:36,080 - using serial LDA version on this node
+2024-05-13 12:39:36,080 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:36,080 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:36,084 - -8.101 per-word bound, 274.5 perplexity estimate based on a held-out corpus of 1 documents with 1942 words
+2024-05-13 12:39:36,084 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:36,086 - topic #0 (0.333): 0.013*"’" + 0.007*"Dorset" + 0.005*"well" + 0.005*"good" + 0.005*"including" + 0.005*"27" + 0.004*"arrangements" + 0.004*"change" + 0.004*"Senior" + 0.004*"needs"
+2024-05-13 12:39:36,086 - topic #1 (0.333): 0.008*"’" + 0.007*"Dorset" + 0.004*"good" + 0.004*"well" + 0.004*"arrangements" + 0.003*"needs" + 0.003*"need" + 0.003*"8" + 0.003*"impact" + 0.003*"practice"
+2024-05-13 12:39:36,086 - topic #2 (0.333): 0.017*"’" + 0.009*"Dorset" + 0.007*"good" + 0.007*"well" + 0.005*"needs" + 0.005*"arrangements" + 0.005*"8" + 0.004*"leaders" + 0.004*"supported" + 0.004*"impact"
+2024-05-13 12:39:36,086 - topic diff=0.744346, rho=1.000000
+2024-05-13 12:39:36,086 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1067, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:36.086672', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:37,048 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:37,049 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:37,049 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:37,049 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:37,049 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:37,049 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:37,050 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:37,050 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:37,050 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:37,050 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:37,051 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:37,051 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:38,537 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:38,539 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)
+2024-05-13 12:39:38,539 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-05-13T12:39:38.539706', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:38,540 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:38,540 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:38,541 - using serial LDA version on this node
+2024-05-13 12:39:38,541 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:38,541 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:38,545 - -8.012 per-word bound, 258.1 perplexity estimate based on a held-out corpus of 1 documents with 2138 words
+2024-05-13 12:39:38,545 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:38,546 - topic #0 (0.333): 0.011*"’" + 0.011*"needs" + 0.007*"Dudley" + 0.006*"well" + 0.005*"plans" + 0.004*"oversight" + 0.004*"arrangements" + 0.004*"always" + 0.004*"However" + 0.004*"2022"
+2024-05-13 12:39:38,546 - topic #1 (0.333): 0.017*"’" + 0.012*"needs" + 0.009*"Dudley" + 0.006*"arrangements" + 0.006*"plans" + 0.006*"always" + 0.005*"well" + 0.005*"ensure" + 0.005*"oversight" + 0.005*"enough"
+2024-05-13 12:39:38,547 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"Dudley" + 0.005*"well" + 0.005*"management" + 0.005*"quality" + 0.005*"always" + 0.004*"arrangements" + 0.004*"practice" + 0.004*"11"
+2024-05-13 12:39:38,547 - topic diff=0.760667, rho=1.000000
+2024-05-13 12:39:38,547 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1050, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:38.547328', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:39,501 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:39,501 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:39,501 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:39,502 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:39,502 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:39,502 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:39,502 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:39,502 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:39,503 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:39,503 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:39,503 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:39,503 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:41,538 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:41,540 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)
+2024-05-13 12:39:41,540 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-05-13T12:39:41.540844', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:41,541 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:41,542 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:41,542 - using serial LDA version on this node
+2024-05-13 12:39:41,542 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:41,542 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:41,549 - -7.977 per-word bound, 252.0 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
+2024-05-13 12:39:41,549 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:41,551 - topic #0 (0.333): 0.017*"’" + 0.011*"needs" + 0.008*"May" + 0.007*"well" + 0.007*"plans" + 0.007*"Durham" + 0.006*"practice" + 0.006*"ensure" + 0.005*"leaders" + 0.005*"risks"
+2024-05-13 12:39:41,552 - topic #1 (0.333): 0.013*"’" + 0.011*"needs" + 0.006*"Durham" + 0.006*"plans" + 0.005*"well" + 0.004*"May" + 0.004*"practice" + 0.004*"family" + 0.004*"identified" + 0.004*"risks"
+2024-05-13 12:39:41,552 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"May" + 0.008*"Durham" + 0.007*"ensure" + 0.007*"well" + 0.006*"plans" + 0.005*"practice" + 0.005*"making" + 0.005*"family"
+2024-05-13 12:39:41,552 - topic diff=0.777693, rho=1.000000
+2024-05-13 12:39:41,552 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1051, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:41.552893', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:42,561 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:42,561 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:42,561 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:42,561 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:42,561 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:42,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:42,562 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:42,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:42,562 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:42,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:42,562 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:42,562 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:44,054 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:44,057 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)
+2024-05-13 12:39:44,057 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-05-13T12:39:44.057163', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:44,058 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:44,058 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:44,058 - using serial LDA version on this node
+2024-05-13 12:39:44,059 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:44,059 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:44,062 - -7.922 per-word bound, 242.6 perplexity estimate based on a held-out corpus of 1 documents with 2014 words
+2024-05-13 12:39:44,062 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:44,063 - topic #0 (0.333): 0.018*"’" + 0.010*"well" + 0.009*"needs" + 0.007*"progress" + 0.007*"Riding" + 0.005*"East" + 0.005*"education" + 0.005*"plans" + 0.005*"February" + 0.005*"good"
+2024-05-13 12:39:44,064 - topic #1 (0.333): 0.013*"’" + 0.009*"plans" + 0.007*"needs" + 0.007*"well" + 0.006*"progress" + 0.005*"East" + 0.005*"partners" + 0.005*"Riding" + 0.004*"30" + 0.004*"January"
+2024-05-13 12:39:44,064 - topic #2 (0.333): 0.016*"’" + 0.010*"plans" + 0.010*"needs" + 0.008*"well" + 0.007*"progress" + 0.007*"East" + 0.006*"Riding" + 0.005*"10" + 0.005*"partners" + 0.005*"supported"
+2024-05-13 12:39:44,064 - topic diff=0.778182, rho=1.000000
+2024-05-13 12:39:44,064 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=972, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:44.064454', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:45,135 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:45,135 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:45,136 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:45,136 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:45,136 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:45,136 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:45,137 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:45,137 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:45,137 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:45,137 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:45,138 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:45,138 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:46,924 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:46,928 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)
+2024-05-13 12:39:46,928 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-05-13T12:39:46.928433', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:46,930 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:46,930 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:46,930 - using serial LDA version on this node
+2024-05-13 12:39:46,931 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:46,931 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:46,935 - -8.081 per-word bound, 270.7 perplexity estimate based on a held-out corpus of 1 documents with 2220 words
+2024-05-13 12:39:46,935 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:46,936 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"impact" + 0.006*"plans" + 0.006*"needs" + 0.006*"progress" + 0.006*"East" + 0.006*"Sussex" + 0.005*"11" + 0.005*"including"
+2024-05-13 12:39:46,937 - topic #1 (0.333): 0.018*"’" + 0.010*"well" + 0.009*"needs" + 0.009*"plans" + 0.008*"East" + 0.006*"Sussex" + 0.006*"progress" + 0.005*"11" + 0.005*"including" + 0.005*"relationships"
+2024-05-13 12:39:46,937 - topic #2 (0.333): 0.015*"’" + 0.010*"well" + 0.007*"plans" + 0.007*"needs" + 0.007*"including" + 0.006*"progress" + 0.006*"Sussex" + 0.005*"effective" + 0.005*"East" + 0.005*"experiences"
+2024-05-13 12:39:46,937 - topic diff=0.758318, rho=1.000000
+2024-05-13 12:39:46,937 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1111, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:46.937473', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:47,898 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:47,899 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:47,899 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:47,899 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:47,899 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:47,899 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:47,899 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:47,899 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:47,900 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:47,900 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:47,900 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:47,900 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:49,655 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:49,658 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)
+2024-05-13 12:39:49,658 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-05-13T12:39:49.658630', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:49,659 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:49,659 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:49,660 - using serial LDA version on this node
+2024-05-13 12:39:49,660 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:49,660 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:49,664 - -8.012 per-word bound, 258.2 perplexity estimate based on a held-out corpus of 1 documents with 2686 words
+2024-05-13 12:39:49,664 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:49,666 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"progress" + 0.006*"plans" + 0.005*"‘" + 0.005*"experiences" + 0.005*"family" + 0.005*"understand" + 0.005*"helped" + 0.004*"well"
+2024-05-13 12:39:49,666 - topic #1 (0.333): 0.018*"’" + 0.008*"well" + 0.006*"family" + 0.006*"needs" + 0.006*"progress" + 0.005*"plans" + 0.005*"26" + 0.004*"‘" + 0.004*"parents" + 0.004*"Essex"
+2024-05-13 12:39:49,666 - topic #2 (0.333): 0.019*"’" + 0.008*"well" + 0.007*"progress" + 0.007*"plans" + 0.006*"risk" + 0.006*"Essex" + 0.006*"need" + 0.006*"advisers" + 0.005*"understand" + 0.005*"needs"
+2024-05-13 12:39:49,666 - topic diff=0.811191, rho=1.000000
+2024-05-13 12:39:49,666 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:49.666757', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:50,793 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:50,793 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:50,793 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:50,793 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:50,794 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:50,794 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:50,794 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:50,794 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:50,794 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:50,794 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:50,795 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:50,795 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:52,456 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:52,458 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)
+2024-05-13 12:39:52,459 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-05-13T12:39:52.459083', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:52,460 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:52,460 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:52,460 - using serial LDA version on this node
+2024-05-13 12:39:52,461 - 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
+2024-05-13 12:39:52,461 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:52,464 - -8.046 per-word bound, 264.4 perplexity estimate based on a held-out corpus of 1 documents with 2356 words
+2024-05-13 12:39:52,464 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:52,466 - topic #0 (0.333): 0.010*"’" + 0.009*"effective" + 0.006*"good" + 0.006*"quality" + 0.005*"needs" + 0.005*"practice" + 0.005*"well" + 0.004*"improve" + 0.004*"team" + 0.004*"education"
+2024-05-13 12:39:52,466 - topic #1 (0.333): 0.018*"’" + 0.008*"effective" + 0.007*"good" + 0.007*"practice" + 0.007*"quality" + 0.006*"timely" + 0.006*"well" + 0.005*"needs" + 0.005*"plans" + 0.005*"home"
+2024-05-13 12:39:52,466 - topic #2 (0.333): 0.010*"’" + 0.009*"effective" + 0.006*"needs" + 0.006*"practice" + 0.006*"good" + 0.005*"need" + 0.005*"quality" + 0.005*"impact" + 0.005*"timely" + 0.005*"well"
+2024-05-13 12:39:52,466 - topic diff=0.780831, rho=1.000000
+2024-05-13 12:39:52,466 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:52.466922', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:53,502 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:53,502 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:53,502 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:53,502 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:53,503 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:53,503 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:53,503 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:53,503 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:53,503 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:53,503 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:53,503 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:53,504 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:54,953 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:54,955 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)
+2024-05-13 12:39:54,956 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-05-13T12:39:54.956160', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:54,957 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:54,957 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:54,957 - using serial LDA version on this node
+2024-05-13 12:39:54,958 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:54,958 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:54,962 - -8.061 per-word bound, 267.0 perplexity estimate based on a held-out corpus of 1 documents with 2579 words
+2024-05-13 12:39:54,962 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:54,963 - topic #0 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"2022" + 0.006*"plans" + 0.006*"progress" + 0.006*"family" + 0.005*"Gloucestershire" + 0.005*"appropriate" + 0.005*"February" + 0.005*"timely"
+2024-05-13 12:39:54,963 - topic #1 (0.333): 0.015*"’" + 0.010*"needs" + 0.007*"February" + 0.007*"2022" + 0.005*"plans" + 0.005*"well" + 0.005*"progress" + 0.005*"experienced" + 0.005*"good" + 0.005*"7"
+2024-05-13 12:39:54,964 - topic #2 (0.333): 0.017*"’" + 0.008*"February" + 0.007*"plans" + 0.007*"well" + 0.006*"needs" + 0.006*"2022" + 0.005*"Gloucestershire" + 0.005*"protection" + 0.004*"effective" + 0.004*"18"
+2024-05-13 12:39:54,964 - topic diff=0.820534, rho=1.000000
+2024-05-13 12:39:54,964 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:54.964257', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:56,149 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:56,149 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:56,150 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:56,150 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:56,150 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:56,150 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:56,150 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:56,151 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:56,151 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:56,151 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:56,151 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:56,151 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:57,229 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:57,232 - built Dictionary<815 unique tokens: ["'s", '0161', '02', '0300', '1']...> from 1 documents (total 1700 corpus positions)
+2024-05-13 12:39:57,232 - Dictionary lifecycle event {'msg': 'built Dictionary<815 unique tokens: ["\'s", \'0161\', \'02\', \'0300\', \'1\']...> from 1 documents (total 1700 corpus positions)', 'datetime': '2024-05-13T12:39:57.232639', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:57,233 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:57,234 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:57,234 - using serial LDA version on this node
+2024-05-13 12:39:57,235 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:39:57,235 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:57,240 - -7.747 per-word bound, 214.8 perplexity estimate based on a held-out corpus of 1 documents with 1700 words
+2024-05-13 12:39:57,241 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:57,243 - topic #0 (0.333): 0.009*"’" + 0.007*"well" + 0.007*"good" + 0.007*"practice" + 0.007*"effective" + 0.006*"planning" + 0.006*"needs" + 0.006*"plans" + 0.006*"need" + 0.006*"risk"
+2024-05-13 12:39:57,243 - topic #1 (0.333): 0.010*"well" + 0.010*"’" + 0.009*"plans" + 0.008*"practice" + 0.007*"risk" + 0.007*"needs" + 0.006*"planning" + 0.006*"need" + 0.006*"effective" + 0.005*"quality"
+2024-05-13 12:39:57,243 - topic #2 (0.333): 0.015*"’" + 0.012*"well" + 0.010*"needs" + 0.009*"practice" + 0.007*"always" + 0.007*"need" + 0.007*"good" + 0.007*"plans" + 0.006*"risk" + 0.006*"quality"
+2024-05-13 12:39:57,244 - topic diff=0.781495, rho=1.000000
+2024-05-13 12:39:57,244 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=815, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:57.244219', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:58,245 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:39:58,245 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:58,245 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:39:58,246 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:58,246 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:39:58,246 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:58,246 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:39:58,246 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:58,247 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:39:58,247 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:58,247 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:39:58,247 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:39:59,818 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:39:59,821 - built Dictionary<1182 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2382 corpus positions)
+2024-05-13 12:39:59,821 - Dictionary lifecycle event {'msg': "built Dictionary<1182 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2382 corpus positions)", 'datetime': '2024-05-13T12:39:59.821923', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:39:59,823 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:39:59,823 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:39:59,823 - using serial LDA version on this node
+2024-05-13 12:39:59,823 - 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
+2024-05-13 12:39:59,823 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:39:59,827 - -8.139 per-word bound, 282.0 perplexity estimate based on a held-out corpus of 1 documents with 2382 words
+2024-05-13 12:39:59,828 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:39:59,829 - topic #0 (0.333): 0.023*"’" + 0.008*"needs" + 0.006*"well" + 0.006*"plans" + 0.005*"quality" + 0.005*"leaders" + 0.004*"strong" + 0.004*"home" + 0.004*"progress" + 0.004*"improve"
+2024-05-13 12:39:59,829 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.006*"well" + 0.006*"plans" + 0.004*"leaders" + 0.004*"Hampshire" + 0.004*"highly" + 0.004*"health" + 0.004*"home" + 0.004*"strong"
+2024-05-13 12:39:59,829 - topic #2 (0.333): 0.014*"’" + 0.005*"plans" + 0.005*"needs" + 0.004*"well" + 0.004*"strong" + 0.004*"quality" + 0.004*"need" + 0.003*"carers" + 0.003*"Hampshire" + 0.003*"leaders"
+2024-05-13 12:39:59,830 - topic diff=0.754511, rho=1.000000
+2024-05-13 12:39:59,830 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1182, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:39:59.830156', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:00,851 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:00,851 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:00,851 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:00,851 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:00,852 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:00,852 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:00,852 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:00,852 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:00,852 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:00,852 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:00,853 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:00,853 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:02,405 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:02,407 - built Dictionary<1152 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2392 corpus positions)
+2024-05-13 12:40:02,408 - Dictionary lifecycle event {'msg': 'built Dictionary<1152 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2392 corpus positions)', 'datetime': '2024-05-13T12:40:02.408112', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:02,409 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:02,409 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:02,409 - using serial LDA version on this node
+2024-05-13 12:40:02,410 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:02,410 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:02,413 - -8.088 per-word bound, 272.2 perplexity estimate based on a held-out corpus of 1 documents with 2392 words
+2024-05-13 12:40:02,413 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:02,415 - topic #0 (0.333): 0.012*"’" + 0.007*"well" + 0.005*"quality" + 0.005*"strong" + 0.004*"early" + 0.004*"good" + 0.004*"plans" + 0.004*"experiences" + 0.003*"education" + 0.003*"timely"
+2024-05-13 12:40:02,415 - topic #1 (0.333): 0.013*"’" + 0.008*"well" + 0.007*"quality" + 0.006*"progress" + 0.006*"strong" + 0.005*"practice" + 0.004*"good" + 0.004*"impact" + 0.004*"early" + 0.004*"‘"
+2024-05-13 12:40:02,415 - topic #2 (0.333): 0.020*"’" + 0.010*"well" + 0.007*"quality" + 0.006*"strong" + 0.006*"good" + 0.005*"plans" + 0.005*"needs" + 0.004*"education" + 0.004*"impact" + 0.004*"agency"
+2024-05-13 12:40:02,415 - topic diff=0.765242, rho=1.000000
+2024-05-13 12:40:02,416 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1152, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:02.416049', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:03,341 - Inspection date 2018-07-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:03,341 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:03,342 - Inspection date 2018-07-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:03,342 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:03,342 - Inspection date 2018-07-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:03,342 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:03,342 - Inspection date 2018-07-23 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:03,342 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:03,342 - Inspection date 2018-07-23 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:03,342 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:03,342 - Inspection date 2018-07-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:03,343 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:05,172 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:05,176 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)
+2024-05-13 12:40:05,177 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-05-13T12:40:05.176972', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:05,178 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:05,179 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:05,179 - using serial LDA version on this node
+2024-05-13 12:40:05,179 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:05,180 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:05,186 - -8.044 per-word bound, 263.8 perplexity estimate based on a held-out corpus of 1 documents with 2531 words
+2024-05-13 12:40:05,187 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:05,189 - topic #0 (0.333): 0.019*"’" + 0.007*"practice" + 0.006*"lack" + 0.005*"Herefordshire" + 0.005*"many" + 0.004*"need" + 0.004*"impact" + 0.004*"18" + 0.004*"oversight" + 0.004*"plans"
+2024-05-13 12:40:05,189 - topic #1 (0.333): 0.018*"’" + 0.005*"needs" + 0.005*"Herefordshire" + 0.005*"impact" + 0.005*"lack" + 0.005*"practice" + 0.004*"July" + 0.004*"plans" + 0.004*"agency" + 0.004*"risk"
+2024-05-13 12:40:05,190 - topic #2 (0.333): 0.014*"’" + 0.005*"practice" + 0.005*"needs" + 0.005*"Herefordshire" + 0.005*"progress" + 0.005*"impact" + 0.005*"many" + 0.004*"lack" + 0.004*"quality" + 0.004*"across"
+2024-05-13 12:40:05,190 - topic diff=0.786958, rho=1.000000
+2024-05-13 12:40:05,190 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:05.190364', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:06,229 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:06,229 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:06,229 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:06,230 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:06,230 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:06,230 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:06,230 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:06,230 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:06,230 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:06,231 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:06,231 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:06,231 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:07,706 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:07,709 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)
+2024-05-13 12:40:07,709 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-05-13T12:40:07.709540', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:07,710 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:07,710 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:07,711 - using serial LDA version on this node
+2024-05-13 12:40:07,711 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:07,711 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:07,715 - -8.132 per-word bound, 280.6 perplexity estimate based on a held-out corpus of 1 documents with 2456 words
+2024-05-13 12:40:07,715 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:07,717 - topic #0 (0.333): 0.025*"’" + 0.007*"Hertfordshire" + 0.006*"well" + 0.005*"receive" + 0.005*"plans" + 0.005*"effective" + 0.005*"27" + 0.004*"January" + 0.004*"need" + 0.004*"23"
+2024-05-13 12:40:07,717 - topic #1 (0.333): 0.023*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Hertfordshire" + 0.005*"receive" + 0.004*"plans" + 0.004*"family" + 0.004*"positive" + 0.004*"risk" + 0.004*"‘"
+2024-05-13 12:40:07,717 - topic #2 (0.333): 0.019*"’" + 0.007*"needs" + 0.006*"well" + 0.005*"Hertfordshire" + 0.004*"receive" + 0.004*"2023" + 0.004*"27" + 0.004*"supported" + 0.004*"plans" + 0.004*"need"
+2024-05-13 12:40:07,717 - topic diff=0.789793, rho=1.000000
+2024-05-13 12:40:07,717 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:07.717719', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:09,618 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:09,618 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:09,618 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:09,618 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:09,619 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:09,619 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:09,619 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:09,619 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:09,619 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:09,619 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:09,619 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:09,619 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:11,126 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:11,128 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)
+2024-05-13 12:40:11,129 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-05-13T12:40:11.129062', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:11,130 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:11,130 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:11,130 - using serial LDA version on this node
+2024-05-13 12:40:11,130 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:11,130 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:11,134 - -7.956 per-word bound, 248.3 perplexity estimate based on a held-out corpus of 1 documents with 1934 words
+2024-05-13 12:40:11,134 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:11,135 - topic #0 (0.333): 0.014*"’" + 0.006*"leaders" + 0.005*"improve" + 0.005*"30" + 0.005*"practice" + 0.005*"supported" + 0.005*"time" + 0.004*"well" + 0.004*"PAs" + 0.004*"Senior"
+2024-05-13 12:40:11,135 - topic #1 (0.333): 0.022*"’" + 0.010*"leaders" + 0.007*"needs" + 0.006*"well" + 0.006*"plans" + 0.006*"progress" + 0.006*"3" + 0.006*"Wight" + 0.006*"supported" + 0.005*"Isle"
+2024-05-13 12:40:11,135 - topic #2 (0.333): 0.012*"’" + 0.008*"leaders" + 0.005*"well" + 0.005*"Senior" + 0.005*"Isle" + 0.005*"needs" + 0.005*"30" + 0.004*"improve" + 0.004*"protection" + 0.004*"information"
+2024-05-13 12:40:11,135 - topic diff=0.792032, rho=1.000000
+2024-05-13 12:40:11,135 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:11.135959', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:12,284 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:12,284 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:12,284 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:12,284 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:12,284 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:12,285 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:12,285 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:12,285 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:12,285 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:12,285 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:12,285 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:12,285 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:14,713 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:14,716 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)
+2024-05-13 12:40:14,716 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-05-13T12:40:14.716563', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:14,717 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:14,718 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:14,718 - using serial LDA version on this node
+2024-05-13 12:40:14,718 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:14,718 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:14,723 - -8.166 per-word bound, 287.3 perplexity estimate based on a held-out corpus of 1 documents with 2888 words
+2024-05-13 12:40:14,723 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:14,725 - topic #0 (0.333): 0.021*"’" + 0.009*"Kent" + 0.008*"needs" + 0.007*"Council" + 0.006*"supported" + 0.006*"well" + 0.005*"practice" + 0.005*"County" + 0.005*"leaders" + 0.005*"progress"
+2024-05-13 12:40:14,725 - topic #1 (0.333): 0.016*"’" + 0.010*"Kent" + 0.007*"well" + 0.006*"needs" + 0.006*"Council" + 0.005*"County" + 0.005*"progress" + 0.004*"2022" + 0.004*"supported" + 0.004*"impact"
+2024-05-13 12:40:14,725 - topic #2 (0.333): 0.016*"’" + 0.011*"Kent" + 0.006*"needs" + 0.006*"supported" + 0.005*"well" + 0.005*"County" + 0.004*"ensure" + 0.004*"progress" + 0.004*"Council" + 0.004*"impact"
+2024-05-13 12:40:14,725 - topic diff=0.795965, rho=1.000000
+2024-05-13 12:40:14,725 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1298, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:14.725853', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:15,775 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:15,776 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:15,780 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:15,780 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:15,780 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:15,780 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:15,781 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:15,781 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:15,781 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:15,781 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:15,782 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:15,782 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:17,488 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:17,490 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)
+2024-05-13 12:40:17,490 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-05-13T12:40:17.490566', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:17,491 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:17,491 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:17,491 - using serial LDA version on this node
+2024-05-13 12:40:17,492 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:17,492 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:17,498 - -7.946 per-word bound, 246.5 perplexity estimate based on a held-out corpus of 1 documents with 1970 words
+2024-05-13 12:40:17,498 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:17,500 - topic #0 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"practice" + 0.006*"management" + 0.006*"need" + 0.006*"oversight" + 0.006*"risks" + 0.006*"small" + 0.006*"protection" + 0.006*"number"
+2024-05-13 12:40:17,500 - topic #1 (0.333): 0.015*"’" + 0.008*"number" + 0.007*"planning" + 0.007*"protection" + 0.007*"practice" + 0.005*"well" + 0.005*"Hull" + 0.005*"need" + 0.005*"right" + 0.005*"25"
+2024-05-13 12:40:17,500 - topic #2 (0.333): 0.016*"’" + 0.007*"planning" + 0.007*"number" + 0.006*"Hull" + 0.005*"risks" + 0.005*"need" + 0.005*"25" + 0.005*"protection" + 0.005*"well" + 0.005*"management"
+2024-05-13 12:40:17,500 - topic diff=0.751328, rho=1.000000
+2024-05-13 12:40:17,500 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:17.500922', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:18,492 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:18,492 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:18,493 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:18,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:18,493 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:18,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:18,493 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:18,493 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:18,494 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:18,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:18,494 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:18,494 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:20,206 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:20,209 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)
+2024-05-13 12:40:20,209 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)", 'datetime': '2024-05-13T12:40:20.209736', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:20,210 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:20,211 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:20,211 - using serial LDA version on this node
+2024-05-13 12:40:20,211 - 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
+2024-05-13 12:40:20,211 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:20,215 - -8.059 per-word bound, 266.7 perplexity estimate based on a held-out corpus of 1 documents with 2489 words
+2024-05-13 12:40:20,215 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:20,217 - topic #0 (0.333): 0.013*"’" + 0.007*"quality" + 0.006*"good" + 0.006*"permanence" + 0.006*"practice" + 0.005*"Senior" + 0.005*"plans" + 0.005*"senior" + 0.005*"protection" + 0.005*"well"
+2024-05-13 12:40:20,217 - topic #1 (0.333): 0.010*"’" + 0.007*"practice" + 0.006*"quality" + 0.005*"plans" + 0.005*"protection" + 0.005*"permanence" + 0.005*"well" + 0.005*"training" + 0.004*"good" + 0.004*"Senior"
+2024-05-13 12:40:20,217 - topic #2 (0.333): 0.011*"’" + 0.006*"good" + 0.006*"quality" + 0.006*"practice" + 0.005*"needs" + 0.005*"well" + 0.005*"training" + 0.004*"result" + 0.004*"Senior" + 0.004*"need"
+2024-05-13 12:40:20,217 - topic diff=0.787923, rho=1.000000
+2024-05-13 12:40:20,217 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1142, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:20.217727', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:21,244 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:21,244 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:21,244 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:21,244 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:21,245 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:21,245 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:21,245 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:21,245 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:21,245 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:21,245 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:21,245 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:21,246 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:22,713 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:22,717 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)
+2024-05-13 12:40:22,717 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-05-13T12:40:22.717640', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:22,719 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:22,719 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:22,719 - using serial LDA version on this node
+2024-05-13 12:40:22,720 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:22,720 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:22,727 - -7.830 per-word bound, 227.5 perplexity estimate based on a held-out corpus of 1 documents with 1837 words
+2024-05-13 12:40:22,727 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:22,729 - topic #0 (0.333): 0.010*"’" + 0.008*"progress" + 0.007*"needs" + 0.006*"Knowsley" + 0.005*"plans" + 0.005*"quality" + 0.005*"education" + 0.004*"need" + 0.004*"experiences" + 0.004*"2021"
+2024-05-13 12:40:22,729 - topic #1 (0.333): 0.017*"’" + 0.009*"progress" + 0.008*"quality" + 0.007*"plans" + 0.007*"needs" + 0.006*"Knowsley" + 0.005*"2021" + 0.005*"22" + 0.005*"experiences" + 0.005*"need"
+2024-05-13 12:40:22,730 - topic #2 (0.333): 0.015*"’" + 0.008*"progress" + 0.008*"plans" + 0.007*"needs" + 0.006*"quality" + 0.006*"2021" + 0.006*"place" + 0.005*"Knowsley" + 0.005*"impact" + 0.005*"good"
+2024-05-13 12:40:22,730 - topic diff=0.748823, rho=1.000000
+2024-05-13 12:40:22,730 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=886, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:22.730370', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:23,681 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:23,681 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:23,681 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:23,681 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:23,682 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:23,682 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:23,682 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:23,682 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:23,682 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:23,682 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:23,682 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:23,683 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:25,065 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:25,067 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)
+2024-05-13 12:40:25,068 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-05-13T12:40:25.068073', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:25,069 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:25,069 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:25,069 - using serial LDA version on this node
+2024-05-13 12:40:25,069 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:25,070 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:25,073 - -7.973 per-word bound, 251.2 perplexity estimate based on a held-out corpus of 1 documents with 2263 words
+2024-05-13 12:40:25,073 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:25,075 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"health" + 0.005*"plans" + 0.005*"Lancashire" + 0.005*"need" + 0.005*"supported" + 0.005*"9" + 0.005*"practice"
+2024-05-13 12:40:25,075 - topic #1 (0.333): 0.018*"’" + 0.008*"well" + 0.008*"need" + 0.007*"needs" + 0.006*"Lancashire" + 0.005*"supported" + 0.005*"positive" + 0.005*"practice" + 0.005*"progress" + 0.005*"information"
+2024-05-13 12:40:25,075 - topic #2 (0.333): 0.016*"’" + 0.010*"well" + 0.008*"need" + 0.008*"needs" + 0.007*"Lancashire" + 0.006*"plans" + 0.005*"number" + 0.005*"supported" + 0.005*"health" + 0.005*"positive"
+2024-05-13 12:40:25,075 - topic diff=0.777439, rho=1.000000
+2024-05-13 12:40:25,075 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1048, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:25.075688', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:26,172 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:26,173 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:26,173 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:26,173 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:26,173 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:26,173 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:26,174 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:26,174 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:26,174 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:26,174 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:26,174 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:26,174 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:27,957 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:27,961 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)
+2024-05-13 12:40:27,961 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-05-13T12:40:27.961855', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:27,963 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:27,963 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:27,964 - using serial LDA version on this node
+2024-05-13 12:40:27,964 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:27,965 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:27,985 - -8.012 per-word bound, 258.2 perplexity estimate based on a held-out corpus of 1 documents with 2261 words
+2024-05-13 12:40:27,988 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:27,990 - topic #0 (0.333): 0.019*"’" + 0.007*"needs" + 0.007*"Leeds" + 0.006*"well" + 0.004*"plans" + 0.004*"practice" + 0.004*"ensure" + 0.004*"supported" + 0.004*"risk" + 0.004*"21"
+2024-05-13 12:40:27,994 - topic #1 (0.333): 0.017*"’" + 0.009*"Leeds" + 0.006*"well" + 0.006*"risk" + 0.006*"protection" + 0.005*"needs" + 0.005*"including" + 0.004*"making" + 0.004*"4" + 0.004*"practice"
+2024-05-13 12:40:27,994 - topic #2 (0.333): 0.011*"’" + 0.009*"needs" + 0.006*"Leeds" + 0.005*"well" + 0.005*"risk" + 0.005*"4" + 0.005*"practice" + 0.005*"plans" + 0.004*"ensure" + 0.004*"supported"
+2024-05-13 12:40:27,994 - topic diff=0.774616, rho=1.000000
+2024-05-13 12:40:27,994 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1071, num_topics=3, decay=0.5, chunksize=2000> in 0.03s', 'datetime': '2024-05-13T12:40:27.994812', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:29,035 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:29,035 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:29,035 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:29,036 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:29,036 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:29,036 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:29,036 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:29,037 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:29,037 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:29,037 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:29,038 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:29,038 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:30,820 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:30,822 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)
+2024-05-13 12:40:30,822 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-05-13T12:40:30.822575', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:30,823 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:30,823 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:30,823 - using serial LDA version on this node
+2024-05-13 12:40:30,824 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:30,824 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:30,827 - -7.874 per-word bound, 234.5 perplexity estimate based on a held-out corpus of 1 documents with 1950 words
+2024-05-13 12:40:30,828 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:30,829 - topic #0 (0.333): 0.025*"’" + 0.010*"well" + 0.010*"2021" + 0.008*"needs" + 0.008*"Leicester" + 0.006*"good" + 0.006*"including" + 0.006*"20" + 0.005*"number" + 0.005*"ensure"
+2024-05-13 12:40:30,829 - topic #1 (0.333): 0.015*"’" + 0.008*"Leicester" + 0.007*"2021" + 0.006*"well" + 0.005*"good" + 0.005*"needs" + 0.005*"Council" + 0.005*"ensure" + 0.005*"October" + 0.005*"1"
+2024-05-13 12:40:30,829 - topic #2 (0.333): 0.017*"’" + 0.009*"well" + 0.007*"2021" + 0.007*"Leicester" + 0.007*"ensure" + 0.006*"good" + 0.006*"number" + 0.005*"needs" + 0.005*"1" + 0.005*"September"
+2024-05-13 12:40:30,829 - topic diff=0.785306, rho=1.000000
+2024-05-13 12:40:30,829 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=932, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:30.829952', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:31,867 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:31,867 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:31,867 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:31,868 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:31,868 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:31,868 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:31,868 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:31,868 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:31,868 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:31,868 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:31,869 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:31,869 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:33,906 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:33,909 - built Dictionary<1187 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2587 corpus positions)
+2024-05-13 12:40:33,909 - Dictionary lifecycle event {'msg': "built Dictionary<1187 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2587 corpus positions)", 'datetime': '2024-05-13T12:40:33.909722', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:33,910 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:33,911 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:33,911 - using serial LDA version on this node
+2024-05-13 12:40:33,911 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:33,911 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:33,915 - -8.088 per-word bound, 272.1 perplexity estimate based on a held-out corpus of 1 documents with 2587 words
+2024-05-13 12:40:33,915 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:33,917 - topic #0 (0.333): 0.010*"’" + 0.008*"well" + 0.008*"good" + 0.006*"quality" + 0.006*"needs" + 0.005*"practice" + 0.005*"impact" + 0.005*"effective" + 0.004*"protection" + 0.004*"need"
+2024-05-13 12:40:33,917 - topic #1 (0.333): 0.011*"’" + 0.007*"well" + 0.007*"effective" + 0.006*"good" + 0.006*"practice" + 0.005*"quality" + 0.005*"risk" + 0.005*"education" + 0.005*"needs" + 0.005*"impact"
+2024-05-13 12:40:33,917 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"good" + 0.007*"effective" + 0.006*"quality" + 0.005*"need" + 0.005*"practice" + 0.005*"education" + 0.005*"leaders"
+2024-05-13 12:40:33,918 - topic diff=0.779191, rho=1.000000
+2024-05-13 12:40:33,918 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1187, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:33.918222', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:35,034 - Inspection date 2019-09-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:35,034 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:35,034 - Inspection date 2019-09-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:35,034 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:35,035 - Inspection date 2019-09-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:35,035 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:35,035 - Inspection date 2019-09-23 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:35,035 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:35,035 - Inspection date 2019-09-23 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:35,035 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:35,036 - Inspection date 2019-09-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:35,036 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:36,845 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:36,848 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)
+2024-05-13 12:40:36,848 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-05-13T12:40:36.848498', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:36,849 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:36,849 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:36,850 - using serial LDA version on this node
+2024-05-13 12:40:36,850 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:36,850 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:36,855 - -8.195 per-word bound, 293.0 perplexity estimate based on a held-out corpus of 1 documents with 2927 words
+2024-05-13 12:40:36,855 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:36,856 - topic #0 (0.333): 0.022*"’" + 0.007*"Lincolnshire" + 0.005*"plans" + 0.005*"needs" + 0.005*"well" + 0.005*"progress" + 0.004*"education" + 0.004*"2023" + 0.004*"need" + 0.004*"24"
+2024-05-13 12:40:36,856 - topic #1 (0.333): 0.024*"’" + 0.007*"Lincolnshire" + 0.007*"needs" + 0.006*"well" + 0.005*"progress" + 0.005*"24" + 0.005*"28" + 0.004*"family" + 0.004*"offer" + 0.004*"effective"
+2024-05-13 12:40:36,857 - topic #2 (0.333): 0.017*"’" + 0.008*"Lincolnshire" + 0.008*"needs" + 0.006*"well" + 0.006*"plans" + 0.005*"family" + 0.004*"need" + 0.004*"effective" + 0.004*"number" + 0.004*"working"
+2024-05-13 12:40:36,857 - topic diff=0.788901, rho=1.000000
+2024-05-13 12:40:36,857 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1323, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:36.857293', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:37,859 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:37,859 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:37,860 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:37,860 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:37,860 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:37,860 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:37,860 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:37,860 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:37,861 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:37,861 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:37,861 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:37,861 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:40,101 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:40,104 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
+2024-05-13 12:40:40,104 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-05-13T12:40:40.104333', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:40,105 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:40,105 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:40,105 - using serial LDA version on this node
+2024-05-13 12:40:40,106 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:40,106 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:40,110 - -7.990 per-word bound, 254.3 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
+2024-05-13 12:40:40,110 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:40,111 - topic #0 (0.333): 0.015*"’" + 0.006*"practice" + 0.006*"Liverpool" + 0.006*"needs" + 0.006*"need" + 0.006*"quality" + 0.005*"timely" + 0.005*"always" + 0.004*"protection" + 0.004*"harm"
+2024-05-13 12:40:40,111 - topic #1 (0.333): 0.019*"’" + 0.008*"need" + 0.007*"always" + 0.007*"practice" + 0.007*"needs" + 0.005*"response" + 0.004*"Liverpool" + 0.004*"13" + 0.004*"protection" + 0.004*"quality"
+2024-05-13 12:40:40,112 - topic #2 (0.333): 0.022*"’" + 0.008*"needs" + 0.006*"Liverpool" + 0.006*"always" + 0.006*"quality" + 0.006*"practice" + 0.006*"need" + 0.005*"protection" + 0.004*"timely" + 0.004*"13"
+2024-05-13 12:40:40,112 - topic diff=0.836126, rho=1.000000
+2024-05-13 12:40:40,112 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1134, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:40.112311', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:41,039 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:41,039 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:41,040 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:41,040 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:41,040 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:41,040 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:41,040 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:41,040 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:41,041 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:41,041 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:41,041 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:41,041 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:42,765 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:42,768 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)
+2024-05-13 12:40:42,768 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-05-13T12:40:42.768250', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:42,769 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:42,769 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:42,769 - using serial LDA version on this node
+2024-05-13 12:40:42,770 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:42,770 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:42,774 - -8.098 per-word bound, 274.0 perplexity estimate based on a held-out corpus of 1 documents with 2610 words
+2024-05-13 12:40:42,774 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:42,775 - topic #0 (0.333): 0.019*"’" + 0.008*"needs" + 0.006*"practice" + 0.006*"plans" + 0.005*"progress" + 0.005*"carers" + 0.005*"ensure" + 0.005*"information" + 0.005*"London" + 0.004*"good"
+2024-05-13 12:40:42,775 - topic #1 (0.333): 0.023*"’" + 0.008*"needs" + 0.006*"well" + 0.005*"carers" + 0.005*"good" + 0.005*"information" + 0.005*"plans" + 0.005*"practice" + 0.004*"timely" + 0.004*"Barking"
+2024-05-13 12:40:42,776 - topic #2 (0.333): 0.024*"’" + 0.008*"needs" + 0.007*"good" + 0.006*"plans" + 0.005*"progress" + 0.005*"carers" + 0.005*"well" + 0.004*"10" + 0.004*"Dagenham" + 0.004*"planning"
+2024-05-13 12:40:42,776 - topic diff=0.799363, rho=1.000000
+2024-05-13 12:40:42,776 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1193, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:42.776296', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:43,892 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:43,893 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:43,893 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:43,893 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:43,893 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:43,893 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:43,894 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:43,894 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:43,894 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:43,894 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:43,894 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:43,894 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:45,505 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:45,507 - built Dictionary<978 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1956 corpus positions)
+2024-05-13 12:40:45,508 - Dictionary lifecycle event {'msg': "built Dictionary<978 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1956 corpus positions)", 'datetime': '2024-05-13T12:40:45.508085', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:45,509 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:45,509 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:45,509 - using serial LDA version on this node
+2024-05-13 12:40:45,509 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:45,509 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:45,513 - -7.957 per-word bound, 248.4 perplexity estimate based on a held-out corpus of 1 documents with 1956 words
+2024-05-13 12:40:45,513 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:45,514 - topic #0 (0.333): 0.014*"’" + 0.012*"needs" + 0.010*"good" + 0.009*"well" + 0.008*"need" + 0.006*"clear" + 0.006*"progress" + 0.006*"plans" + 0.005*"ensure" + 0.005*"risk"
+2024-05-13 12:40:45,514 - topic #1 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"good" + 0.008*"need" + 0.005*"quality" + 0.005*"progress" + 0.005*"effective" + 0.005*"plans" + 0.005*"ensure"
+2024-05-13 12:40:45,515 - topic #2 (0.333): 0.012*"’" + 0.010*"good" + 0.008*"well" + 0.007*"progress" + 0.007*"need" + 0.007*"plans" + 0.007*"needs" + 0.006*"ensure" + 0.006*"clear" + 0.005*"risk"
+2024-05-13 12:40:45,515 - topic diff=0.767547, rho=1.000000
+2024-05-13 12:40:45,515 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=978, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:45.515303', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:46,583 - Inspection date 2019-05-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:46,583 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:46,584 - Inspection date 2019-05-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:46,584 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:46,584 - Inspection date 2019-05-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:46,585 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:46,585 - Inspection date 2019-05-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:46,585 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:46,585 - Inspection date 2019-05-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:46,585 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:46,586 - Inspection date 2019-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:46,586 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:48,254 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:48,257 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)
+2024-05-13 12:40:48,257 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-05-13T12:40:48.257691', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:48,258 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:48,259 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:48,259 - using serial LDA version on this node
+2024-05-13 12:40:48,259 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:48,259 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:48,263 - -8.100 per-word bound, 274.5 perplexity estimate based on a held-out corpus of 1 documents with 2563 words
+2024-05-13 12:40:48,263 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:48,265 - topic #0 (0.333): 0.017*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"Bexley" + 0.005*"make" + 0.005*"effective" + 0.005*"need" + 0.004*"plans" + 0.004*"including" + 0.004*"progress"
+2024-05-13 12:40:48,265 - topic #1 (0.333): 0.020*"’" + 0.008*"needs" + 0.005*"10" + 0.005*"effective" + 0.005*"well" + 0.005*"Bexley" + 0.004*"2023" + 0.004*"practice" + 0.004*"need" + 0.004*"plans"
+2024-05-13 12:40:48,265 - topic #2 (0.333): 0.021*"’" + 0.007*"well" + 0.007*"need" + 0.007*"plans" + 0.006*"effective" + 0.005*"Bexley" + 0.005*"needs" + 0.005*"6" + 0.004*"practice" + 0.004*"clear"
+2024-05-13 12:40:48,265 - topic diff=0.778256, rho=1.000000
+2024-05-13 12:40:48,265 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1190, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:48.265930', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:49,603 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:49,605 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:49,606 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:49,606 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:49,608 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:49,612 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:49,612 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:49,612 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:49,613 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:49,613 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:49,613 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:49,614 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:51,202 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:51,204 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)
+2024-05-13 12:40:51,204 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-05-13T12:40:51.204967', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:51,206 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:51,206 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:51,206 - using serial LDA version on this node
+2024-05-13 12:40:51,206 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:51,206 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:51,210 - -7.926 per-word bound, 243.1 perplexity estimate based on a held-out corpus of 1 documents with 2371 words
+2024-05-13 12:40:51,210 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:51,211 - topic #0 (0.333): 0.020*"’" + 0.009*"leaders" + 0.008*"well" + 0.007*"plans" + 0.007*"progress" + 0.006*"quality" + 0.006*"good" + 0.005*"needs" + 0.005*"senior" + 0.005*"However"
+2024-05-13 12:40:51,212 - topic #1 (0.333): 0.014*"’" + 0.009*"well" + 0.006*"plans" + 0.006*"leaders" + 0.006*"Brent" + 0.005*"progress" + 0.005*"timely" + 0.005*"practice" + 0.005*"information" + 0.005*"good"
+2024-05-13 12:40:51,212 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.006*"number" + 0.006*"plans" + 0.006*"progress" + 0.006*"good" + 0.006*"leaders" + 0.006*"quality" + 0.005*"senior" + 0.005*"Brent"
+2024-05-13 12:40:51,212 - topic diff=0.820560, rho=1.000000
+2024-05-13 12:40:51,212 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:51.212472', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:52,157 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:52,158 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:52,158 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:52,158 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:52,158 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:52,158 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:52,158 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:52,159 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:52,159 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:52,159 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:52,159 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:52,159 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:53,981 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:53,985 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)
+2024-05-13 12:40:53,985 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-05-13T12:40:53.985330', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:53,987 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:53,987 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:53,988 - using serial LDA version on this node
+2024-05-13 12:40:53,988 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:53,988 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:53,993 - -8.181 per-word bound, 290.2 perplexity estimate based on a held-out corpus of 1 documents with 2640 words
+2024-05-13 12:40:53,993 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:53,994 - topic #0 (0.333): 0.021*"’" + 0.008*"Bromley" + 0.006*"well" + 0.005*"education" + 0.005*"needs" + 0.005*"health" + 0.004*"plans" + 0.004*"practice" + 0.004*"leaders" + 0.004*"relationships"
+2024-05-13 12:40:53,995 - topic #1 (0.333): 0.023*"’" + 0.010*"Bromley" + 0.009*"needs" + 0.007*"well" + 0.006*"leaders" + 0.006*"plans" + 0.005*"health" + 0.005*"practice" + 0.005*"education" + 0.005*"17"
+2024-05-13 12:40:53,995 - topic #2 (0.333): 0.014*"’" + 0.008*"Bromley" + 0.007*"well" + 0.006*"needs" + 0.006*"practice" + 0.005*"plans" + 0.005*"progress" + 0.004*"leaders" + 0.004*"training" + 0.004*"13"
+2024-05-13 12:40:53,995 - topic diff=0.768135, rho=1.000000
+2024-05-13 12:40:53,995 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1266, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:53.995536', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:55,194 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:55,197 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:55,197 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:55,198 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:55,198 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:55,198 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:55,199 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:55,199 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:55,199 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:55,199 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:55,200 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:55,200 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:56,717 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:56,721 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)
+2024-05-13 12:40:56,721 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-05-13T12:40:56.721593', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:56,723 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:56,723 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:56,723 - using serial LDA version on this node
+2024-05-13 12:40:56,724 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:56,724 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:56,730 - -8.060 per-word bound, 266.8 perplexity estimate based on a held-out corpus of 1 documents with 1735 words
+2024-05-13 12:40:56,730 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:56,732 - topic #0 (0.333): 0.010*"’" + 0.008*"Camden" + 0.005*"protection" + 0.005*"leaders" + 0.005*"well" + 0.005*"2022" + 0.005*"practice" + 0.004*"appropriate" + 0.004*"29" + 0.004*"response"
+2024-05-13 12:40:56,732 - topic #1 (0.333): 0.009*"’" + 0.007*"Camden" + 0.005*"leaders" + 0.005*"practice" + 0.004*"well" + 0.004*"protection" + 0.004*"appropriate" + 0.004*"needs" + 0.004*"health" + 0.003*"April"
+2024-05-13 12:40:56,732 - topic #2 (0.333): 0.012*"’" + 0.008*"leaders" + 0.007*"practice" + 0.007*"Camden" + 0.006*"needs" + 0.006*"well" + 0.005*"response" + 0.005*"protection" + 0.005*"25" + 0.005*"29"
+2024-05-13 12:40:56,733 - topic diff=0.714940, rho=1.000000
+2024-05-13 12:40:56,733 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=993, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:56.733193', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:57,778 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:40:57,779 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:57,779 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:40:57,779 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:57,779 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:40:57,779 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:57,780 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:40:57,780 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:57,780 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:40:57,780 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:57,780 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:40:57,780 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:40:59,462 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:40:59,464 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)
+2024-05-13 12:40:59,465 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-05-13T12:40:59.465100', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:40:59,466 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:40:59,466 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:40:59,466 - using serial LDA version on this node
+2024-05-13 12:40:59,466 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:40:59,467 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:40:59,470 - -7.985 per-word bound, 253.3 perplexity estimate based on a held-out corpus of 1 documents with 2209 words
+2024-05-13 12:40:59,470 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:40:59,471 - topic #0 (0.333): 0.010*"’" + 0.006*"needs" + 0.006*"Croydon" + 0.006*"well" + 0.005*"good" + 0.005*"Senior" + 0.005*"ensure" + 0.005*"need" + 0.005*"quality" + 0.005*"plans"
+2024-05-13 12:40:59,472 - topic #1 (0.333): 0.014*"’" + 0.010*"well" + 0.009*"needs" + 0.007*"Senior" + 0.006*"Croydon" + 0.006*"quality" + 0.006*"health" + 0.005*"need" + 0.005*"education" + 0.005*"effective"
+2024-05-13 12:40:59,472 - topic #2 (0.333): 0.011*"’" + 0.006*"needs" + 0.005*"ensure" + 0.005*"need" + 0.005*"well" + 0.005*"quality" + 0.004*"Croydon" + 0.004*"arrangements" + 0.004*"However" + 0.004*"health"
+2024-05-13 12:40:59,472 - topic diff=0.776042, rho=1.000000
+2024-05-13 12:40:59,472 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1046, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:40:59.472598', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:01,014 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:01,015 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:01,015 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:01,015 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:01,015 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:01,015 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:01,016 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:01,016 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:01,016 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:01,016 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:01,016 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:01,016 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:02,427 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:02,430 - built Dictionary<1012 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2046 corpus positions)
+2024-05-13 12:41:02,430 - Dictionary lifecycle event {'msg': "built Dictionary<1012 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2046 corpus positions)", 'datetime': '2024-05-13T12:41:02.430220', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:02,431 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:02,431 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:02,431 - using serial LDA version on this node
+2024-05-13 12:41:02,432 - 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
+2024-05-13 12:41:02,432 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:02,435 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2046 words
+2024-05-13 12:41:02,435 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:02,437 - topic #0 (0.333): 0.011*"’" + 0.009*"quality" + 0.008*"needs" + 0.006*"good" + 0.005*"plans" + 0.005*"management" + 0.005*"progress" + 0.004*"risk" + 0.004*"well" + 0.004*"experiences"
+2024-05-13 12:41:02,437 - topic #1 (0.333): 0.013*"’" + 0.010*"quality" + 0.007*"good" + 0.006*"needs" + 0.005*"risk" + 0.005*"progress" + 0.005*"plans" + 0.005*"experiences" + 0.005*"well" + 0.004*"provide"
+2024-05-13 12:41:02,437 - topic #2 (0.333): 0.009*"quality" + 0.008*"’" + 0.007*"needs" + 0.006*"good" + 0.004*"progress" + 0.004*"plans" + 0.004*"fully" + 0.004*"always" + 0.004*"family" + 0.004*"appropriately"
+2024-05-13 12:41:02,437 - topic diff=0.757534, rho=1.000000
+2024-05-13 12:41:02,437 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1012, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:02.437801', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:03,661 - Inspection date 2019-11-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:03,662 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:03,662 - Inspection date 2019-11-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:03,662 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:03,662 - Inspection date 2019-11-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:03,663 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:03,663 - Inspection date 2019-11-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:03,663 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:03,663 - Inspection date 2019-11-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:03,663 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:03,663 - Inspection date 2019-11-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:03,663 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:04,968 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:04,970 - built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)
+2024-05-13 12:41:04,971 - Dictionary lifecycle event {'msg': "built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)", 'datetime': '2024-05-13T12:41:04.971052', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:04,972 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:04,972 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:04,972 - using serial LDA version on this node
+2024-05-13 12:41:04,972 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:04,972 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:04,976 - -7.941 per-word bound, 245.8 perplexity estimate based on a held-out corpus of 1 documents with 2104 words
+2024-05-13 12:41:04,976 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:04,977 - topic #0 (0.333): 0.010*"’" + 0.008*"good" + 0.008*"needs" + 0.007*"ensure" + 0.007*"timely" + 0.007*"practice" + 0.006*"Enfield" + 0.006*"effective" + 0.006*"clear" + 0.006*"quality"
+2024-05-13 12:41:04,977 - topic #1 (0.333): 0.013*"’" + 0.009*"leaders" + 0.007*"needs" + 0.007*"practice" + 0.007*"ensure" + 0.006*"timely" + 0.006*"Enfield" + 0.006*"good" + 0.006*"clear" + 0.005*"quality"
+2024-05-13 12:41:04,978 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.008*"practice" + 0.008*"ensure" + 0.008*"effective" + 0.008*"good" + 0.007*"clear" + 0.006*"quality" + 0.006*"Enfield" + 0.006*"improve"
+2024-05-13 12:41:04,978 - topic diff=0.777545, rho=1.000000
+2024-05-13 12:41:04,978 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=999, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:04.978446', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:06,176 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:06,181 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:06,181 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:06,181 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:06,181 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:06,182 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:06,182 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:06,182 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:06,182 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:06,183 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:06,183 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:06,183 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:07,605 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:07,607 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1898 corpus positions)
+2024-05-13 12:41:07,608 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1898 corpus positions)", 'datetime': '2024-05-13T12:41:07.608026', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:07,608 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:07,609 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:07,609 - using serial LDA version on this node
+2024-05-13 12:41:07,609 - 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
+2024-05-13 12:41:07,609 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:07,613 - -7.916 per-word bound, 241.4 perplexity estimate based on a held-out corpus of 1 documents with 1898 words
+2024-05-13 12:41:07,613 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:07,614 - topic #0 (0.333): 0.013*"’" + 0.008*"well" + 0.007*"good" + 0.006*"needs" + 0.006*"need" + 0.006*"range" + 0.006*"progress" + 0.005*"quality" + 0.005*"plans" + 0.004*"information"
+2024-05-13 12:41:07,614 - topic #1 (0.333): 0.010*"’" + 0.008*"good" + 0.007*"needs" + 0.007*"well" + 0.005*"plans" + 0.005*"risk" + 0.005*"ensure" + 0.004*"effective" + 0.004*"need" + 0.004*"timely"
+2024-05-13 12:41:07,614 - topic #2 (0.333): 0.013*"’" + 0.012*"well" + 0.011*"plans" + 0.008*"good" + 0.008*"needs" + 0.007*"need" + 0.007*"range" + 0.006*"ensure" + 0.005*"consistently" + 0.005*"development"
+2024-05-13 12:41:07,615 - topic diff=0.752809, rho=1.000000
+2024-05-13 12:41:07,615 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=945, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:07.615165', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:08,798 - Inspection date 2019-12-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:08,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:08,799 - Inspection date 2019-12-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:08,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:08,799 - Inspection date 2019-12-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:08,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:08,800 - Inspection date 2019-12-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:08,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:08,800 - Inspection date 2019-12-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:08,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:08,800 - Inspection date 2019-12-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:08,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:10,599 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:10,603 - built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)
+2024-05-13 12:41:10,603 - Dictionary lifecycle event {'msg': "built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)", 'datetime': '2024-05-13T12:41:10.603849', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:10,605 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:10,605 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:10,606 - using serial LDA version on this node
+2024-05-13 12:41:10,606 - 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
+2024-05-13 12:41:10,607 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:10,614 - -7.998 per-word bound, 255.6 perplexity estimate based on a held-out corpus of 1 documents with 2603 words
+2024-05-13 12:41:10,614 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:10,616 - topic #0 (0.333): 0.010*"’" + 0.009*"practice" + 0.006*"number" + 0.006*"plans" + 0.006*"quality" + 0.006*"needs" + 0.005*"However" + 0.005*"effective" + 0.005*"making" + 0.005*"small"
+2024-05-13 12:41:10,616 - topic #1 (0.333): 0.014*"’" + 0.011*"practice" + 0.006*"number" + 0.006*"need" + 0.006*"planning" + 0.006*"within" + 0.006*"needs" + 0.006*"quality" + 0.006*"plans" + 0.005*"effective"
+2024-05-13 12:41:10,617 - topic #2 (0.333): 0.014*"’" + 0.009*"practice" + 0.007*"planning" + 0.006*"number" + 0.006*"within" + 0.006*"effective" + 0.006*"small" + 0.006*"leaders" + 0.005*"including" + 0.005*"oversight"
+2024-05-13 12:41:10,617 - topic diff=0.840399, rho=1.000000
+2024-05-13 12:41:10,617 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1122, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:10.617369', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:12,144 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:12,144 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:12,145 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:12,145 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:12,145 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:12,145 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:12,146 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:12,146 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:12,146 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:12,146 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:12,147 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:12,147 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:13,474 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:13,476 - built Dictionary<885 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1806 corpus positions)
+2024-05-13 12:41:13,476 - Dictionary lifecycle event {'msg': "built Dictionary<885 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1806 corpus positions)", 'datetime': '2024-05-13T12:41:13.476301', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:13,477 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:13,477 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:13,477 - using serial LDA version on this node
+2024-05-13 12:41:13,477 - 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
+2024-05-13 12:41:13,478 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:13,481 - -7.843 per-word bound, 229.6 perplexity estimate based on a held-out corpus of 1 documents with 1806 words
+2024-05-13 12:41:13,481 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:13,482 - topic #0 (0.333): 0.013*"’" + 0.010*"effective" + 0.009*"needs" + 0.007*"well" + 0.007*"good" + 0.006*"timely" + 0.006*"education" + 0.005*"arrangements" + 0.005*"improve" + 0.005*"leaders"
+2024-05-13 12:41:13,482 - topic #1 (0.333): 0.009*"’" + 0.009*"well" + 0.009*"needs" + 0.007*"appropriate" + 0.007*"effective" + 0.005*"good" + 0.005*"arrangements" + 0.005*"risk" + 0.004*"shared" + 0.004*"need"
+2024-05-13 12:41:13,482 - topic #2 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"well" + 0.007*"appropriate" + 0.007*"effective" + 0.007*"ensure" + 0.006*"good" + 0.005*"leaders" + 0.005*"arrangements" + 0.005*"experiences"
+2024-05-13 12:41:13,482 - topic diff=0.753017, rho=1.000000
+2024-05-13 12:41:13,483 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=885, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:13.483119', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:14,700 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:14,701 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:14,701 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:14,701 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:14,701 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:14,701 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:14,701 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:14,701 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:14,702 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:14,702 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:14,702 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:14,702 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:16,277 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:16,281 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)
+2024-05-13 12:41:16,281 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-05-13T12:41:16.281836', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:16,283 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:16,283 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:16,283 - using serial LDA version on this node
+2024-05-13 12:41:16,283 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:16,284 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:16,289 - -8.171 per-word bound, 288.1 perplexity estimate based on a held-out corpus of 1 documents with 2620 words
+2024-05-13 12:41:16,289 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:16,290 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.007*"plans" + 0.006*"Haringey" + 0.006*"good" + 0.005*"need" + 0.005*"well" + 0.005*"risk" + 0.005*"education" + 0.004*"impact"
+2024-05-13 12:41:16,291 - topic #1 (0.333): 0.016*"’" + 0.011*"Haringey" + 0.010*"needs" + 0.007*"plans" + 0.006*"progress" + 0.006*"well" + 0.005*"need" + 0.004*"good" + 0.004*"supported" + 0.004*"risk"
+2024-05-13 12:41:16,291 - topic #2 (0.333): 0.013*"’" + 0.007*"Haringey" + 0.007*"well" + 0.006*"plans" + 0.005*"good" + 0.005*"needs" + 0.004*"24" + 0.004*"education" + 0.004*"training" + 0.004*"need"
+2024-05-13 12:41:16,291 - topic diff=0.774351, rho=1.000000
+2024-05-13 12:41:16,291 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1252, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:16.291471', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:17,413 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:17,414 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:17,414 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:17,414 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:17,414 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:17,415 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:17,415 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:17,415 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:17,415 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:17,416 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:17,417 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:17,417 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:18,912 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:18,914 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)
+2024-05-13 12:41:18,914 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-05-13T12:41:18.914753', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:18,916 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:18,916 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:18,916 - using serial LDA version on this node
+2024-05-13 12:41:18,916 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:18,917 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:18,921 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 1732 words
+2024-05-13 12:41:18,921 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:18,923 - topic #0 (0.333): 0.010*"’" + 0.008*"well" + 0.007*"good" + 0.006*"needs" + 0.006*"impact" + 0.005*"Harrow" + 0.005*"plans" + 0.005*"experiences" + 0.004*"need" + 0.004*"school"
+2024-05-13 12:41:18,923 - topic #1 (0.333): 0.014*"’" + 0.013*"good" + 0.009*"needs" + 0.009*"well" + 0.006*"early" + 0.006*"plans" + 0.006*"protection" + 0.006*"practice" + 0.005*"need" + 0.005*"impact"
+2024-05-13 12:41:18,923 - topic #2 (0.333): 0.010*"good" + 0.009*"’" + 0.008*"well" + 0.007*"needs" + 0.005*"planning" + 0.005*"practice" + 0.005*"impact" + 0.005*"need" + 0.005*"plans" + 0.005*"protection"
+2024-05-13 12:41:18,923 - topic diff=0.708652, rho=1.000000
+2024-05-13 12:41:18,923 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=942, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:18.923762', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:20,994 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:20,995 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:20,995 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:20,995 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:20,995 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:20,995 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:20,996 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:20,996 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:20,996 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:20,996 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:20,996 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:20,996 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:22,475 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:22,478 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)
+2024-05-13 12:41:22,478 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-05-13T12:41:22.478329', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:22,479 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:22,479 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:22,479 - using serial LDA version on this node
+2024-05-13 12:41:22,480 - 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
+2024-05-13 12:41:22,480 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:22,483 - -8.009 per-word bound, 257.6 perplexity estimate based on a held-out corpus of 1 documents with 2243 words
+2024-05-13 12:41:22,483 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:22,485 - topic #0 (0.333): 0.017*"’" + 0.012*"Havering" + 0.008*"quality" + 0.007*"plans" + 0.006*"effective" + 0.006*"oversight" + 0.005*"11" + 0.005*"well" + 0.004*"December" + 0.004*"many"
+2024-05-13 12:41:22,485 - topic #1 (0.333): 0.020*"’" + 0.010*"Havering" + 0.010*"quality" + 0.007*"plans" + 0.005*"needs" + 0.005*"oversight" + 0.004*"11" + 0.004*"progress" + 0.004*"22" + 0.004*"practice"
+2024-05-13 12:41:22,485 - topic #2 (0.333): 0.016*"’" + 0.011*"Havering" + 0.008*"quality" + 0.007*"plans" + 0.005*"effective" + 0.005*"oversight" + 0.005*"needs" + 0.004*"practice" + 0.004*"22" + 0.004*"leaders"
+2024-05-13 12:41:22,485 - topic diff=0.765724, rho=1.000000
+2024-05-13 12:41:22,485 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:22.485907', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:23,716 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:23,717 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:23,717 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:23,717 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:23,717 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:23,717 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:23,717 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:23,717 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:23,718 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:23,718 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:23,718 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:23,718 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:25,549 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:25,551 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)
+2024-05-13 12:41:25,552 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-05-13T12:41:25.552022', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:25,553 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:25,553 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:25,553 - using serial LDA version on this node
+2024-05-13 12:41:25,553 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:25,554 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:25,557 - -8.075 per-word bound, 269.7 perplexity estimate based on a held-out corpus of 1 documents with 2511 words
+2024-05-13 12:41:25,557 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:25,559 - topic #0 (0.333): 0.019*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"Hillingdon" + 0.006*"plans" + 0.005*"need" + 0.004*"team" + 0.004*"family" + 0.004*"leaders" + 0.003*"6"
+2024-05-13 12:41:25,559 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.007*"Hillingdon" + 0.006*"plans" + 0.006*"well" + 0.005*"team" + 0.004*"6" + 0.004*"need" + 0.004*"leaders" + 0.004*"good"
+2024-05-13 12:41:25,559 - topic #2 (0.333): 0.016*"’" + 0.010*"needs" + 0.009*"plans" + 0.008*"well" + 0.008*"Hillingdon" + 0.006*"2" + 0.005*"team" + 0.005*"2023" + 0.004*"need" + 0.004*"PAs"
+2024-05-13 12:41:25,559 - topic diff=0.801202, rho=1.000000
+2024-05-13 12:41:25,559 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1161, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:25.559952', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:26,590 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:26,591 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:26,591 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:26,591 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:26,591 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:26,591 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:26,591 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:26,591 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:26,591 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:26,592 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:26,592 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:26,592 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:28,702 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:28,705 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)
+2024-05-13 12:41:28,706 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-05-13T12:41:28.706230', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:28,708 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:28,708 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:28,708 - using serial LDA version on this node
+2024-05-13 12:41:28,709 - 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
+2024-05-13 12:41:28,709 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:28,715 - -8.007 per-word bound, 257.3 perplexity estimate based on a held-out corpus of 1 documents with 2271 words
+2024-05-13 12:41:28,715 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:28,717 - topic #0 (0.333): 0.024*"’" + 0.011*"needs" + 0.009*"well" + 0.007*"Hounslow" + 0.007*"effective" + 0.007*"timely" + 0.005*"plans" + 0.005*"16" + 0.005*"progress" + 0.004*"October"
+2024-05-13 12:41:28,717 - topic #1 (0.333): 0.019*"’" + 0.010*"well" + 0.009*"needs" + 0.008*"effective" + 0.007*"Hounslow" + 0.005*"plans" + 0.005*"timely" + 0.005*"training" + 0.005*"oversight" + 0.005*"experiences"
+2024-05-13 12:41:28,717 - topic #2 (0.333): 0.016*"’" + 0.012*"needs" + 0.011*"well" + 0.006*"effective" + 0.006*"Hounslow" + 0.006*"timely" + 0.005*"plans" + 0.005*"20" + 0.004*"experiences" + 0.004*"strong"
+2024-05-13 12:41:28,718 - topic diff=0.779475, rho=1.000000
+2024-05-13 12:41:28,718 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1070, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:28.718343', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:29,859 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:29,860 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:29,860 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:29,860 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:29,860 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:29,860 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:29,860 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:29,861 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:29,861 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:29,861 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:29,861 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:29,861 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:31,294 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:31,296 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)
+2024-05-13 12:41:31,296 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-05-13T12:41:31.296575', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:31,297 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:31,297 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:31,297 - using serial LDA version on this node
+2024-05-13 12:41:31,298 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:31,298 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:31,301 - -7.927 per-word bound, 243.4 perplexity estimate based on a held-out corpus of 1 documents with 1982 words
+2024-05-13 12:41:31,301 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:31,303 - topic #0 (0.333): 0.009*"well" + 0.008*"needs" + 0.008*"’" + 0.007*"plans" + 0.005*"good" + 0.005*"highly" + 0.005*"quality" + 0.004*"leaders" + 0.004*"practice" + 0.004*"Islington"
+2024-05-13 12:41:31,303 - topic #1 (0.333): 0.013*"’" + 0.012*"needs" + 0.008*"well" + 0.006*"highly" + 0.006*"leaders" + 0.006*"effective" + 0.006*"quality" + 0.006*"good" + 0.005*"Islington" + 0.005*"plans"
+2024-05-13 12:41:31,303 - topic #2 (0.333): 0.015*"’" + 0.012*"well" + 0.011*"needs" + 0.007*"plans" + 0.006*"good" + 0.006*"highly" + 0.005*"quality" + 0.005*"effective" + 0.005*"risk" + 0.005*"Islington"
+2024-05-13 12:41:31,303 - topic diff=0.748875, rho=1.000000
+2024-05-13 12:41:31,303 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:31.303714', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:33,219 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:33,219 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:33,220 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:33,220 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:33,220 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:33,220 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:33,220 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:33,220 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:33,220 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:33,221 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:33,221 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:33,221 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:34,808 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:34,812 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)
+2024-05-13 12:41:34,812 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-05-13T12:41:34.812797', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:34,814 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:34,814 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:34,815 - using serial LDA version on this node
+2024-05-13 12:41:34,815 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:34,815 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:34,822 - -7.908 per-word bound, 240.1 perplexity estimate based on a held-out corpus of 1 documents with 2090 words
+2024-05-13 12:41:34,822 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:34,824 - topic #0 (0.333): 0.012*"’" + 0.007*"good" + 0.007*"plans" + 0.007*"well" + 0.007*"progress" + 0.006*"needs" + 0.006*"need" + 0.006*"leaders" + 0.005*"Lambeth" + 0.005*"impact"
+2024-05-13 12:41:34,824 - topic #1 (0.333): 0.014*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"plans" + 0.006*"good" + 0.006*"Lambeth" + 0.005*"need" + 0.005*"4" + 0.005*"progress" + 0.005*"impact"
+2024-05-13 12:41:34,825 - topic #2 (0.333): 0.018*"’" + 0.012*"needs" + 0.009*"well" + 0.008*"plans" + 0.007*"Lambeth" + 0.007*"good" + 0.006*"impact" + 0.006*"need" + 0.005*"progress" + 0.005*"2022"
+2024-05-13 12:41:34,825 - topic diff=0.802016, rho=1.000000
+2024-05-13 12:41:34,825 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:34.825627', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:35,954 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:35,954 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:35,954 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:35,954 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:35,955 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:35,955 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:35,955 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:35,955 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:35,955 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:35,955 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:35,955 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:35,956 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:37,354 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:37,356 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)
+2024-05-13 12:41:37,356 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-05-13T12:41:37.356789', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:37,357 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:37,358 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:37,358 - using serial LDA version on this node
+2024-05-13 12:41:37,358 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:37,358 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:37,362 - -8.048 per-word bound, 264.7 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
+2024-05-13 12:41:37,362 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:37,364 - topic #0 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"plans" + 0.005*"needs" + 0.005*"effective" + 0.004*"good" + 0.004*"receive" + 0.004*"leaders" + 0.004*"practice" + 0.004*"appropriate"
+2024-05-13 12:41:37,364 - topic #1 (0.333): 0.017*"’" + 0.008*"well" + 0.006*"plans" + 0.005*"needs" + 0.005*"progress" + 0.005*"effective" + 0.004*"leaders" + 0.004*"good" + 0.004*"15" + 0.004*"4"
+2024-05-13 12:41:37,364 - topic #2 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"Lewisham" + 0.007*"plans" + 0.007*"effective" + 0.006*"progress" + 0.006*"4" + 0.005*"good" + 0.005*"arrangements"
+2024-05-13 12:41:37,364 - topic diff=0.800088, rho=1.000000
+2024-05-13 12:41:37,364 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:37.364858', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:38,370 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:38,370 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:38,370 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:38,371 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:38,371 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:38,371 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:38,371 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:38,372 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:38,372 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:38,372 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:38,372 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:38,372 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:40,093 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:40,098 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)
+2024-05-13 12:41:40,098 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-05-13T12:41:40.098861', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:40,100 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:40,100 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:40,101 - using serial LDA version on this node
+2024-05-13 12:41:40,101 - 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
+2024-05-13 12:41:40,102 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:40,109 - -7.988 per-word bound, 253.9 perplexity estimate based on a held-out corpus of 1 documents with 2032 words
+2024-05-13 12:41:40,109 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:40,111 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.006*"Merton" + 0.005*"needs" + 0.005*"helping" + 0.004*"good" + 0.004*"February" + 0.004*"progress" + 0.004*"2022" + 0.004*"health"
+2024-05-13 12:41:40,112 - topic #1 (0.333): 0.017*"’" + 0.009*"well" + 0.006*"Merton" + 0.006*"needs" + 0.005*"plans" + 0.004*"ensure" + 0.004*"family" + 0.004*"access" + 0.004*"good" + 0.004*"progress"
+2024-05-13 12:41:40,112 - topic #2 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"Merton" + 0.006*"needs" + 0.005*"plans" + 0.005*"progress" + 0.005*"4" + 0.005*"family" + 0.004*"information" + 0.004*"28"
+2024-05-13 12:41:40,112 - topic diff=0.751848, rho=1.000000
+2024-05-13 12:41:40,112 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1015, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:40.112850', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:40,998 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:40,998 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:40,998 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:40,998 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:40,998 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:40,998 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:40,999 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:40,999 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:40,999 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:40,999 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:40,999 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:40,999 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:42,835 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:42,838 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)
+2024-05-13 12:41:42,838 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-05-13T12:41:42.838594', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:42,839 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:42,839 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:42,840 - using serial LDA version on this node
+2024-05-13 12:41:42,840 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:42,840 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:42,844 - -8.063 per-word bound, 267.4 perplexity estimate based on a held-out corpus of 1 documents with 2540 words
+2024-05-13 12:41:42,844 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:42,846 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.008*"Newham" + 0.006*"plans" + 0.006*"progress" + 0.006*"practice" + 0.005*"need" + 0.005*"effective" + 0.004*"good" + 0.004*"planning"
+2024-05-13 12:41:42,846 - topic #1 (0.333): 0.021*"’" + 0.008*"needs" + 0.007*"Newham" + 0.006*"practice" + 0.006*"plans" + 0.006*"effective" + 0.005*"good" + 0.005*"need" + 0.005*"progress" + 0.005*"Leaders"
+2024-05-13 12:41:42,846 - topic #2 (0.333): 0.021*"’" + 0.007*"needs" + 0.007*"progress" + 0.007*"need" + 0.006*"effective" + 0.006*"practice" + 0.005*"plans" + 0.005*"Newham" + 0.005*"good" + 0.004*"receive"
+2024-05-13 12:41:42,846 - topic diff=0.776103, rho=1.000000
+2024-05-13 12:41:42,846 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1153, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:42.846762', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:43,798 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:43,798 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:43,799 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:43,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:43,799 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:43,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:43,799 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:43,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:43,800 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:43,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:43,800 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:43,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:45,944 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:45,946 - built Dictionary<1149 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2458 corpus positions)
+2024-05-13 12:41:45,946 - Dictionary lifecycle event {'msg': "built Dictionary<1149 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2458 corpus positions)", 'datetime': '2024-05-13T12:41:45.946623', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:45,947 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:45,947 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:45,948 - using serial LDA version on this node
+2024-05-13 12:41:45,948 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:45,948 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:45,952 - -8.073 per-word bound, 269.3 perplexity estimate based on a held-out corpus of 1 documents with 2458 words
+2024-05-13 12:41:45,952 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:45,954 - topic #0 (0.333): 0.008*"well" + 0.007*"’" + 0.007*"practice" + 0.006*"effective" + 0.006*"strong" + 0.006*"needs" + 0.005*"need" + 0.005*"Redbridge" + 0.005*"progress" + 0.005*"risk"
+2024-05-13 12:41:45,954 - topic #1 (0.333): 0.008*"’" + 0.007*"practice" + 0.006*"needs" + 0.006*"need" + 0.005*"well" + 0.005*"Redbridge" + 0.005*"team" + 0.005*"including" + 0.005*"strong" + 0.005*"effective"
+2024-05-13 12:41:45,954 - topic #2 (0.333): 0.007*"’" + 0.006*"practice" + 0.005*"needs" + 0.005*"need" + 0.005*"well" + 0.005*"risk" + 0.005*"Redbridge" + 0.005*"ensure" + 0.004*"effective" + 0.004*"strong"
+2024-05-13 12:41:45,954 - topic diff=0.765949, rho=1.000000
+2024-05-13 12:41:45,954 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1149, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:45.954726', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:46,938 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:46,938 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:46,939 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:46,939 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:46,939 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:46,939 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:46,939 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:46,939 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:46,940 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:46,940 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:46,940 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:46,940 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:48,258 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:48,261 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)
+2024-05-13 12:41:48,261 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-05-13T12:41:48.261256', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:48,262 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:48,262 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:48,263 - using serial LDA version on this node
+2024-05-13 12:41:48,263 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:48,263 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:48,266 - -7.983 per-word bound, 253.0 perplexity estimate based on a held-out corpus of 1 documents with 1818 words
+2024-05-13 12:41:48,266 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:48,268 - topic #0 (0.333): 0.018*"’" + 0.011*"well" + 0.008*"Richmond" + 0.007*"supported" + 0.007*"needs" + 0.006*"good" + 0.005*"team" + 0.005*"need" + 0.005*"ensure" + 0.004*"4"
+2024-05-13 12:41:48,268 - topic #1 (0.333): 0.010*"’" + 0.008*"well" + 0.007*"Richmond" + 0.006*"needs" + 0.005*"need" + 0.005*"team" + 0.005*"supported" + 0.004*"2022" + 0.004*"4" + 0.004*"range"
+2024-05-13 12:41:48,268 - topic #2 (0.333): 0.016*"’" + 0.013*"well" + 0.008*"needs" + 0.008*"Richmond" + 0.006*"good" + 0.006*"team" + 0.006*"need" + 0.005*"supported" + 0.005*"additional" + 0.005*"strong"
+2024-05-13 12:41:48,268 - topic diff=0.731289, rho=1.000000
+2024-05-13 12:41:48,268 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=968, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:48.268874', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:49,391 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:49,391 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:49,391 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:49,392 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:49,392 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:49,392 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:49,392 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:49,392 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:49,392 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:49,392 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:49,393 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:49,393 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:50,886 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:50,895 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)
+2024-05-13 12:41:50,896 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-05-13T12:41:50.896064', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:50,897 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:50,901 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:50,901 - using serial LDA version on this node
+2024-05-13 12:41:50,902 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:50,902 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:50,907 - -7.929 per-word bound, 243.7 perplexity estimate based on a held-out corpus of 1 documents with 1878 words
+2024-05-13 12:41:50,908 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:50,910 - topic #0 (0.333): 0.020*"’" + 0.010*"Southwark" + 0.008*"well" + 0.007*"good" + 0.007*"needs" + 0.006*"need" + 0.006*"Leaders" + 0.006*"plans" + 0.005*"leaders" + 0.005*"progress"
+2024-05-13 12:41:50,910 - topic #1 (0.333): 0.014*"’" + 0.009*"good" + 0.009*"Southwark" + 0.007*"needs" + 0.007*"progress" + 0.007*"well" + 0.006*"need" + 0.006*"plans" + 0.005*"effective" + 0.005*"receive"
+2024-05-13 12:41:50,910 - topic #2 (0.333): 0.019*"’" + 0.009*"Southwark" + 0.007*"good" + 0.007*"well" + 0.007*"needs" + 0.005*"strong" + 0.005*"progress" + 0.005*"plans" + 0.005*"risks" + 0.005*"need"
+2024-05-13 12:41:50,911 - topic diff=0.735005, rho=1.000000
+2024-05-13 12:41:50,911 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=945, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:50.911226', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:51,956 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:51,956 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:51,956 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:51,956 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:51,957 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:51,957 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:51,957 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:51,957 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:51,957 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:51,957 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:51,958 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:51,958 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:53,180 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:53,183 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)
+2024-05-13 12:41:53,184 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-05-13T12:41:53.183997', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:53,185 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:53,185 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:53,186 - using serial LDA version on this node
+2024-05-13 12:41:53,186 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:53,186 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:53,192 - -7.987 per-word bound, 253.7 perplexity estimate based on a held-out corpus of 1 documents with 1847 words
+2024-05-13 12:41:53,193 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:53,195 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"Sutton" + 0.006*"progress" + 0.005*"needs" + 0.005*"effective" + 0.005*"supported" + 0.004*"receive" + 0.004*"December" + 0.004*"home"
+2024-05-13 12:41:53,195 - topic #1 (0.333): 0.018*"’" + 0.007*"needs" + 0.006*"well" + 0.005*"Sutton" + 0.005*"good" + 0.005*"receive" + 0.005*"10" + 0.004*"progress" + 0.004*"effective" + 0.004*"6"
+2024-05-13 12:41:53,195 - topic #2 (0.333): 0.016*"’" + 0.006*"well" + 0.006*"Sutton" + 0.005*"6" + 0.005*"good" + 0.005*"progress" + 0.005*"need" + 0.005*"receive" + 0.005*"needs" + 0.004*"effective"
+2024-05-13 12:41:53,196 - topic diff=0.724328, rho=1.000000
+2024-05-13 12:41:53,196 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=976, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:53.196364', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:55,235 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:55,235 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:55,235 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:55,236 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:55,236 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:55,236 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:55,236 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:55,236 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:55,236 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:55,237 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:55,237 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:55,237 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:57,022 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:57,024 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)
+2024-05-13 12:41:57,024 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-05-13T12:41:57.024820', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:57,025 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:57,026 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:57,026 - using serial LDA version on this node
+2024-05-13 12:41:57,026 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:57,026 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:57,030 - -8.129 per-word bound, 280.0 perplexity estimate based on a held-out corpus of 1 documents with 2465 words
+2024-05-13 12:41:57,030 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:57,032 - topic #0 (0.333): 0.013*"’" + 0.007*"good" + 0.006*"including" + 0.006*"‘" + 0.006*"well" + 0.006*"plans" + 0.006*"practice" + 0.005*"need" + 0.005*"effective" + 0.005*"progress"
+2024-05-13 12:41:57,032 - topic #1 (0.333): 0.020*"’" + 0.007*"effective" + 0.007*"good" + 0.007*"plans" + 0.006*"well" + 0.006*"practice" + 0.005*"early" + 0.005*"need" + 0.005*"risk" + 0.005*"needs"
+2024-05-13 12:41:57,032 - topic #2 (0.333): 0.008*"’" + 0.006*"‘" + 0.006*"plans" + 0.005*"effective" + 0.005*"good" + 0.004*"including" + 0.004*"progress" + 0.004*"well" + 0.004*"practice" + 0.004*"need"
+2024-05-13 12:41:57,032 - topic diff=0.777417, rho=1.000000
+2024-05-13 12:41:57,033 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1194, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:57.032982', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:57,974 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:41:57,975 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:57,975 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:41:57,975 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:57,975 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:41:57,975 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:57,975 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:41:57,976 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:57,976 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:41:57,976 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:57,976 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:41:57,976 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:41:59,624 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:41:59,626 - built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)
+2024-05-13 12:41:59,627 - Dictionary lifecycle event {'msg': "built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-05-13T12:41:59.627023', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:41:59,628 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:41:59,628 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:41:59,628 - using serial LDA version on this node
+2024-05-13 12:41:59,628 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:41:59,629 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:41:59,632 - -7.975 per-word bound, 251.6 perplexity estimate based on a held-out corpus of 1 documents with 2199 words
+2024-05-13 12:41:59,632 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:41:59,633 - topic #0 (0.333): 0.016*"’" + 0.010*"well" + 0.010*"needs" + 0.009*"effective" + 0.009*"good" + 0.006*"need" + 0.005*"plans" + 0.005*"risk" + 0.004*"timely" + 0.004*"clear"
+2024-05-13 12:41:59,634 - topic #1 (0.333): 0.016*"’" + 0.013*"well" + 0.009*"good" + 0.009*"needs" + 0.007*"need" + 0.006*"effective" + 0.006*"plans" + 0.005*"progress" + 0.005*"ensure" + 0.005*"timely"
+2024-05-13 12:41:59,634 - topic #2 (0.333): 0.013*"well" + 0.009*"’" + 0.007*"needs" + 0.006*"good" + 0.005*"effective" + 0.005*"plans" + 0.005*"timely" + 0.004*"need" + 0.004*"risk" + 0.004*"actions"
+2024-05-13 12:41:59,634 - topic diff=0.786315, rho=1.000000
+2024-05-13 12:41:59,634 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1036, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:41:59.634596', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:00,735 - Inspection date 2019-01-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:00,735 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:00,736 - Inspection date 2019-01-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:00,736 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:00,736 - Inspection date 2019-01-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:00,736 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:00,736 - Inspection date 2019-01-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:00,736 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:00,737 - Inspection date 2019-01-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:00,737 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:00,737 - Inspection date 2019-01-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:00,737 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:02,345 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:02,347 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)
+2024-05-13 12:42:02,348 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-05-13T12:42:02.348098', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:02,349 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:02,349 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:02,349 - using serial LDA version on this node
+2024-05-13 12:42:02,349 - 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
+2024-05-13 12:42:02,349 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:02,352 - -7.853 per-word bound, 231.3 perplexity estimate based on a held-out corpus of 1 documents with 1772 words
+2024-05-13 12:42:02,353 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:02,354 - topic #0 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"Wandsworth" + 0.006*"practice" + 0.006*"quality" + 0.006*"progress" + 0.005*"good" + 0.005*"supported" + 0.005*"protection" + 0.005*"timely"
+2024-05-13 12:42:02,354 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.006*"protection" + 0.005*"needs" + 0.005*"Senior" + 0.005*"7" + 0.005*"progress" + 0.005*"practice" + 0.005*"ensure" + 0.005*"effective"
+2024-05-13 12:42:02,354 - topic #2 (0.333): 0.010*"’" + 0.006*"needs" + 0.006*"well" + 0.005*"Senior" + 0.005*"progress" + 0.005*"7" + 0.004*"supported" + 0.004*"team" + 0.004*"effective" + 0.004*"ensure"
+2024-05-13 12:42:02,354 - topic diff=0.756709, rho=1.000000
+2024-05-13 12:42:02,354 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=884, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:02.354847', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:03,310 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:03,310 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:03,310 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:03,311 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:03,311 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:03,311 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:03,311 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:03,311 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:03,311 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:03,312 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:03,312 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:03,312 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:05,135 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:05,137 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)
+2024-05-13 12:42:05,138 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-05-13T12:42:05.138055', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:05,139 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:05,139 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:05,139 - using serial LDA version on this node
+2024-05-13 12:42:05,139 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:05,140 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:05,143 - -8.155 per-word bound, 285.1 perplexity estimate based on a held-out corpus of 1 documents with 2101 words
+2024-05-13 12:42:05,144 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:05,145 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"practice" + 0.005*"well" + 0.005*"highly" + 0.005*"many" + 0.004*"across" + 0.004*"plans" + 0.003*"need" + 0.003*"skilled"
+2024-05-13 12:42:05,145 - topic #1 (0.333): 0.013*"’" + 0.007*"practice" + 0.007*"highly" + 0.005*"needs" + 0.004*"family" + 0.004*"well" + 0.004*"across" + 0.004*"high" + 0.003*"Westminster" + 0.003*"shared"
+2024-05-13 12:42:05,145 - topic #2 (0.333): 0.012*"’" + 0.006*"practice" + 0.006*"needs" + 0.005*"well" + 0.005*"highly" + 0.003*"skilled" + 0.003*"direct" + 0.003*"many" + 0.003*"plans" + 0.003*"protection"
+2024-05-13 12:42:05,146 - topic diff=0.691696, rho=1.000000
+2024-05-13 12:42:05,146 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1136, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:05.146184', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:06,486 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:06,487 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:06,487 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:06,487 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:06,488 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:06,488 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:06,488 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:06,488 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:06,488 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:06,488 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:06,489 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:06,489 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:08,524 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:08,526 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)
+2024-05-13 12:42:08,526 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-05-13T12:42:08.526953', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:08,528 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:08,528 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:08,528 - using serial LDA version on this node
+2024-05-13 12:42:08,528 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:08,529 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:08,533 - -8.109 per-word bound, 276.0 perplexity estimate based on a held-out corpus of 1 documents with 2593 words
+2024-05-13 12:42:08,533 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:08,534 - topic #0 (0.333): 0.023*"’" + 0.007*"needs" + 0.007*"need" + 0.006*"plans" + 0.006*"effective" + 0.006*"impact" + 0.005*"progress" + 0.005*"good" + 0.005*"Luton" + 0.005*"quality"
+2024-05-13 12:42:08,534 - topic #1 (0.333): 0.014*"’" + 0.007*"need" + 0.006*"Luton" + 0.006*"plans" + 0.005*"effective" + 0.005*"needs" + 0.005*"receive" + 0.005*"well" + 0.005*"good" + 0.005*"progress"
+2024-05-13 12:42:08,534 - topic #2 (0.333): 0.012*"’" + 0.006*"plans" + 0.006*"ensure" + 0.006*"Luton" + 0.006*"needs" + 0.005*"good" + 0.004*"need" + 0.004*"impact" + 0.004*"effective" + 0.004*"receive"
+2024-05-13 12:42:08,535 - topic diff=0.792466, rho=1.000000
+2024-05-13 12:42:08,535 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1199, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:08.535219', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:09,641 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:09,641 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:09,642 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:09,642 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:09,642 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:09,642 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:09,643 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:09,643 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:09,643 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:09,643 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:09,643 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:09,644 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:11,171 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:11,173 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)
+2024-05-13 12:42:11,173 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-05-13T12:42:11.173589', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:11,174 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:11,174 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:11,174 - using serial LDA version on this node
+2024-05-13 12:42:11,175 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:11,175 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:11,178 - -7.775 per-word bound, 219.0 perplexity estimate based on a held-out corpus of 1 documents with 1938 words
+2024-05-13 12:42:11,178 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:11,179 - topic #0 (0.333): 0.010*"’" + 0.007*"needs" + 0.005*"supported" + 0.005*"always" + 0.005*"plans" + 0.005*"Manchester" + 0.004*"well" + 0.004*"disabled" + 0.004*"March" + 0.003*"effective"
+2024-05-13 12:42:11,180 - topic #1 (0.333): 0.025*"’" + 0.013*"Manchester" + 0.009*"needs" + 0.007*"always" + 0.006*"supported" + 0.006*"plans" + 0.006*"well" + 0.005*"quality" + 0.005*"education" + 0.005*"protection"
+2024-05-13 12:42:11,180 - topic #2 (0.333): 0.022*"’" + 0.011*"needs" + 0.011*"Manchester" + 0.009*"well" + 0.007*"supported" + 0.006*"always" + 0.006*"effective" + 0.006*"education" + 0.006*"protection" + 0.005*"disabled"
+2024-05-13 12:42:11,180 - topic diff=0.843169, rho=1.000000
+2024-05-13 12:42:11,180 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=871, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:11.180526', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:12,267 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:12,267 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:12,268 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:12,268 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:12,268 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:12,268 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:12,268 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:12,268 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:12,268 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:12,269 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:12,269 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:12,269 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:13,963 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:13,965 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)
+2024-05-13 12:42:13,966 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-05-13T12:42:13.966049', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:13,966 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:13,967 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:13,967 - using serial LDA version on this node
+2024-05-13 12:42:13,967 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:13,967 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:13,970 - -7.888 per-word bound, 236.9 perplexity estimate based on a held-out corpus of 1 documents with 1857 words
+2024-05-13 12:42:13,971 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:13,972 - topic #0 (0.333): 0.015*"’" + 0.009*"Medway" + 0.009*"quality" + 0.008*"well" + 0.007*"experiences" + 0.006*"impact" + 0.005*"leaders" + 0.005*"practice" + 0.005*"Senior" + 0.005*"progress"
+2024-05-13 12:42:13,972 - topic #1 (0.333): 0.009*"’" + 0.007*"Medway" + 0.007*"practice" + 0.006*"leaders" + 0.005*"well" + 0.005*"needs" + 0.005*"quality" + 0.004*"clear" + 0.004*"risk" + 0.004*"oversight"
+2024-05-13 12:42:13,972 - topic #2 (0.333): 0.020*"’" + 0.010*"practice" + 0.009*"Medway" + 0.008*"well" + 0.008*"quality" + 0.008*"needs" + 0.007*"oversight" + 0.007*"leaders" + 0.006*"impact" + 0.006*"17"
+2024-05-13 12:42:13,972 - topic diff=0.792363, rho=1.000000
+2024-05-13 12:42:13,973 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=922, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:13.973106', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:14,944 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:14,944 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:14,944 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:14,944 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:14,945 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:14,945 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:14,945 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:14,945 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:14,945 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:14,945 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:14,946 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:14,946 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:17,043 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:17,046 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)
+2024-05-13 12:42:17,046 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-05-13T12:42:17.046259', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:17,047 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:17,047 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:17,047 - using serial LDA version on this node
+2024-05-13 12:42:17,048 - 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
+2024-05-13 12:42:17,048 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:17,052 - -7.998 per-word bound, 255.7 perplexity estimate based on a held-out corpus of 1 documents with 2278 words
+2024-05-13 12:42:17,052 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:17,053 - topic #0 (0.333): 0.012*"’" + 0.007*"effective" + 0.006*"well" + 0.006*"plans" + 0.006*"Middlesbrough" + 0.006*"progress" + 0.006*"needs" + 0.004*"impact" + 0.004*"practice" + 0.004*"place"
+2024-05-13 12:42:17,053 - topic #1 (0.333): 0.013*"’" + 0.007*"plans" + 0.007*"effective" + 0.007*"Middlesbrough" + 0.007*"practice" + 0.006*"well" + 0.005*"progress" + 0.005*"needs" + 0.005*"means" + 0.005*"impact"
+2024-05-13 12:42:17,054 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"plans" + 0.007*"well" + 0.007*"effective" + 0.007*"Middlesbrough" + 0.005*"24" + 0.005*"practice" + 0.005*"March" + 0.005*"place"
+2024-05-13 12:42:17,054 - topic diff=0.779107, rho=1.000000
+2024-05-13 12:42:17,054 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1068, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:17.054300', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:18,213 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:18,217 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:18,217 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:18,217 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:18,218 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:18,218 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:18,218 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:18,218 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:18,218 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:18,219 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:18,224 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:18,227 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:20,229 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:20,233 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)
+2024-05-13 12:42:20,234 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-05-13T12:42:20.234161', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:20,235 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:20,236 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:20,236 - using serial LDA version on this node
+2024-05-13 12:42:20,237 - 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
+2024-05-13 12:42:20,237 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:20,244 - -8.030 per-word bound, 261.3 perplexity estimate based on a held-out corpus of 1 documents with 2328 words
+2024-05-13 12:42:20,244 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:20,246 - topic #0 (0.333): 0.021*"’" + 0.006*"well" + 0.006*"need" + 0.006*"Keynes" + 0.006*"Milton" + 0.005*"25" + 0.005*"plans" + 0.005*"practice" + 0.005*"education" + 0.005*"leaders"
+2024-05-13 12:42:20,250 - topic #1 (0.333): 0.012*"’" + 0.005*"Keynes" + 0.005*"good" + 0.005*"Milton" + 0.005*"well" + 0.005*"practice" + 0.004*"October" + 0.004*"need" + 0.004*"family" + 0.004*"team"
+2024-05-13 12:42:20,251 - topic #2 (0.333): 0.008*"’" + 0.007*"Milton" + 0.006*"Keynes" + 0.005*"well" + 0.004*"need" + 0.004*"leaders" + 0.004*"practice" + 0.004*"plans" + 0.004*"25" + 0.004*"2021"
+2024-05-13 12:42:20,251 - topic diff=0.792331, rho=1.000000
+2024-05-13 12:42:20,251 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1101, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:20.251569', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:21,209 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:21,209 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:21,210 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:21,210 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:21,210 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:21,210 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:21,211 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:21,211 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:21,211 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:21,211 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:21,212 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:21,212 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:22,618 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:22,621 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)
+2024-05-13 12:42:22,621 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-05-13T12:42:22.621514', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:22,622 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:22,623 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:22,623 - using serial LDA version on this node
+2024-05-13 12:42:22,623 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:22,623 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:22,630 - -7.880 per-word bound, 235.5 perplexity estimate based on a held-out corpus of 1 documents with 2076 words
+2024-05-13 12:42:22,630 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:22,632 - topic #0 (0.333): 0.013*"’" + 0.008*"plans" + 0.007*"Newcastle" + 0.006*"protection" + 0.006*"well" + 0.005*"needs" + 0.005*"management" + 0.005*"2021" + 0.005*"need" + 0.005*"good"
+2024-05-13 12:42:22,632 - topic #1 (0.333): 0.017*"’" + 0.010*"plans" + 0.008*"protection" + 0.008*"Newcastle" + 0.007*"needs" + 0.007*"progress" + 0.007*"good" + 0.007*"well" + 0.006*"ensure" + 0.005*"need"
+2024-05-13 12:42:22,632 - topic #2 (0.333): 0.017*"’" + 0.012*"plans" + 0.009*"needs" + 0.008*"good" + 0.006*"well" + 0.006*"response" + 0.006*"making" + 0.006*"ensure" + 0.006*"Newcastle" + 0.006*"protection"
+2024-05-13 12:42:22,633 - topic diff=0.789929, rho=1.000000
+2024-05-13 12:42:22,633 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=956, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:22.633170', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:23,776 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:23,776 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:23,777 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:23,777 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:23,777 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:23,777 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:23,777 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:23,777 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:23,777 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:23,777 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:23,778 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:23,778 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:25,589 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:25,592 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)
+2024-05-13 12:42:25,592 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-05-13T12:42:25.592348', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:25,593 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:25,593 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:25,593 - using serial LDA version on this node
+2024-05-13 12:42:25,594 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:25,594 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:25,598 - -8.123 per-word bound, 278.8 perplexity estimate based on a held-out corpus of 1 documents with 2655 words
+2024-05-13 12:42:25,598 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:25,600 - topic #0 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"Norfolk" + 0.007*"carers" + 0.006*"supported" + 0.005*"practice" + 0.005*"range" + 0.005*"needs" + 0.005*"leaders" + 0.004*"information"
+2024-05-13 12:42:25,600 - topic #1 (0.333): 0.019*"’" + 0.009*"Norfolk" + 0.008*"well" + 0.007*"needs" + 0.006*"carers" + 0.005*"practice" + 0.005*"plans" + 0.005*"including" + 0.005*"supported" + 0.005*"effective"
+2024-05-13 12:42:25,600 - topic #2 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"Norfolk" + 0.006*"practice" + 0.005*"carers" + 0.005*"needs" + 0.004*"supported" + 0.004*"18" + 0.004*"family" + 0.004*"also"
+2024-05-13 12:42:25,600 - topic diff=0.780077, rho=1.000000
+2024-05-13 12:42:25,600 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1221, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:25.600841', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:26,665 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:26,665 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:26,666 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:26,666 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:26,666 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:26,666 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:26,666 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:26,667 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:26,667 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:26,667 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:26,667 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:26,667 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:28,510 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:28,514 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)
+2024-05-13 12:42:28,514 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-05-13T12:42:28.514857', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:28,515 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:28,516 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:28,516 - using serial LDA version on this node
+2024-05-13 12:42:28,516 - 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
+2024-05-13 12:42:28,516 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:28,520 - -7.894 per-word bound, 237.9 perplexity estimate based on a held-out corpus of 1 documents with 2045 words
+2024-05-13 12:42:28,520 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:28,522 - topic #0 (0.333): 0.014*"’" + 0.007*"risk" + 0.006*"leaders" + 0.006*"practice" + 0.005*"East" + 0.005*"Lincolnshire" + 0.005*"needs" + 0.005*"planning" + 0.005*"plans" + 0.005*"many"
+2024-05-13 12:42:28,522 - topic #1 (0.333): 0.014*"’" + 0.008*"practice" + 0.008*"leaders" + 0.007*"needs" + 0.007*"risk" + 0.007*"planning" + 0.006*"2021" + 0.006*"need" + 0.005*"many" + 0.005*"North"
+2024-05-13 12:42:28,522 - topic #2 (0.333): 0.014*"’" + 0.009*"practice" + 0.006*"planning" + 0.006*"risk" + 0.005*"needs" + 0.005*"need" + 0.005*"quality" + 0.005*"leaders" + 0.005*"oversight" + 0.005*"Council"
+2024-05-13 12:42:28,523 - topic diff=0.767941, rho=1.000000
+2024-05-13 12:42:28,523 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=958, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:28.523436', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:29,728 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:29,728 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:29,728 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:29,728 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:29,728 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:29,728 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:29,729 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:29,729 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:29,729 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:29,729 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:29,729 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:29,729 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:31,361 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:31,364 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)
+2024-05-13 12:42:31,364 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-05-13T12:42:31.364223', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:31,365 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:31,365 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:31,365 - using serial LDA version on this node
+2024-05-13 12:42:31,366 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:31,366 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:31,369 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2174 words
+2024-05-13 12:42:31,370 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:31,371 - topic #0 (0.333): 0.022*"’" + 0.007*"‘" + 0.006*"Lincolnshire" + 0.006*"North" + 0.006*"approach" + 0.005*"family" + 0.005*"well" + 0.005*"need" + 0.004*"leaders" + 0.004*"10"
+2024-05-13 12:42:31,371 - topic #1 (0.333): 0.016*"’" + 0.009*"‘" + 0.007*"family" + 0.005*"leaders" + 0.005*"team" + 0.005*"approach" + 0.005*"10" + 0.005*"Lincolnshire" + 0.005*"well" + 0.005*"North"
+2024-05-13 12:42:31,371 - topic #2 (0.333): 0.023*"’" + 0.006*"‘" + 0.005*"family" + 0.005*"North" + 0.005*"leaders" + 0.005*"well" + 0.005*"10" + 0.005*"Lincolnshire" + 0.005*"protection" + 0.004*"October"
+2024-05-13 12:42:31,371 - topic diff=0.747076, rho=1.000000
+2024-05-13 12:42:31,372 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:31.371992', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:32,466 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:32,467 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:32,467 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:32,467 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:32,467 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:32,467 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:32,467 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:32,467 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:32,468 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:32,468 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:32,468 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:32,468 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:33,977 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:33,980 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)
+2024-05-13 12:42:33,980 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-05-13T12:42:33.980683', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:33,981 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:33,981 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:33,982 - using serial LDA version on this node
+2024-05-13 12:42:33,982 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:33,982 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:33,986 - -8.031 per-word bound, 261.6 perplexity estimate based on a held-out corpus of 1 documents with 2204 words
+2024-05-13 12:42:33,986 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:33,987 - topic #0 (0.333): 0.013*"’" + 0.007*"Northamptonshire" + 0.007*"well" + 0.006*"NCT" + 0.005*"North" + 0.005*"practice" + 0.005*"need" + 0.004*"October" + 0.004*"quality" + 0.004*"3"
+2024-05-13 12:42:33,987 - topic #1 (0.333): 0.014*"’" + 0.007*"Northamptonshire" + 0.007*"quality" + 0.007*"well" + 0.005*"North" + 0.005*"However" + 0.005*"practice" + 0.005*"e" + 0.004*"plans" + 0.004*"Leaders"
+2024-05-13 12:42:33,988 - topic #2 (0.333): 0.021*"’" + 0.009*"Northamptonshire" + 0.008*"North" + 0.006*"impact" + 0.005*"needs" + 0.005*"well" + 0.005*"quality" + 0.005*"Leaders" + 0.005*"need" + 0.005*"experiences"
+2024-05-13 12:42:33,988 - topic diff=0.747328, rho=1.000000
+2024-05-13 12:42:33,988 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:33.988293', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:35,099 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:35,099 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:35,100 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:35,100 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:35,100 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:35,101 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:35,101 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:35,101 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:35,101 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:35,101 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:35,102 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:35,102 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:36,634 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:36,639 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)
+2024-05-13 12:42:36,639 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-05-13T12:42:36.639721', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:36,641 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:36,641 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:36,642 - using serial LDA version on this node
+2024-05-13 12:42:36,642 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:36,642 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:36,650 - -8.065 per-word bound, 267.8 perplexity estimate based on a held-out corpus of 1 documents with 2902 words
+2024-05-13 12:42:36,650 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:36,652 - topic #0 (0.333): 0.013*"’" + 0.006*"needs" + 0.006*"Somerset" + 0.006*"quality" + 0.006*"always" + 0.005*"practice" + 0.005*"risk" + 0.005*"North" + 0.005*"progress" + 0.004*"need"
+2024-05-13 12:42:36,653 - topic #1 (0.333): 0.019*"’" + 0.007*"quality" + 0.007*"needs" + 0.006*"practice" + 0.006*"always" + 0.006*"North" + 0.006*"plans" + 0.006*"Somerset" + 0.006*"progress" + 0.006*"need"
+2024-05-13 12:42:36,653 - topic #2 (0.333): 0.017*"’" + 0.009*"quality" + 0.007*"needs" + 0.006*"number" + 0.006*"North" + 0.006*"always" + 0.005*"well" + 0.005*"experienced" + 0.005*"Somerset" + 0.004*"practice"
+2024-05-13 12:42:36,653 - topic diff=0.832780, rho=1.000000
+2024-05-13 12:42:36,653 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1219, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:36.653797', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:38,450 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:38,450 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:38,451 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:38,451 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:38,451 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:38,451 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:38,451 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:38,451 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:38,452 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:38,452 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:38,452 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:38,452 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:40,347 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:40,353 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)
+2024-05-13 12:42:40,353 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-05-13T12:42:40.353467', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:40,355 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:40,355 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:40,356 - using serial LDA version on this node
+2024-05-13 12:42:40,356 - 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
+2024-05-13 12:42:40,356 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:40,365 - -8.220 per-word bound, 298.2 perplexity estimate based on a held-out corpus of 1 documents with 2518 words
+2024-05-13 12:42:40,365 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:40,368 - topic #0 (0.333): 0.016*"’" + 0.006*"well" + 0.005*"quality" + 0.005*"need" + 0.004*"leaders" + 0.004*"make" + 0.004*"needs" + 0.004*"impact" + 0.004*"early" + 0.004*"clear"
+2024-05-13 12:42:40,368 - topic #1 (0.333): 0.015*"’" + 0.007*"well" + 0.005*"make" + 0.005*"leaders" + 0.005*"need" + 0.004*"needs" + 0.004*"quality" + 0.004*"experiences" + 0.003*"understand" + 0.003*"progress"
+2024-05-13 12:42:40,368 - topic #2 (0.333): 0.016*"’" + 0.006*"leaders" + 0.006*"well" + 0.005*"need" + 0.005*"impact" + 0.005*"needs" + 0.004*"quality" + 0.004*"protection" + 0.004*"early" + 0.004*"make"
+2024-05-13 12:42:40,369 - topic diff=0.730722, rho=1.000000
+2024-05-13 12:42:40,369 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1273, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:40.369305', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:41,959 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:41,960 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:41,960 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:41,960 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:41,960 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:41,961 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:41,961 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:41,961 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:41,961 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:41,961 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:41,961 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:41,961 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:43,678 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:43,681 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)
+2024-05-13 12:42:43,681 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-05-13T12:42:43.681880', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:43,683 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:43,683 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:43,683 - using serial LDA version on this node
+2024-05-13 12:42:43,683 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:43,684 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:43,688 - -8.149 per-word bound, 283.8 perplexity estimate based on a held-out corpus of 1 documents with 2759 words
+2024-05-13 12:42:43,689 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:43,690 - topic #0 (0.333): 0.018*"’" + 0.008*"well" + 0.006*"family" + 0.006*"practice" + 0.006*"needs" + 0.006*"Yorkshire" + 0.006*"‘" + 0.006*"North" + 0.005*"3" + 0.004*"7"
+2024-05-13 12:42:43,690 - topic #1 (0.333): 0.025*"’" + 0.009*"well" + 0.007*"North" + 0.006*"Yorkshire" + 0.006*"practice" + 0.005*"needs" + 0.005*"family" + 0.004*"‘" + 0.004*"supported" + 0.004*"need"
+2024-05-13 12:42:43,690 - topic #2 (0.333): 0.018*"’" + 0.007*"well" + 0.006*"practice" + 0.006*"North" + 0.006*"family" + 0.005*"Yorkshire" + 0.005*"needs" + 0.004*"2023" + 0.004*"‘" + 0.004*"3"
+2024-05-13 12:42:43,690 - topic diff=0.799460, rho=1.000000
+2024-05-13 12:42:43,691 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1259, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:43.691101', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:44,696 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:44,696 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:44,696 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:44,696 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:44,696 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:44,696 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:44,697 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:44,697 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:44,697 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:44,697 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:44,697 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:44,697 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:46,264 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:46,267 - built Dictionary<889 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1709 corpus positions)
+2024-05-13 12:42:46,267 - Dictionary lifecycle event {'msg': "built Dictionary<889 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1709 corpus positions)", 'datetime': '2024-05-13T12:42:46.267320', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:46,268 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:46,269 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:46,269 - using serial LDA version on this node
+2024-05-13 12:42:46,269 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:46,269 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:46,275 - -7.884 per-word bound, 236.2 perplexity estimate based on a held-out corpus of 1 documents with 1709 words
+2024-05-13 12:42:46,275 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:46,277 - topic #0 (0.333): 0.022*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"good" + 0.006*"need" + 0.005*"experiences" + 0.005*"impact" + 0.005*"quality" + 0.005*"leaders" + 0.005*"plans"
+2024-05-13 12:42:46,277 - topic #1 (0.333): 0.029*"’" + 0.012*"well" + 0.012*"needs" + 0.007*"education" + 0.006*"practice" + 0.006*"good" + 0.006*"experiences" + 0.005*"need" + 0.005*"impact" + 0.004*"quality"
+2024-05-13 12:42:46,277 - topic #2 (0.333): 0.011*"’" + 0.009*"good" + 0.008*"needs" + 0.007*"well" + 0.007*"need" + 0.005*"experiences" + 0.004*"practice" + 0.004*"quality" + 0.004*"leaders" + 0.004*"impact"
+2024-05-13 12:42:46,277 - topic diff=0.733865, rho=1.000000
+2024-05-13 12:42:46,278 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=889, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:46.278092', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:47,740 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:47,740 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:47,741 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:47,741 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:47,741 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:47,741 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:47,741 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:47,741 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:47,742 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:47,742 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:47,742 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:47,742 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:49,359 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:49,362 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
+2024-05-13 12:42:49,362 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-05-13T12:42:49.362225', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:49,363 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:49,363 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:49,363 - using serial LDA version on this node
+2024-05-13 12:42:49,364 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:49,364 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:49,368 - -8.029 per-word bound, 261.2 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
+2024-05-13 12:42:49,368 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:49,369 - topic #0 (0.333): 0.011*"’" + 0.009*"needs" + 0.006*"Nottingham" + 0.006*"plans" + 0.005*"City" + 0.005*"effective" + 0.005*"11" + 0.005*"impact" + 0.005*"However" + 0.004*"2022"
+2024-05-13 12:42:49,369 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.006*"Nottingham" + 0.005*"impact" + 0.004*"effective" + 0.004*"plans" + 0.004*"11" + 0.004*"protection" + 0.004*"oversight" + 0.004*"practice"
+2024-05-13 12:42:49,369 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"effective" + 0.006*"plans" + 0.006*"Nottingham" + 0.005*"risk" + 0.005*"oversight" + 0.005*"need" + 0.005*"practice" + 0.004*"However"
+2024-05-13 12:42:49,370 - topic diff=0.765958, rho=1.000000
+2024-05-13 12:42:49,370 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:49.370192', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:50,429 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:50,429 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:50,429 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:50,430 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:50,430 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:50,430 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:50,430 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:50,430 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:50,430 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:50,430 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:50,431 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:50,431 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:52,598 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:52,601 - built Dictionary<1167 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)
+2024-05-13 12:42:52,601 - Dictionary lifecycle event {'msg': "built Dictionary<1167 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-05-13T12:42:52.601603', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:52,602 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:52,602 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:52,603 - using serial LDA version on this node
+2024-05-13 12:42:52,603 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:52,603 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:52,607 - -8.098 per-word bound, 274.0 perplexity estimate based on a held-out corpus of 1 documents with 2465 words
+2024-05-13 12:42:52,607 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:52,608 - topic #0 (0.333): 0.009*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"practice" + 0.005*"e" + 0.004*"receive" + 0.004*"ensure" + 0.003*"plans" + 0.003*"quality" + 0.003*"areas"
+2024-05-13 12:42:52,609 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.008*"practice" + 0.006*"plans" + 0.006*"made" + 0.005*"ensure" + 0.005*"needs" + 0.005*"receive" + 0.005*"progress" + 0.004*"quality"
+2024-05-13 12:42:52,609 - topic #2 (0.333): 0.012*"’" + 0.009*"practice" + 0.008*"well" + 0.006*"needs" + 0.006*"receive" + 0.006*"areas" + 0.006*"progress" + 0.006*"quality" + 0.005*"ensure" + 0.005*"carers"
+2024-05-13 12:42:52,609 - topic diff=0.802177, rho=1.000000
+2024-05-13 12:42:52,609 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1167, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:52.609531', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:53,689 - Inspection date 2019-10-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:53,689 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:53,689 - Inspection date 2019-10-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:53,689 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:53,689 - Inspection date 2019-10-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:53,690 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:53,690 - Inspection date 2019-10-07 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:53,690 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:53,690 - Inspection date 2019-10-07 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:53,690 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:53,690 - Inspection date 2019-10-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:53,690 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:55,248 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:55,250 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2364 corpus positions)
+2024-05-13 12:42:55,251 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2364 corpus positions)", 'datetime': '2024-05-13T12:42:55.251149', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:55,252 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:55,252 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:55,252 - using serial LDA version on this node
+2024-05-13 12:42:55,253 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:55,253 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:55,256 - -7.910 per-word bound, 240.6 perplexity estimate based on a held-out corpus of 1 documents with 2364 words
+2024-05-13 12:42:55,256 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:55,258 - topic #0 (0.333): 0.010*"’" + 0.009*"needs" + 0.009*"effective" + 0.008*"practice" + 0.008*"good" + 0.007*"planning" + 0.006*"plans" + 0.006*"progress" + 0.005*"quality" + 0.005*"risk"
+2024-05-13 12:42:55,258 - topic #1 (0.333): 0.012*"’" + 0.009*"needs" + 0.009*"practice" + 0.008*"good" + 0.007*"progress" + 0.007*"effective" + 0.006*"well" + 0.006*"quality" + 0.005*"information" + 0.005*"plans"
+2024-05-13 12:42:55,258 - topic #2 (0.333): 0.011*"good" + 0.010*"’" + 0.009*"needs" + 0.009*"practice" + 0.008*"well" + 0.008*"quality" + 0.007*"effective" + 0.006*"planning" + 0.006*"plans" + 0.006*"progress"
+2024-05-13 12:42:55,258 - topic diff=0.790411, rho=1.000000
+2024-05-13 12:42:55,258 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:55.258667', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:56,375 - Inspection date 2019-01-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:56,375 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:56,375 - Inspection date 2019-01-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:56,376 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:56,376 - Inspection date 2019-01-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:56,376 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:56,376 - Inspection date 2019-01-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:56,376 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:56,376 - Inspection date 2019-01-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:56,377 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:56,377 - Inspection date 2019-01-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:56,377 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:58,134 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:42:58,136 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)
+2024-05-13 12:42:58,137 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-05-13T12:42:58.136986', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:58,138 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:42:58,138 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:42:58,138 - using serial LDA version on this node
+2024-05-13 12:42:58,138 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:42:58,138 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:42:58,142 - -7.989 per-word bound, 254.0 perplexity estimate based on a held-out corpus of 1 documents with 2294 words
+2024-05-13 12:42:58,142 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:42:58,143 - topic #0 (0.333): 0.019*"’" + 0.008*"needs" + 0.008*"Oxfordshire" + 0.007*"well" + 0.007*"risk" + 0.006*"supported" + 0.005*"23" + 0.005*"quality" + 0.005*"leaders" + 0.005*"practice"
+2024-05-13 12:42:58,144 - topic #1 (0.333): 0.016*"’" + 0.012*"needs" + 0.006*"good" + 0.006*"well" + 0.006*"Oxfordshire" + 0.006*"risk" + 0.005*"quality" + 0.005*"12" + 0.005*"supported" + 0.005*"education"
+2024-05-13 12:42:58,144 - topic #2 (0.333): 0.022*"’" + 0.009*"needs" + 0.007*"Oxfordshire" + 0.006*"well" + 0.005*"good" + 0.005*"supported" + 0.005*"progress" + 0.005*"practice" + 0.005*"receive" + 0.004*"risk"
+2024-05-13 12:42:58,144 - topic diff=0.774380, rho=1.000000
+2024-05-13 12:42:58,144 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1066, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:42:58.144571', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:42:59,137 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:42:59,138 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:59,138 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:42:59,138 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:59,138 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:42:59,138 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:59,138 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:42:59,139 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:59,139 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:42:59,139 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:42:59,139 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:42:59,139 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:00,515 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:00,517 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)
+2024-05-13 12:43:00,517 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-05-13T12:43:00.517320', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:00,518 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:00,518 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:00,518 - using serial LDA version on this node
+2024-05-13 12:43:00,518 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:00,519 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:00,522 - -7.883 per-word bound, 236.1 perplexity estimate based on a held-out corpus of 1 documents with 1737 words
+2024-05-13 12:43:00,522 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:00,524 - topic #0 (0.333): 0.016*"’" + 0.014*"needs" + 0.007*"need" + 0.007*"2023" + 0.006*"progress" + 0.006*"Peterborough" + 0.006*"good" + 0.005*"plans" + 0.005*"receive" + 0.005*"well"
+2024-05-13 12:43:00,524 - topic #1 (0.333): 0.011*"needs" + 0.010*"’" + 0.007*"Peterborough" + 0.006*"well" + 0.006*"need" + 0.005*"supported" + 0.005*"2023" + 0.005*"progress" + 0.004*"education" + 0.004*"plans"
+2024-05-13 12:43:00,524 - topic #2 (0.333): 0.016*"’" + 0.014*"needs" + 0.007*"need" + 0.007*"Peterborough" + 0.007*"well" + 0.006*"2023" + 0.006*"progress" + 0.006*"8" + 0.006*"27" + 0.005*"plans"
+2024-05-13 12:43:00,524 - topic diff=0.731302, rho=1.000000
+2024-05-13 12:43:00,524 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=893, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:00.524798', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:01,593 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:01,593 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:01,593 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:01,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:01,594 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:01,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:01,594 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:01,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:01,594 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:01,594 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:01,595 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:01,595 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:03,902 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:03,905 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)
+2024-05-13 12:43:03,905 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-05-13T12:43:03.905626', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:03,906 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:03,907 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:03,907 - using serial LDA version on this node
+2024-05-13 12:43:03,907 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:03,907 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:03,911 - -8.084 per-word bound, 271.3 perplexity estimate based on a held-out corpus of 1 documents with 2905 words
+2024-05-13 12:43:03,911 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:03,913 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.008*"Plymouth" + 0.007*"well" + 0.006*"practice" + 0.005*"2024" + 0.005*"education" + 0.005*"2" + 0.005*"February" + 0.005*"always"
+2024-05-13 12:43:03,913 - topic #1 (0.333): 0.010*"’" + 0.006*"Plymouth" + 0.006*"needs" + 0.005*"well" + 0.004*"plans" + 0.004*"22" + 0.004*"January" + 0.004*"positive" + 0.004*"appropriate" + 0.004*"Council"
+2024-05-13 12:43:03,913 - topic #2 (0.333): 0.013*"’" + 0.010*"needs" + 0.008*"well" + 0.006*"practice" + 0.005*"Plymouth" + 0.005*"appropriate" + 0.005*"plans" + 0.005*"education" + 0.005*"timely" + 0.004*"benefit"
+2024-05-13 12:43:03,913 - topic diff=0.840455, rho=1.000000
+2024-05-13 12:43:03,913 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1232, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:03.913938', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:04,901 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:04,901 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:04,901 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:04,902 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:04,902 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:04,902 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:04,902 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:04,902 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:04,902 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:04,902 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:04,903 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:04,903 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:06,793 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:06,795 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)
+2024-05-13 12:43:06,795 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-05-13T12:43:06.795620', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:06,796 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:06,797 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:06,797 - using serial LDA version on this node
+2024-05-13 12:43:06,797 - 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
+2024-05-13 12:43:06,797 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:06,801 - -8.107 per-word bound, 275.6 perplexity estimate based on a held-out corpus of 1 documents with 2738 words
+2024-05-13 12:43:06,801 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:06,803 - topic #0 (0.333): 0.022*"’" + 0.008*"well" + 0.008*"care-experienced" + 0.007*"needs" + 0.007*"Portsmouth" + 0.006*"family" + 0.005*"need" + 0.005*"health" + 0.005*"practice" + 0.005*"plans"
+2024-05-13 12:43:06,803 - topic #1 (0.333): 0.016*"’" + 0.008*"care-experienced" + 0.007*"needs" + 0.007*"Portsmouth" + 0.006*"well" + 0.006*"plans" + 0.005*"health" + 0.005*"family" + 0.004*"risk" + 0.004*"15"
+2024-05-13 12:43:06,803 - topic #2 (0.333): 0.011*"’" + 0.008*"care-experienced" + 0.007*"well" + 0.006*"Portsmouth" + 0.005*"health" + 0.005*"needs" + 0.005*"plans" + 0.005*"family" + 0.005*"risk" + 0.004*"leaders"
+2024-05-13 12:43:06,803 - topic diff=0.794201, rho=1.000000
+2024-05-13 12:43:06,803 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1223, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:06.803859', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:07,924 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:07,925 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:07,925 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:07,925 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:07,925 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:07,925 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:07,926 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:07,926 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:07,926 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:07,926 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:07,926 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:07,926 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:09,686 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:09,689 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)
+2024-05-13 12:43:09,689 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-05-13T12:43:09.689221', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:09,690 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:09,690 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:09,690 - using serial LDA version on this node
+2024-05-13 12:43:09,691 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:09,691 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:09,694 - -8.001 per-word bound, 256.1 perplexity estimate based on a held-out corpus of 1 documents with 2272 words
+2024-05-13 12:43:09,694 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:09,696 - topic #0 (0.333): 0.020*"’" + 0.008*"number" + 0.007*"quality" + 0.007*"well" + 0.006*"plans" + 0.006*"good" + 0.006*"practice" + 0.006*"effective" + 0.005*"needs" + 0.005*"need"
+2024-05-13 12:43:09,696 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.006*"quality" + 0.006*"number" + 0.006*"effective" + 0.006*"plans" + 0.006*"good" + 0.006*"need" + 0.004*"arrangements" + 0.004*"timely"
+2024-05-13 12:43:09,696 - topic #2 (0.333): 0.014*"’" + 0.006*"well" + 0.006*"quality" + 0.005*"plans" + 0.005*"timely" + 0.005*"number" + 0.005*"good" + 0.004*"need" + 0.004*"always" + 0.004*"progress"
+2024-05-13 12:43:09,696 - topic diff=0.779718, rho=1.000000
+2024-05-13 12:43:09,696 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1067, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:09.696832', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:10,908 - Inspection date 2019-09-16 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:10,909 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:10,909 - Inspection date 2019-09-16 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:10,909 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:10,909 - Inspection date 2019-09-16 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:10,909 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:10,910 - Inspection date 2019-09-16 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:10,910 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:10,910 - Inspection date 2019-09-16 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:10,910 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:10,910 - Inspection date 2019-09-16 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:10,910 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:12,783 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:12,786 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)
+2024-05-13 12:43:12,787 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-05-13T12:43:12.787286', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:12,789 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:12,789 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:12,789 - using serial LDA version on this node
+2024-05-13 12:43:12,790 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:12,790 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:12,796 - -8.007 per-word bound, 257.2 perplexity estimate based on a held-out corpus of 1 documents with 2515 words
+2024-05-13 12:43:12,796 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:12,799 - topic #0 (0.333): 0.021*"’" + 0.007*"plans" + 0.006*"However" + 0.005*"needs" + 0.005*"leaders" + 0.005*"20" + 0.005*"practice" + 0.005*"consistently" + 0.005*"July" + 0.004*"ensure"
+2024-05-13 12:43:12,799 - topic #1 (0.333): 0.013*"’" + 0.007*"leaders" + 0.006*"needs" + 0.006*"2022" + 0.006*"risk" + 0.005*"Redcar" + 0.005*"consistently" + 0.005*"carers" + 0.005*"Cleveland" + 0.005*"plans"
+2024-05-13 12:43:12,799 - topic #2 (0.333): 0.018*"’" + 0.006*"However" + 0.006*"leaders" + 0.006*"consistently" + 0.005*"practice" + 0.005*"needs" + 0.004*"carers" + 0.004*"20" + 0.004*"plans" + 0.004*"Redcar"
+2024-05-13 12:43:12,799 - topic diff=0.798088, rho=1.000000
+2024-05-13 12:43:12,800 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1112, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:12.800068', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:14,055 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:14,055 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:14,056 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:14,056 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:14,056 - Inspection date None / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:14,056 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:14,056 - Inspection date None / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:14,057 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:14,057 - Inspection date None / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:14,057 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:14,057 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:14,057 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:15,752 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:15,754 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)
+2024-05-13 12:43:15,755 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-05-13T12:43:15.755029', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:15,756 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:15,756 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:15,756 - using serial LDA version on this node
+2024-05-13 12:43:15,757 - 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
+2024-05-13 12:43:15,757 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:15,761 - -8.031 per-word bound, 261.6 perplexity estimate based on a held-out corpus of 1 documents with 2656 words
+2024-05-13 12:43:15,761 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:15,762 - topic #0 (0.333): 0.018*"’" + 0.010*"practice" + 0.008*"experienced" + 0.007*"needs" + 0.006*"plans" + 0.006*"quality" + 0.005*"response" + 0.005*"consistently" + 0.004*"3" + 0.004*"well"
+2024-05-13 12:43:15,762 - topic #1 (0.333): 0.018*"’" + 0.009*"experienced" + 0.008*"needs" + 0.007*"practice" + 0.006*"response" + 0.005*"good" + 0.005*"plans" + 0.004*"23" + 0.004*"quality" + 0.004*"January"
+2024-05-13 12:43:15,763 - topic #2 (0.333): 0.024*"’" + 0.011*"experienced" + 0.008*"needs" + 0.007*"practice" + 0.007*"consistently" + 0.006*"plans" + 0.006*"response" + 0.006*"Rochdale" + 0.005*"well" + 0.005*"good"
+2024-05-13 12:43:15,763 - topic diff=0.817524, rho=1.000000
+2024-05-13 12:43:15,763 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1150, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:15.763300', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:16,798 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:16,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:16,799 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:16,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:16,799 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:16,799 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:16,800 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:16,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:16,800 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:16,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:16,800 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:16,800 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:18,399 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:18,401 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)
+2024-05-13 12:43:18,402 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-05-13T12:43:18.402052', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:18,403 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:18,403 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:18,403 - using serial LDA version on this node
+2024-05-13 12:43:18,403 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:18,404 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:18,407 - -8.063 per-word bound, 267.4 perplexity estimate based on a held-out corpus of 1 documents with 2366 words
+2024-05-13 12:43:18,407 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:18,409 - topic #0 (0.333): 0.011*"’" + 0.007*"Rotherham" + 0.006*"needs" + 0.005*"well" + 0.005*"good" + 0.005*"Council" + 0.004*"ensure" + 0.004*"plans" + 0.004*"However" + 0.004*"27"
+2024-05-13 12:43:18,409 - topic #1 (0.333): 0.019*"’" + 0.010*"Rotherham" + 0.006*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"ensure" + 0.005*"good" + 0.005*"Council" + 0.004*"1" + 0.004*"clear"
+2024-05-13 12:43:18,409 - topic #2 (0.333): 0.014*"’" + 0.008*"Rotherham" + 0.007*"needs" + 0.005*"good" + 0.005*"However" + 0.004*"Council" + 0.004*"Borough" + 0.004*"well" + 0.004*"Metropolitan" + 0.004*"ensure"
+2024-05-13 12:43:18,409 - topic diff=0.772925, rho=1.000000
+2024-05-13 12:43:18,410 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1127, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:18.409982', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:19,380 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:19,380 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:19,381 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:19,381 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:19,381 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:19,381 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:19,381 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:19,381 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:19,381 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:19,382 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:19,382 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:19,382 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:21,132 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:21,135 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)
+2024-05-13 12:43:21,135 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-05-13T12:43:21.135423', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:21,136 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:21,136 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:21,136 - using serial LDA version on this node
+2024-05-13 12:43:21,137 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:21,137 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:21,141 - -8.049 per-word bound, 264.9 perplexity estimate based on a held-out corpus of 1 documents with 2380 words
+2024-05-13 12:43:21,141 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:21,142 - topic #0 (0.333): 0.012*"well" + 0.010*"’" + 0.009*"practice" + 0.007*"strong" + 0.007*"highly" + 0.005*"effective" + 0.005*"leaders" + 0.005*"needs" + 0.004*"need" + 0.004*"high"
+2024-05-13 12:43:21,142 - topic #1 (0.333): 0.016*"well" + 0.011*"’" + 0.010*"practice" + 0.007*"highly" + 0.006*"strong" + 0.006*"needs" + 0.005*"leaders" + 0.004*"professionals" + 0.004*"high" + 0.004*"effective"
+2024-05-13 12:43:21,143 - topic #2 (0.333): 0.013*"’" + 0.012*"practice" + 0.012*"well" + 0.008*"highly" + 0.006*"effective" + 0.006*"strong" + 0.006*"needs" + 0.005*"leaders" + 0.004*"risk" + 0.004*"high"
+2024-05-13 12:43:21,143 - topic diff=0.771913, rho=1.000000
+2024-05-13 12:43:21,143 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1119, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:21.143410', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:22,324 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:22,324 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:22,324 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:22,325 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:22,325 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:22,325 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:22,325 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:22,325 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:22,325 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:22,326 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:22,326 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:22,326 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:24,592 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:24,595 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)
+2024-05-13 12:43:24,596 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-05-13T12:43:24.596138', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:24,597 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:24,597 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:24,597 - using serial LDA version on this node
+2024-05-13 12:43:24,598 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:24,598 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:24,602 - -8.065 per-word bound, 267.7 perplexity estimate based on a held-out corpus of 1 documents with 2257 words
+2024-05-13 12:43:24,602 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:24,604 - topic #0 (0.333): 0.016*"’" + 0.011*"well" + 0.008*"plans" + 0.007*"needs" + 0.005*"supported" + 0.005*"practice" + 0.005*"good" + 0.005*"effective" + 0.005*"parents" + 0.004*"Kingston"
+2024-05-13 12:43:24,604 - topic #1 (0.333): 0.012*"’" + 0.008*"plans" + 0.007*"well" + 0.006*"good" + 0.006*"needs" + 0.005*"clear" + 0.004*"effective" + 0.004*"risk" + 0.004*"need" + 0.004*"range"
+2024-05-13 12:43:24,604 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"plans" + 0.008*"well" + 0.005*"good" + 0.004*"effective" + 0.004*"need" + 0.004*"clear" + 0.004*"range" + 0.004*"parents"
+2024-05-13 12:43:24,605 - topic diff=0.751243, rho=1.000000
+2024-05-13 12:43:24,605 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1107, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:24.605235', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:25,884 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:25,885 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:25,885 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:25,885 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:25,886 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:25,886 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:25,886 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:25,886 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:25,886 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:25,887 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:25,887 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:25,887 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:27,445 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:27,448 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)
+2024-05-13 12:43:27,448 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-05-13T12:43:27.448547', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:27,449 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:27,449 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:27,450 - using serial LDA version on this node
+2024-05-13 12:43:27,450 - 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
+2024-05-13 12:43:27,450 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:27,454 - -8.118 per-word bound, 277.9 perplexity estimate based on a held-out corpus of 1 documents with 2088 words
+2024-05-13 12:43:27,454 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:27,455 - topic #0 (0.333): 0.013*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"quality" + 0.005*"use" + 0.004*"health" + 0.004*"effective" + 0.004*"However" + 0.004*"plans" + 0.004*"benefit"
+2024-05-13 12:43:27,455 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"plans" + 0.005*"quality" + 0.004*"benefit" + 0.004*"effective" + 0.004*"needs" + 0.004*"informed" + 0.004*"timely" + 0.004*"need"
+2024-05-13 12:43:27,456 - topic #2 (0.333): 0.010*"’" + 0.005*"needs" + 0.004*"information" + 0.004*"quality" + 0.004*"plans" + 0.004*"well" + 0.004*"always" + 0.003*"early" + 0.003*"actions" + 0.003*"benefit"
+2024-05-13 12:43:27,456 - topic diff=0.715434, rho=1.000000
+2024-05-13 12:43:27,456 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1109, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:27.456354', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:28,681 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:28,681 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:28,682 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:28,682 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:28,682 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:28,682 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:28,682 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:28,682 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:28,683 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:28,683 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:28,683 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:28,683 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:30,140 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:30,144 - built Dictionary<1018 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2144 corpus positions)
+2024-05-13 12:43:30,144 - Dictionary lifecycle event {'msg': "built Dictionary<1018 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2144 corpus positions)", 'datetime': '2024-05-13T12:43:30.144815', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:30,146 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:30,146 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:30,146 - using serial LDA version on this node
+2024-05-13 12:43:30,146 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:30,147 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:30,150 - -7.959 per-word bound, 248.9 perplexity estimate based on a held-out corpus of 1 documents with 2144 words
+2024-05-13 12:43:30,150 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:30,152 - topic #0 (0.333): 0.011*"’" + 0.011*"well" + 0.008*"needs" + 0.007*"good" + 0.006*"team" + 0.006*"practice" + 0.005*"ensure" + 0.005*"effective" + 0.005*"protection" + 0.005*"need"
+2024-05-13 12:43:30,152 - topic #1 (0.333): 0.009*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"good" + 0.005*"team" + 0.005*"plans" + 0.005*"need" + 0.005*"ensure" + 0.004*"practice" + 0.004*"protection"
+2024-05-13 12:43:30,153 - topic #2 (0.333): 0.015*"’" + 0.011*"needs" + 0.011*"well" + 0.008*"good" + 0.008*"need" + 0.007*"practice" + 0.007*"team" + 0.007*"enough" + 0.006*"protection" + 0.006*"effective"
+2024-05-13 12:43:30,153 - topic diff=0.787973, rho=1.000000
+2024-05-13 12:43:30,153 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1018, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:30.153285', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:31,193 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:31,193 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:31,194 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:31,194 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:31,194 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:31,194 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:31,195 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:31,195 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:31,195 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:31,195 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:31,195 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:31,196 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:32,593 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:32,595 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)
+2024-05-13 12:43:32,596 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-05-13T12:43:32.596124', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:32,597 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:32,597 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:32,597 - using serial LDA version on this node
+2024-05-13 12:43:32,598 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:32,598 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:32,601 - -8.009 per-word bound, 257.7 perplexity estimate based on a held-out corpus of 1 documents with 2253 words
+2024-05-13 12:43:32,601 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:32,603 - topic #0 (0.333): 0.016*"’" + 0.009*"plans" + 0.009*"needs" + 0.007*"well" + 0.007*"effective" + 0.006*"Salford" + 0.006*"planning" + 0.005*"practice" + 0.005*"quality" + 0.005*"experiences"
+2024-05-13 12:43:32,603 - topic #1 (0.333): 0.010*"’" + 0.006*"effective" + 0.005*"well" + 0.005*"plans" + 0.005*"needs" + 0.004*"Salford" + 0.004*"leaders" + 0.004*"Council" + 0.004*"planning" + 0.004*"appropriate"
+2024-05-13 12:43:32,603 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.007*"plans" + 0.007*"needs" + 0.006*"Salford" + 0.005*"effective" + 0.005*"practice" + 0.005*"progress" + 0.005*"6" + 0.005*"ensure"
+2024-05-13 12:43:32,603 - topic diff=0.810498, rho=1.000000
+2024-05-13 12:43:32,603 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1069, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:32.603787', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:33,563 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:33,563 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:33,563 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:33,563 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:33,563 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:33,564 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:33,564 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:33,564 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:33,564 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:33,564 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:33,564 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:33,564 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:35,602 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:35,606 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)
+2024-05-13 12:43:35,606 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-05-13T12:43:35.606445', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:35,607 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:35,608 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:35,608 - using serial LDA version on this node
+2024-05-13 12:43:35,608 - 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
+2024-05-13 12:43:35,609 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:35,614 - -7.949 per-word bound, 247.1 perplexity estimate based on a held-out corpus of 1 documents with 2066 words
+2024-05-13 12:43:35,614 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:35,615 - topic #0 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"Sandwell" + 0.007*"plans" + 0.006*"well" + 0.006*"quality" + 0.005*"Trust" + 0.004*"changes" + 0.004*"number" + 0.004*"2022"
+2024-05-13 12:43:35,615 - topic #1 (0.333): 0.015*"’" + 0.008*"Sandwell" + 0.007*"well" + 0.007*"plans" + 0.006*"needs" + 0.005*"quality" + 0.004*"effective" + 0.004*"20" + 0.004*"progress" + 0.004*"education"
+2024-05-13 12:43:35,615 - topic #2 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"plans" + 0.007*"Sandwell" + 0.006*"quality" + 0.006*"well" + 0.005*"Trust" + 0.005*"education" + 0.005*"20" + 0.005*"progress"
+2024-05-13 12:43:35,616 - topic diff=0.765507, rho=1.000000
+2024-05-13 12:43:35,616 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=995, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:35.616208', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:36,545 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:36,545 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:36,546 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:36,546 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:36,546 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:36,546 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:36,546 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:36,547 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:36,547 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:36,547 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:36,547 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:36,547 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:38,403 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:38,406 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)
+2024-05-13 12:43:38,406 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-05-13T12:43:38.406385', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:38,407 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:38,407 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:38,407 - using serial LDA version on this node
+2024-05-13 12:43:38,408 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:38,408 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:38,411 - -7.928 per-word bound, 243.5 perplexity estimate based on a held-out corpus of 1 documents with 2300 words
+2024-05-13 12:43:38,411 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:38,413 - topic #0 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"lack" + 0.006*"practice" + 0.006*"protection" + 0.005*"including" + 0.005*"oversight" + 0.005*"timely" + 0.005*"always" + 0.005*"4"
+2024-05-13 12:43:38,413 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.006*"practice" + 0.006*"oversight" + 0.005*"◼" + 0.005*"many" + 0.005*"protection" + 0.005*"including" + 0.005*"plans" + 0.005*"management"
+2024-05-13 12:43:38,413 - topic #2 (0.333): 0.014*"’" + 0.009*"needs" + 0.005*"oversight" + 0.005*"practice" + 0.005*"management" + 0.005*"Sefton" + 0.005*"lack" + 0.004*"March" + 0.004*"timely" + 0.004*"plans"
+2024-05-13 12:43:38,413 - topic diff=0.794699, rho=1.000000
+2024-05-13 12:43:38,413 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1023, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:38.413832', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:39,438 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:39,438 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:39,438 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:39,438 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:39,439 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:39,439 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:39,439 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:39,439 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:39,439 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:39,439 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:39,439 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:39,440 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:40,966 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:40,968 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)
+2024-05-13 12:43:40,968 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-05-13T12:43:40.968773', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:40,969 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:40,970 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:40,970 - using serial LDA version on this node
+2024-05-13 12:43:40,970 - 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
+2024-05-13 12:43:40,970 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:40,974 - -8.067 per-word bound, 268.1 perplexity estimate based on a held-out corpus of 1 documents with 2327 words
+2024-05-13 12:43:40,974 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:40,975 - topic #0 (0.333): 0.019*"’" + 0.010*"Sheffield" + 0.008*"needs" + 0.006*"leaders" + 0.006*"well" + 0.006*"health" + 0.005*"practice" + 0.005*"quality" + 0.005*"11" + 0.004*"good"
+2024-05-13 12:43:40,976 - topic #1 (0.333): 0.017*"’" + 0.011*"Sheffield" + 0.008*"needs" + 0.006*"well" + 0.006*"practice" + 0.005*"adviser" + 0.004*"ensure" + 0.004*"2023" + 0.004*"leaders" + 0.004*"effective"
+2024-05-13 12:43:40,976 - topic #2 (0.333): 0.024*"’" + 0.012*"Sheffield" + 0.009*"needs" + 0.007*"well" + 0.006*"leaders" + 0.005*"health" + 0.005*"practice" + 0.005*"plans" + 0.005*"experiences" + 0.004*"22"
+2024-05-13 12:43:40,976 - topic diff=0.766779, rho=1.000000
+2024-05-13 12:43:40,976 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1124, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:40.976596', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:41,905 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:41,905 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:41,906 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:41,906 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:41,906 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:41,906 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:41,906 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:41,906 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:41,907 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:41,907 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:41,907 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:41,907 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:43,395 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:43,397 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)
+2024-05-13 12:43:43,397 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-05-13T12:43:43.397821', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:43,398 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:43,398 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:43,399 - using serial LDA version on this node
+2024-05-13 12:43:43,399 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:43,399 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:43,402 - -7.957 per-word bound, 248.5 perplexity estimate based on a held-out corpus of 1 documents with 1749 words
+2024-05-13 12:43:43,403 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:43,404 - topic #0 (0.333): 0.014*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"Shropshire" + 0.005*"7" + 0.005*"plans" + 0.005*"progress" + 0.005*"2022" + 0.005*"making" + 0.004*"practice"
+2024-05-13 12:43:43,404 - topic #1 (0.333): 0.015*"’" + 0.009*"needs" + 0.008*"Shropshire" + 0.006*"well" + 0.006*"2022" + 0.005*"progress" + 0.005*"leaders" + 0.005*"effectively" + 0.005*"plans" + 0.005*"practice"
+2024-05-13 12:43:43,404 - topic #2 (0.333): 0.021*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"Shropshire" + 0.006*"progress" + 0.006*"plans" + 0.005*"making" + 0.005*"11" + 0.005*"7" + 0.004*"training"
+2024-05-13 12:43:43,404 - topic diff=0.716373, rho=1.000000
+2024-05-13 12:43:43,405 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=939, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:43.405025', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:44,393 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:44,393 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:44,394 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:44,394 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:44,395 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:44,395 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:44,395 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:44,395 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:44,396 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:44,396 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:44,396 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:44,396 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:46,025 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:46,028 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)
+2024-05-13 12:43:46,028 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-05-13T12:43:46.028447', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:46,029 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:46,029 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:46,030 - using serial LDA version on this node
+2024-05-13 12:43:46,030 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:46,030 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:46,034 - -8.044 per-word bound, 263.9 perplexity estimate based on a held-out corpus of 1 documents with 2352 words
+2024-05-13 12:43:46,034 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:46,036 - topic #0 (0.333): 0.014*"’" + 0.009*"Slough" + 0.006*"plans" + 0.006*"needs" + 0.005*"3" + 0.005*"2023" + 0.005*"impact" + 0.005*"practice" + 0.004*"However" + 0.004*"quality"
+2024-05-13 12:43:46,036 - topic #1 (0.333): 0.013*"’" + 0.006*"needs" + 0.006*"Slough" + 0.006*"plans" + 0.005*"practice" + 0.005*"leaders" + 0.004*"senior" + 0.004*"3" + 0.004*"need" + 0.004*"quality"
+2024-05-13 12:43:46,036 - topic #2 (0.333): 0.019*"’" + 0.008*"quality" + 0.008*"Slough" + 0.006*"practice" + 0.006*"needs" + 0.006*"plans" + 0.005*"supported" + 0.005*"impact" + 0.005*"23" + 0.005*"However"
+2024-05-13 12:43:46,036 - topic diff=0.782643, rho=1.000000
+2024-05-13 12:43:46,036 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1113, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:46.036879', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:46,983 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:46,983 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:46,984 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:46,984 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:46,984 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:46,984 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:46,984 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:46,984 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:46,984 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:46,985 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:46,985 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:46,985 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:48,822 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:48,826 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)
+2024-05-13 12:43:48,826 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-05-13T12:43:48.826463', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:48,828 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:48,828 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:48,828 - using serial LDA version on this node
+2024-05-13 12:43:48,829 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:48,829 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:48,835 - -7.918 per-word bound, 241.9 perplexity estimate based on a held-out corpus of 1 documents with 2163 words
+2024-05-13 12:43:48,836 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:48,838 - topic #0 (0.333): 0.014*"’" + 0.012*"lack" + 0.010*"2022" + 0.007*"Solihull" + 0.006*"risk" + 0.006*"quality" + 0.006*"need" + 0.005*"significant" + 0.005*"timely" + 0.005*"practice"
+2024-05-13 12:43:48,838 - topic #1 (0.333): 0.018*"’" + 0.009*"lack" + 0.008*"2022" + 0.007*"need" + 0.006*"experiences" + 0.005*"practice" + 0.005*"Solihull" + 0.005*"risk" + 0.005*"quality" + 0.005*"means"
+2024-05-13 12:43:48,838 - topic #2 (0.333): 0.014*"’" + 0.010*"lack" + 0.006*"2022" + 0.006*"Solihull" + 0.005*"risk" + 0.005*"effective" + 0.005*"quality" + 0.005*"practice" + 0.004*"experiences" + 0.004*"need"
+2024-05-13 12:43:48,839 - topic diff=0.791615, rho=1.000000
+2024-05-13 12:43:48,839 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=996, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:48.839209', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:49,812 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:49,812 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:49,813 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:49,813 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:49,813 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:49,813 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:49,813 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:49,813 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:49,814 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:49,814 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:49,814 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:49,814 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:51,793 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:51,795 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)
+2024-05-13 12:43:51,795 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-05-13T12:43:51.795816', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:51,796 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:51,796 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:51,797 - using serial LDA version on this node
+2024-05-13 12:43:51,797 - 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
+2024-05-13 12:43:51,797 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:51,804 - -7.921 per-word bound, 242.4 perplexity estimate based on a held-out corpus of 1 documents with 2181 words
+2024-05-13 12:43:51,804 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:51,806 - topic #0 (0.333): 0.015*"’" + 0.010*"needs" + 0.008*"well" + 0.007*"plans" + 0.006*"good" + 0.005*"number" + 0.005*"leaders" + 0.005*"Somerset" + 0.005*"supported" + 0.005*"need"
+2024-05-13 12:43:51,806 - topic #1 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"needs" + 0.006*"plans" + 0.005*"Somerset" + 0.005*"positive" + 0.005*"need" + 0.004*"progress" + 0.004*"good" + 0.004*"leaders"
+2024-05-13 12:43:51,806 - topic #2 (0.333): 0.019*"’" + 0.010*"well" + 0.009*"Somerset" + 0.008*"needs" + 0.006*"good" + 0.006*"plans" + 0.006*"supported" + 0.006*"practice" + 0.006*"including" + 0.006*"progress"
+2024-05-13 12:43:51,806 - topic diff=0.807142, rho=1.000000
+2024-05-13 12:43:51,807 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:51.807120', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:52,751 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:52,752 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:52,752 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:52,752 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:52,752 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:52,752 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:52,753 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:52,753 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:52,753 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:52,753 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:52,753 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:52,753 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:54,527 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:54,529 - built Dictionary<1052 unique tokens: ['0', '016', '0161', '0300', '0–25']...> from 1 documents (total 2383 corpus positions)
+2024-05-13 12:43:54,529 - Dictionary lifecycle event {'msg': "built Dictionary<1052 unique tokens: ['0', '016', '0161', '0300', '0–25']...> from 1 documents (total 2383 corpus positions)", 'datetime': '2024-05-13T12:43:54.529674', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:54,530 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:54,531 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:54,531 - using serial LDA version on this node
+2024-05-13 12:43:54,531 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:54,531 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:54,535 - -7.945 per-word bound, 246.5 perplexity estimate based on a held-out corpus of 1 documents with 2383 words
+2024-05-13 12:43:54,535 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:54,536 - topic #0 (0.333): 0.010*"quality" + 0.010*"’" + 0.009*"well" + 0.008*"plans" + 0.008*"good" + 0.008*"leaders" + 0.005*"needs" + 0.005*"practice" + 0.005*"timeliness" + 0.005*"Senior"
+2024-05-13 12:43:54,536 - topic #1 (0.333): 0.012*"well" + 0.012*"quality" + 0.010*"leaders" + 0.009*"’" + 0.008*"timely" + 0.008*"plans" + 0.006*"progress" + 0.006*"good" + 0.006*"needs" + 0.005*"practice"
+2024-05-13 12:43:54,537 - topic #2 (0.333): 0.010*"well" + 0.009*"quality" + 0.007*"plans" + 0.007*"good" + 0.007*"’" + 0.006*"leaders" + 0.005*"needs" + 0.005*"impact" + 0.005*"progress" + 0.005*"timely"
+2024-05-13 12:43:54,537 - topic diff=0.798439, rho=1.000000
+2024-05-13 12:43:54,537 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1052, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:54.537398', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:55,929 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:55,930 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:55,930 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:55,930 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:55,930 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:55,930 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:55,930 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:55,931 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:55,931 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:55,931 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:55,931 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:55,931 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:57,311 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:43:57,313 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions)
+2024-05-13 12:43:57,314 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-05-13T12:43:57.313982', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:57,315 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:43:57,315 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:43:57,315 - using serial LDA version on this node
+2024-05-13 12:43:57,315 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:43:57,315 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:43:57,319 - -7.889 per-word bound, 237.1 perplexity estimate based on a held-out corpus of 1 documents with 2189 words
+2024-05-13 12:43:57,319 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:43:57,320 - topic #0 (0.333): 0.026*"’" + 0.010*"Tyneside" + 0.008*"needs" + 0.007*"South" + 0.006*"oversight" + 0.005*"effective" + 0.005*"risk" + 0.005*"management" + 0.005*"practice" + 0.005*"9"
+2024-05-13 12:43:57,320 - topic #1 (0.333): 0.027*"’" + 0.009*"needs" + 0.008*"South" + 0.006*"Tyneside" + 0.006*"However" + 0.005*"carers" + 0.005*"5" + 0.005*"management" + 0.005*"homes" + 0.005*"progress"
+2024-05-13 12:43:57,321 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.006*"South" + 0.005*"Tyneside" + 0.005*"2022" + 0.004*"management" + 0.004*"carers" + 0.004*"9" + 0.004*"However" + 0.004*"effective"
+2024-05-13 12:43:57,321 - topic diff=0.802604, rho=1.000000
+2024-05-13 12:43:57,321 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=981, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:43:57.321358', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:43:58,295 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:43:58,296 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:58,296 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:43:58,296 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:58,297 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:43:58,297 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:58,297 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:43:58,297 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:58,298 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:43:58,298 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:43:58,298 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:43:58,298 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:00,074 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:00,077 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)
+2024-05-13 12:44:00,077 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-05-13T12:44:00.077879', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:00,079 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:00,079 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:00,079 - using serial LDA version on this node
+2024-05-13 12:44:00,079 - 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
+2024-05-13 12:44:00,079 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:00,083 - -8.144 per-word bound, 282.8 perplexity estimate based on a held-out corpus of 1 documents with 2318 words
+2024-05-13 12:44:00,083 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:00,085 - topic #0 (0.333): 0.016*"’" + 0.005*"plans" + 0.005*"improve" + 0.005*"including" + 0.005*"progress" + 0.004*"5" + 0.004*"Southampton" + 0.004*"16" + 0.004*"experiences" + 0.004*"leaders"
+2024-05-13 12:44:00,085 - topic #1 (0.333): 0.011*"’" + 0.005*"progress" + 0.005*"Southampton" + 0.004*"16" + 0.004*"plans" + 0.004*"experiences" + 0.004*"including" + 0.004*"improve" + 0.004*"June" + 0.004*"needs"
+2024-05-13 12:44:00,085 - topic #2 (0.333): 0.019*"’" + 0.007*"plans" + 0.007*"Southampton" + 0.005*"needs" + 0.005*"timely" + 0.005*"5" + 0.005*"well" + 0.005*"improve" + 0.004*"progress" + 0.004*"provide"
+2024-05-13 12:44:00,086 - topic diff=0.751984, rho=1.000000
+2024-05-13 12:44:00,086 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1178, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:00.086162', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:01,015 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:01,015 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:01,016 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:01,016 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:01,016 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:01,016 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:01,016 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:01,016 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:01,017 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:01,017 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:01,017 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:01,017 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:02,724 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:02,726 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)
+2024-05-13 12:44:02,726 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-05-13T12:44:02.726462', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:02,727 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:02,727 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:02,727 - using serial LDA version on this node
+2024-05-13 12:44:02,728 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:02,728 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:02,731 - -7.943 per-word bound, 246.0 perplexity estimate based on a held-out corpus of 1 documents with 2086 words
+2024-05-13 12:44:02,731 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:02,733 - topic #0 (0.333): 0.016*"’" + 0.009*"planning" + 0.006*"practice" + 0.006*"leaders" + 0.006*"quality" + 0.006*"number" + 0.006*"always" + 0.006*"effective" + 0.006*"carers" + 0.005*"However"
+2024-05-13 12:44:02,733 - topic #1 (0.333): 0.012*"’" + 0.007*"practice" + 0.007*"planning" + 0.007*"quality" + 0.006*"protection" + 0.005*"number" + 0.005*"risk" + 0.005*"effective" + 0.005*"leaders" + 0.004*"within"
+2024-05-13 12:44:02,733 - topic #2 (0.333): 0.011*"’" + 0.007*"practice" + 0.007*"quality" + 0.006*"planning" + 0.006*"leaders" + 0.006*"within" + 0.005*"well" + 0.005*"protection" + 0.005*"good" + 0.005*"needs"
+2024-05-13 12:44:02,733 - topic diff=0.770959, rho=1.000000
+2024-05-13 12:44:02,733 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:02.733889', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:05,167 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:05,167 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:05,173 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:05,173 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:05,173 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:05,173 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:05,174 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:05,174 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:05,174 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:05,174 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:05,175 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:05,175 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:06,773 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:06,775 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)
+2024-05-13 12:44:06,775 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-05-13T12:44:06.775485', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:06,776 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:06,776 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:06,776 - using serial LDA version on this node
+2024-05-13 12:44:06,777 - 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
+2024-05-13 12:44:06,777 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:06,781 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2218 words
+2024-05-13 12:44:06,781 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:06,782 - topic #0 (0.333): 0.011*"’" + 0.007*"St" + 0.006*"21" + 0.005*"progress" + 0.005*"need" + 0.005*"needs" + 0.005*"well" + 0.004*"Helens" + 0.004*"July" + 0.004*"10"
+2024-05-13 12:44:06,782 - topic #1 (0.333): 0.016*"’" + 0.008*"Helens" + 0.008*"needs" + 0.007*"St" + 0.007*"progress" + 0.006*"well" + 0.006*"10" + 0.006*"need" + 0.006*"receive" + 0.005*"good"
+2024-05-13 12:44:06,783 - topic #2 (0.333): 0.019*"’" + 0.009*"Helens" + 0.008*"St" + 0.008*"needs" + 0.007*"well" + 0.006*"good" + 0.006*"receive" + 0.005*"21" + 0.005*"effective" + 0.005*"risk"
+2024-05-13 12:44:06,783 - topic diff=0.773044, rho=1.000000
+2024-05-13 12:44:06,783 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1092, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:06.783400', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:07,873 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:07,873 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:07,874 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:07,874 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:07,874 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:07,874 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:07,874 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:07,874 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:07,875 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:07,875 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:07,875 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:07,875 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:09,309 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:09,312 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)
+2024-05-13 12:44:09,313 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-05-13T12:44:09.313231', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:09,315 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:09,315 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:09,315 - using serial LDA version on this node
+2024-05-13 12:44:09,316 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:09,316 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:09,322 - -7.997 per-word bound, 255.4 perplexity estimate based on a held-out corpus of 1 documents with 2334 words
+2024-05-13 12:44:09,323 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:09,325 - topic #0 (0.333): 0.019*"’" + 0.014*"needs" + 0.007*"quality" + 0.007*"health" + 0.007*"Staffordshire" + 0.006*"progress" + 0.006*"oversight" + 0.005*"practice" + 0.005*"10" + 0.005*"ensure"
+2024-05-13 12:44:09,325 - topic #1 (0.333): 0.011*"’" + 0.008*"needs" + 0.006*"ensure" + 0.005*"practice" + 0.005*"progress" + 0.004*"oversight" + 0.004*"Staffordshire" + 0.004*"quality" + 0.004*"plans" + 0.004*"health"
+2024-05-13 12:44:09,325 - topic #2 (0.333): 0.018*"’" + 0.011*"needs" + 0.006*"practice" + 0.006*"quality" + 0.006*"oversight" + 0.005*"ensure" + 0.005*"plans" + 0.005*"progress" + 0.005*"health" + 0.004*"Staffordshire"
+2024-05-13 12:44:09,325 - topic diff=0.811271, rho=1.000000
+2024-05-13 12:44:09,326 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1076, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:09.326168', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:10,309 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:10,309 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:10,310 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:10,310 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:10,310 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:10,310 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:10,311 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:10,311 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:10,311 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:10,316 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:10,316 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:10,316 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:11,754 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:11,756 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)
+2024-05-13 12:44:11,756 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-05-13T12:44:11.756961', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:11,758 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:11,758 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:11,758 - using serial LDA version on this node
+2024-05-13 12:44:11,758 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:11,758 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:11,762 - -7.973 per-word bound, 251.3 perplexity estimate based on a held-out corpus of 1 documents with 2316 words
+2024-05-13 12:44:11,762 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:11,764 - topic #0 (0.333): 0.010*"’" + 0.008*"well" + 0.007*"practice" + 0.007*"Stockport" + 0.006*"strong" + 0.005*"risk" + 0.005*"needs" + 0.005*"quality" + 0.004*"28" + 0.004*"ensure"
+2024-05-13 12:44:11,764 - topic #1 (0.333): 0.011*"’" + 0.009*"well" + 0.008*"practice" + 0.007*"Stockport" + 0.006*"needs" + 0.006*"plans" + 0.005*"risk" + 0.005*"ensure" + 0.005*"leaders" + 0.005*"1"
+2024-05-13 12:44:11,764 - topic #2 (0.333): 0.012*"’" + 0.007*"well" + 0.006*"strong" + 0.006*"needs" + 0.006*"practice" + 0.005*"Stockport" + 0.005*"plans" + 0.005*"response" + 0.004*"leaders" + 0.004*"quality"
+2024-05-13 12:44:11,764 - topic diff=0.790721, rho=1.000000
+2024-05-13 12:44:11,764 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1060, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:11.764898', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:12,758 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:12,759 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:12,759 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:12,759 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:12,759 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:12,759 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:12,760 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:12,760 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:12,760 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:12,760 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:12,760 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:12,760 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:14,259 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:14,261 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)
+2024-05-13 12:44:14,261 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-05-13T12:44:14.261863', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:14,262 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:14,263 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:14,263 - using serial LDA version on this node
+2024-05-13 12:44:14,263 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:14,263 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:14,267 - -7.971 per-word bound, 250.9 perplexity estimate based on a held-out corpus of 1 documents with 2269 words
+2024-05-13 12:44:14,267 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:14,268 - topic #0 (0.333): 0.018*"’" + 0.008*"leaders" + 0.007*"plans" + 0.007*"needs" + 0.006*"on-Tees" + 0.006*"Stockton" + 0.005*"well" + 0.005*"quality" + 0.005*"senior" + 0.004*"good"
+2024-05-13 12:44:14,268 - topic #1 (0.333): 0.022*"’" + 0.010*"leaders" + 0.008*"plans" + 0.007*"quality" + 0.007*"needs" + 0.006*"Stockton" + 0.006*"well" + 0.006*"on-Tees" + 0.006*"senior" + 0.006*"good"
+2024-05-13 12:44:14,269 - topic #2 (0.333): 0.018*"’" + 0.010*"plans" + 0.007*"leaders" + 0.007*"well" + 0.006*"good" + 0.006*"needs" + 0.006*"on-Tees" + 0.005*"Stockton" + 0.005*"17" + 0.005*"carers"
+2024-05-13 12:44:14,269 - topic diff=0.769571, rho=1.000000
+2024-05-13 12:44:14,269 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1044, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:14.269325', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:15,359 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:15,360 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:15,360 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:15,360 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:15,361 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:15,361 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:15,361 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:15,361 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:15,362 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:15,362 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:15,362 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:15,362 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:17,249 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:17,251 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)
+2024-05-13 12:44:17,251 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-05-13T12:44:17.251450', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:17,252 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:17,252 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:17,252 - using serial LDA version on this node
+2024-05-13 12:44:17,253 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:17,253 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:17,256 - -7.902 per-word bound, 239.2 perplexity estimate based on a held-out corpus of 1 documents with 2165 words
+2024-05-13 12:44:17,256 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:17,258 - topic #0 (0.333): 0.018*"’" + 0.009*"needs" + 0.009*"on-Trent" + 0.008*"well" + 0.008*"Stoke" + 0.007*"However" + 0.007*"plans" + 0.006*"protection" + 0.005*"progress" + 0.005*"ensure"
+2024-05-13 12:44:17,258 - topic #1 (0.333): 0.014*"’" + 0.008*"needs" + 0.007*"Stoke" + 0.007*"plans" + 0.006*"However" + 0.006*"on-Trent" + 0.006*"ensure" + 0.005*"well" + 0.005*"protection" + 0.005*"quality"
+2024-05-13 12:44:17,258 - topic #2 (0.333): 0.020*"’" + 0.008*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"However" + 0.005*"ensure" + 0.005*"on-Trent" + 0.005*"timely" + 0.005*"quality" + 0.005*"Stoke"
+2024-05-13 12:44:17,258 - topic diff=0.777850, rho=1.000000
+2024-05-13 12:44:17,258 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=986, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:17.258846', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:18,329 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:18,330 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:18,330 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:18,330 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:18,330 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:18,331 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:18,331 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:18,331 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:18,332 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:18,332 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:18,332 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:18,332 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:20,129 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:20,133 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)
+2024-05-13 12:44:20,133 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)", 'datetime': '2024-05-13T12:44:20.133879', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:20,135 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:20,136 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:20,136 - using serial LDA version on this node
+2024-05-13 12:44:20,137 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:20,137 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:20,143 - -8.183 per-word bound, 290.7 perplexity estimate based on a held-out corpus of 1 documents with 2286 words
+2024-05-13 12:44:20,144 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:20,146 - topic #0 (0.333): 0.012*"’" + 0.005*"progress" + 0.005*"effective" + 0.005*"well" + 0.005*"ensure" + 0.004*"practice" + 0.004*"leaders" + 0.004*"high" + 0.004*"good" + 0.004*"Suffolk"
+2024-05-13 12:44:20,146 - topic #1 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"progress" + 0.005*"leaders" + 0.005*"good" + 0.005*"effective" + 0.004*"ensure" + 0.004*"experiences" + 0.004*"need" + 0.004*"carers"
+2024-05-13 12:44:20,147 - topic #2 (0.333): 0.013*"’" + 0.006*"well" + 0.006*"progress" + 0.005*"effective" + 0.005*"good" + 0.004*"needs" + 0.004*"leaders" + 0.004*"practice" + 0.004*"ensure" + 0.004*"high"
+2024-05-13 12:44:20,147 - topic diff=0.727986, rho=1.000000
+2024-05-13 12:44:20,147 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1192, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:20.147427', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:21,289 - Got stderr: May 13, 2024 12:44:20 PM org.apache.pdfbox.pdmodel.font.PDTrueTypeFont <init>
+WARNING: Using fallback font 'LiberationSans' for 'TimesNewRomanPSMT'
+
+2024-05-13 12:44:21,296 - Inspection date 2019-04-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:21,296 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:21,296 - Inspection date 2019-04-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:21,296 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:21,296 - Inspection date 2019-04-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:21,297 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:21,297 - Inspection date 2019-04-08 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:21,297 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:21,297 - Inspection date 2019-04-08 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:21,297 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:21,297 - Inspection date 2019-04-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:21,297 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:22,863 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:22,866 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)
+2024-05-13 12:44:22,866 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-05-13T12:44:22.866659', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:22,867 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:22,867 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:22,868 - using serial LDA version on this node
+2024-05-13 12:44:22,868 - 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
+2024-05-13 12:44:22,868 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:22,872 - -8.056 per-word bound, 266.1 perplexity estimate based on a held-out corpus of 1 documents with 2409 words
+2024-05-13 12:44:22,872 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:22,873 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.007*"quality" + 0.007*"needs" + 0.006*"experienced" + 0.006*"Sunderland" + 0.005*"good" + 0.005*"TfC" + 0.005*"robust" + 0.005*"highly"
+2024-05-13 12:44:22,873 - topic #1 (0.333): 0.015*"’" + 0.007*"quality" + 0.006*"needs" + 0.005*"Sunderland" + 0.005*"practice" + 0.005*"council" + 0.004*"well" + 0.004*"protection" + 0.004*"parents" + 0.004*"training"
+2024-05-13 12:44:22,874 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.006*"Sunderland" + 0.006*"needs" + 0.005*"quality" + 0.005*"practice" + 0.005*"parents" + 0.004*"experienced" + 0.004*"protection" + 0.004*"training"
+2024-05-13 12:44:22,874 - topic diff=0.779895, rho=1.000000
+2024-05-13 12:44:22,874 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1128, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:22.874272', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:24,251 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:24,251 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:24,251 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:24,251 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:24,251 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:24,252 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:24,252 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:24,252 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:24,252 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:24,252 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:24,252 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:24,252 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:25,929 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:25,931 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)
+2024-05-13 12:44:25,931 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-05-13T12:44:25.931519', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:25,932 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:25,932 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:25,932 - using serial LDA version on this node
+2024-05-13 12:44:25,933 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:25,933 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:25,936 - -7.962 per-word bound, 249.3 perplexity estimate based on a held-out corpus of 1 documents with 2111 words
+2024-05-13 12:44:25,937 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:25,938 - topic #0 (0.333): 0.016*"’" + 0.010*"needs" + 0.009*"well" + 0.008*"practice" + 0.008*"progress" + 0.006*"quality" + 0.005*"Surrey" + 0.005*"good" + 0.005*"carers" + 0.005*"plans"
+2024-05-13 12:44:25,938 - topic #1 (0.333): 0.014*"’" + 0.010*"needs" + 0.010*"well" + 0.008*"practice" + 0.006*"17" + 0.005*"effective" + 0.005*"progress" + 0.005*"However" + 0.005*"carers" + 0.005*"plans"
+2024-05-13 12:44:25,938 - topic #2 (0.333): 0.008*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"progress" + 0.006*"plans" + 0.005*"practice" + 0.005*"quality" + 0.004*"good" + 0.004*"carers" + 0.004*"effective"
+2024-05-13 12:44:25,938 - topic diff=0.764917, rho=1.000000
+2024-05-13 12:44:25,939 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1016, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:25.939015', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:27,073 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:27,074 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:27,076 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:27,076 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:27,077 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:27,077 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:27,077 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:27,077 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:27,078 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:27,078 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:27,078 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:27,078 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:29,024 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:29,026 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)
+2024-05-13 12:44:29,026 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-05-13T12:44:29.026875', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:29,027 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:29,028 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:29,028 - using serial LDA version on this node
+2024-05-13 12:44:29,028 - 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
+2024-05-13 12:44:29,028 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:29,032 - -7.828 per-word bound, 227.3 perplexity estimate based on a held-out corpus of 1 documents with 2229 words
+2024-05-13 12:44:29,032 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:29,033 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Swindon" + 0.006*"need" + 0.005*"effective" + 0.005*"always" + 0.005*"plans" + 0.004*"17" + 0.004*"Council"
+2024-05-13 12:44:29,033 - topic #1 (0.333): 0.025*"’" + 0.015*"needs" + 0.010*"Swindon" + 0.010*"need" + 0.008*"well" + 0.008*"plans" + 0.007*"always" + 0.006*"impact" + 0.006*"lack" + 0.005*"effective"
+2024-05-13 12:44:29,034 - topic #2 (0.333): 0.024*"’" + 0.013*"needs" + 0.009*"well" + 0.008*"Swindon" + 0.008*"need" + 0.007*"always" + 0.006*"28" + 0.006*"health" + 0.006*"home" + 0.006*"plans"
+2024-05-13 12:44:29,034 - topic diff=0.838194, rho=1.000000
+2024-05-13 12:44:29,034 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=951, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:29.034406', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:30,177 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:30,177 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:30,177 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:30,177 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:30,178 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:30,178 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:30,178 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:30,178 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:30,178 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:30,178 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:30,178 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:30,179 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:31,623 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:31,626 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)
+2024-05-13 12:44:31,626 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-05-13T12:44:31.626464', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:31,627 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:31,627 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:31,628 - using serial LDA version on this node
+2024-05-13 12:44:31,628 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:31,628 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:31,632 - -7.949 per-word bound, 247.2 perplexity estimate based on a held-out corpus of 1 documents with 2491 words
+2024-05-13 12:44:31,632 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:31,633 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"impact" + 0.006*"quality" + 0.005*"experienced" + 0.005*"experiences" + 0.005*"protection" + 0.005*"2023" + 0.005*"plans" + 0.005*"practice"
+2024-05-13 12:44:31,633 - topic #1 (0.333): 0.014*"’" + 0.008*"needs" + 0.006*"risk" + 0.006*"impact" + 0.006*"practice" + 0.005*"2023" + 0.005*"understand" + 0.005*"quality" + 0.004*"experienced" + 0.004*"◼"
+2024-05-13 12:44:31,634 - topic #2 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"risk" + 0.006*"response" + 0.006*"quality" + 0.005*"4" + 0.005*"impact" + 0.005*"experienced" + 0.005*"Tameside" + 0.005*"practice"
+2024-05-13 12:44:31,634 - topic diff=0.823682, rho=1.000000
+2024-05-13 12:44:31,634 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:31.634219', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:32,567 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:32,567 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:32,568 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:32,568 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:32,568 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:32,568 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:32,568 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:32,569 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:32,569 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:32,569 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:32,569 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:32,569 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:34,474 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:34,476 - built Dictionary<1110 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2461 corpus positions)
+2024-05-13 12:44:34,476 - Dictionary lifecycle event {'msg': "built Dictionary<1110 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2461 corpus positions)", 'datetime': '2024-05-13T12:44:34.476818', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:34,477 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:34,478 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:34,478 - using serial LDA version on this node
+2024-05-13 12:44:34,478 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:34,478 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:34,482 - -8.020 per-word bound, 259.6 perplexity estimate based on a held-out corpus of 1 documents with 2461 words
+2024-05-13 12:44:34,482 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:34,484 - topic #0 (0.333): 0.021*"’" + 0.011*"well" + 0.009*"needs" + 0.007*"effective" + 0.006*"plans" + 0.005*"improve" + 0.005*"need" + 0.005*"strong" + 0.005*"ensure" + 0.005*"planning"
+2024-05-13 12:44:34,484 - topic #1 (0.333): 0.013*"well" + 0.010*"’" + 0.007*"needs" + 0.007*"effective" + 0.005*"leaders" + 0.005*"practice" + 0.005*"need" + 0.005*"strong" + 0.005*"carers" + 0.004*"improve"
+2024-05-13 12:44:34,484 - topic #2 (0.333): 0.016*"’" + 0.009*"well" + 0.007*"effective" + 0.007*"needs" + 0.006*"practice" + 0.006*"strong" + 0.005*"plans" + 0.005*"need" + 0.005*"ensure" + 0.005*"planning"
+2024-05-13 12:44:34,484 - topic diff=0.794265, rho=1.000000
+2024-05-13 12:44:34,484 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1110, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:34.484684', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:35,641 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:35,642 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:35,642 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:35,642 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:35,643 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:35,643 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:35,643 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:35,643 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:35,644 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:35,644 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:35,644 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:35,645 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:37,017 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:37,020 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)
+2024-05-13 12:44:37,020 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-05-13T12:44:37.020569', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:37,021 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:37,021 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:37,022 - using serial LDA version on this node
+2024-05-13 12:44:37,022 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:37,022 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:37,026 - -8.135 per-word bound, 281.2 perplexity estimate based on a held-out corpus of 1 documents with 2160 words
+2024-05-13 12:44:37,026 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:37,028 - topic #0 (0.333): 0.011*"’" + 0.009*"well" + 0.005*"carers" + 0.005*"need" + 0.005*"needs" + 0.004*"practice" + 0.004*"ensure" + 0.004*"leaders" + 0.004*"effective" + 0.004*"protection"
+2024-05-13 12:44:37,028 - topic #1 (0.333): 0.011*"’" + 0.008*"well" + 0.006*"carers" + 0.005*"need" + 0.004*"needs" + 0.004*"good" + 0.004*"leaders" + 0.004*"ensure" + 0.003*"Good" + 0.003*"time"
+2024-05-13 12:44:37,028 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.005*"carers" + 0.005*"need" + 0.005*"Thurrock" + 0.004*"practice" + 0.004*"effective" + 0.004*"impact" + 0.004*"needs" + 0.004*"ensure"
+2024-05-13 12:44:37,029 - topic diff=0.722701, rho=1.000000
+2024-05-13 12:44:37,029 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1138, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:37.029198', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:39,430 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:39,430 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:39,430 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:39,431 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:39,431 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:39,431 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:39,431 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:39,431 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:39,431 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:39,431 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:39,431 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:39,432 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:41,044 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:41,046 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)
+2024-05-13 12:44:41,046 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-05-13T12:44:41.046656', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:41,047 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:41,048 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:41,048 - using serial LDA version on this node
+2024-05-13 12:44:41,048 - 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
+2024-05-13 12:44:41,048 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:41,052 - -8.037 per-word bound, 262.7 perplexity estimate based on a held-out corpus of 1 documents with 2065 words
+2024-05-13 12:44:41,052 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:41,054 - topic #0 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"Torbay" + 0.007*"good" + 0.005*"needs" + 0.005*"progress" + 0.005*"effective" + 0.005*"team" + 0.004*"agencies" + 0.004*"quality"
+2024-05-13 12:44:41,054 - topic #1 (0.333): 0.021*"’" + 0.010*"well" + 0.008*"Torbay" + 0.007*"needs" + 0.005*"effective" + 0.005*"good" + 0.004*"2022" + 0.004*"timely" + 0.004*"focus" + 0.004*"plans"
+2024-05-13 12:44:41,054 - topic #2 (0.333): 0.012*"’" + 0.007*"well" + 0.006*"Torbay" + 0.005*"21" + 0.004*"good" + 0.004*"needs" + 0.004*"effective" + 0.004*"timely" + 0.004*"team" + 0.004*"progress"
+2024-05-13 12:44:41,054 - topic diff=0.750342, rho=1.000000
+2024-05-13 12:44:41,054 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1054, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:41.054692', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:42,084 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:42,084 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:42,084 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:42,085 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:42,085 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:42,085 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:42,085 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:42,085 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:42,086 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:42,086 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:42,086 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:42,086 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:43,731 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:43,733 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)
+2024-05-13 12:44:43,733 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-05-13T12:44:43.733701', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:43,734 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:43,734 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:43,735 - using serial LDA version on this node
+2024-05-13 12:44:43,735 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:43,735 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:43,739 - -7.906 per-word bound, 239.8 perplexity estimate based on a held-out corpus of 1 documents with 2448 words
+2024-05-13 12:44:43,739 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:43,740 - topic #0 (0.333): 0.014*"’" + 0.008*"Trafford" + 0.008*"plans" + 0.006*"quality" + 0.006*"well" + 0.006*"practice" + 0.005*"leaders" + 0.005*"placed" + 0.005*"needs" + 0.005*"December"
+2024-05-13 12:44:43,741 - topic #1 (0.333): 0.020*"’" + 0.013*"needs" + 0.008*"Trafford" + 0.008*"well" + 0.007*"quality" + 0.007*"plans" + 0.006*"leaders" + 0.006*"practice" + 0.006*"impact" + 0.005*"ensure"
+2024-05-13 12:44:43,741 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"Trafford" + 0.006*"plans" + 0.006*"quality" + 0.005*"leaders" + 0.005*"placed" + 0.004*"worker" + 0.004*"December"
+2024-05-13 12:44:43,741 - topic diff=0.831127, rho=1.000000
+2024-05-13 12:44:43,741 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1038, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:43.741579', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:44,961 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:44,961 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:44,962 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:44,962 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:44,962 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:44,962 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:44,962 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:44,963 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:44,963 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:44,963 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:44,963 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:44,963 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:46,925 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:46,927 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions)
+2024-05-13 12:44:46,928 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-05-13T12:44:46.928130', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:46,929 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:46,929 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:46,929 - using serial LDA version on this node
+2024-05-13 12:44:46,930 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:46,930 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:46,934 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2626 words
+2024-05-13 12:44:46,934 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:46,935 - topic #0 (0.333): 0.015*"’" + 0.008*"leaders" + 0.006*"needs" + 0.006*"well" + 0.005*"Walsall" + 0.005*"oversight" + 0.004*"Senior" + 0.004*"positive" + 0.004*"information" + 0.004*"need"
+2024-05-13 12:44:46,935 - topic #1 (0.333): 0.020*"’" + 0.007*"leaders" + 0.005*"well" + 0.005*"2021" + 0.005*"4" + 0.005*"needs" + 0.004*"information" + 0.004*"oversight" + 0.004*"Walsall" + 0.004*"plans"
+2024-05-13 12:44:46,936 - topic #2 (0.333): 0.026*"’" + 0.008*"needs" + 0.007*"leaders" + 0.006*"Walsall" + 0.006*"well" + 0.005*"4" + 0.005*"information" + 0.005*"Senior" + 0.005*"good" + 0.004*"practice"
+2024-05-13 12:44:46,936 - topic diff=0.816892, rho=1.000000
+2024-05-13 12:44:46,936 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1162, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:46.936316', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:47,861 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:47,861 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:47,861 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:47,862 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:47,862 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:47,862 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:47,862 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:47,862 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:47,862 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:47,863 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:47,863 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:47,863 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:49,791 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:49,794 - built Dictionary<1110 unique tokens: ['0161', '0300', '08', '1', '10']...> from 1 documents (total 2187 corpus positions)
+2024-05-13 12:44:49,794 - Dictionary lifecycle event {'msg': "built Dictionary<1110 unique tokens: ['0161', '0300', '08', '1', '10']...> from 1 documents (total 2187 corpus positions)", 'datetime': '2024-05-13T12:44:49.794375', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:49,795 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:49,795 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:49,795 - using serial LDA version on this node
+2024-05-13 12:44:49,796 - 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
+2024-05-13 12:44:49,796 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:49,799 - -8.091 per-word bound, 272.7 perplexity estimate based on a held-out corpus of 1 documents with 2187 words
+2024-05-13 12:44:49,800 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:49,801 - topic #0 (0.333): 0.011*"’" + 0.006*"practice" + 0.006*"well" + 0.004*"home" + 0.004*"number" + 0.004*"plans" + 0.004*"information" + 0.004*"progress" + 0.004*"carers" + 0.004*"good"
+2024-05-13 12:44:49,801 - topic #1 (0.333): 0.014*"’" + 0.006*"practice" + 0.006*"well" + 0.005*"plans" + 0.005*"Senior" + 0.004*"progress" + 0.004*"needs" + 0.004*"senior" + 0.004*"parents" + 0.004*"number"
+2024-05-13 12:44:49,801 - topic #2 (0.333): 0.017*"’" + 0.007*"well" + 0.006*"practice" + 0.005*"number" + 0.004*"Senior" + 0.004*"carers" + 0.004*"need" + 0.004*"progress" + 0.004*"home" + 0.004*"plans"
+2024-05-13 12:44:49,802 - topic diff=0.723735, rho=1.000000
+2024-05-13 12:44:49,802 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1110, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:49.802171', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:51,069 - Inspection date 2019-07-08 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:51,069 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:51,070 - Inspection date 2019-07-08 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:51,070 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:51,070 - Inspection date 2019-07-08 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:51,070 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:51,071 - Inspection date 2019-07-08 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:51,071 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:51,073 - Inspection date 2019-07-08 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:51,074 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:51,074 - Inspection date 2019-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:51,074 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:52,628 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:52,630 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)
+2024-05-13 12:44:52,631 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-05-13T12:44:52.631132', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:52,632 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:52,632 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:52,632 - using serial LDA version on this node
+2024-05-13 12:44:52,632 - 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
+2024-05-13 12:44:52,633 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:52,636 - -8.005 per-word bound, 256.8 perplexity estimate based on a held-out corpus of 1 documents with 2113 words
+2024-05-13 12:44:52,636 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:52,637 - topic #0 (0.333): 0.009*"’" + 0.007*"Warwickshire" + 0.006*"practice" + 0.006*"plans" + 0.005*"well" + 0.005*"needs" + 0.005*"Senior" + 0.004*"progress" + 0.004*"carers" + 0.004*"supported"
+2024-05-13 12:44:52,638 - topic #1 (0.333): 0.009*"’" + 0.006*"plans" + 0.005*"well" + 0.005*"Warwickshire" + 0.005*"needs" + 0.004*"progress" + 0.004*"good" + 0.004*"practice" + 0.004*"22" + 0.004*"agencies"
+2024-05-13 12:44:52,638 - topic #2 (0.333): 0.015*"’" + 0.008*"needs" + 0.008*"well" + 0.006*"plans" + 0.006*"carers" + 0.005*"good" + 0.005*"Warwickshire" + 0.005*"3" + 0.005*"clear" + 0.005*"effective"
+2024-05-13 12:44:52,638 - topic diff=0.764374, rho=1.000000
+2024-05-13 12:44:52,638 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1040, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:52.638576', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:53,548 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:53,548 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:53,548 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:53,548 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:53,549 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:53,549 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:53,549 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:53,549 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:53,549 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:53,549 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:53,549 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:53,550 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:54,833 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:54,836 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)
+2024-05-13 12:44:54,836 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-05-13T12:44:54.836531', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:54,837 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:54,837 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:54,838 - using serial LDA version on this node
+2024-05-13 12:44:54,838 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:54,838 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:54,842 - -8.106 per-word bound, 275.5 perplexity estimate based on a held-out corpus of 1 documents with 2146 words
+2024-05-13 12:44:54,842 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:54,843 - topic #0 (0.333): 0.011*"’" + 0.006*"well" + 0.006*"Berkshire" + 0.005*"14" + 0.004*"18" + 0.004*"need" + 0.004*"practice" + 0.004*"West" + 0.004*"working" + 0.004*"plans"
+2024-05-13 12:44:54,844 - topic #1 (0.333): 0.012*"’" + 0.008*"West" + 0.007*"Berkshire" + 0.005*"well" + 0.004*"ensure" + 0.004*"needs" + 0.004*"18" + 0.004*"2022" + 0.004*"progress" + 0.004*"need"
+2024-05-13 12:44:54,844 - topic #2 (0.333): 0.019*"’" + 0.007*"West" + 0.006*"well" + 0.006*"Berkshire" + 0.005*"agency" + 0.005*"plans" + 0.004*"needs" + 0.004*"early" + 0.004*"need" + 0.004*"education"
+2024-05-13 12:44:54,844 - topic diff=0.714033, rho=1.000000
+2024-05-13 12:44:54,844 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1115, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:54.844546', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:55,807 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:55,807 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:55,808 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:55,808 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:55,808 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:55,808 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:55,808 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:55,808 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:55,809 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:55,809 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:55,809 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:55,809 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:57,588 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:44:57,591 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)
+2024-05-13 12:44:57,591 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-05-13T12:44:57.591488', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:57,592 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:44:57,592 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:44:57,592 - using serial LDA version on this node
+2024-05-13 12:44:57,593 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:44:57,593 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:44:57,597 - -8.045 per-word bound, 264.0 perplexity estimate based on a held-out corpus of 1 documents with 2224 words
+2024-05-13 12:44:57,597 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:44:57,598 - topic #0 (0.333): 0.018*"’" + 0.008*"Northamptonshire" + 0.007*"quality" + 0.005*"West" + 0.005*"plans" + 0.005*"well" + 0.005*"needs" + 0.005*"NCT" + 0.004*"practice" + 0.004*"Leaders"
+2024-05-13 12:44:57,598 - topic #1 (0.333): 0.020*"’" + 0.007*"West" + 0.007*"Northamptonshire" + 0.007*"well" + 0.006*"quality" + 0.005*"NCT" + 0.005*"practice" + 0.005*"14" + 0.005*"impact" + 0.004*"However"
+2024-05-13 12:44:57,599 - topic #2 (0.333): 0.014*"’" + 0.009*"Northamptonshire" + 0.007*"West" + 0.007*"quality" + 0.006*"well" + 0.006*"needs" + 0.006*"practice" + 0.005*"3" + 0.005*"need" + 0.005*"experiences"
+2024-05-13 12:44:57,599 - topic diff=0.755219, rho=1.000000
+2024-05-13 12:44:57,599 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1087, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:44:57.599371', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:44:58,536 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:44:58,536 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:58,536 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:44:58,536 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:58,537 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:44:58,537 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:58,537 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:44:58,537 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:58,537 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:44:58,537 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:44:58,538 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:44:58,538 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:00,373 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:00,375 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)
+2024-05-13 12:45:00,376 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-05-13T12:45:00.376002', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:00,377 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:00,377 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:00,377 - using serial LDA version on this node
+2024-05-13 12:45:00,378 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:45:00,378 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:00,382 - -8.124 per-word bound, 279.1 perplexity estimate based on a held-out corpus of 1 documents with 2720 words
+2024-05-13 12:45:00,382 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:00,383 - topic #0 (0.333): 0.017*"’" + 0.007*"well" + 0.006*"plans" + 0.006*"needs" + 0.006*"Sussex" + 0.005*"13" + 0.005*"quality" + 0.005*"health" + 0.005*"West" + 0.004*"number"
+2024-05-13 12:45:00,383 - topic #1 (0.333): 0.012*"’" + 0.007*"plans" + 0.005*"needs" + 0.005*"well" + 0.005*"West" + 0.005*"13" + 0.004*"Sussex" + 0.004*"practice" + 0.004*"number" + 0.004*"strong"
+2024-05-13 12:45:00,384 - topic #2 (0.333): 0.010*"’" + 0.006*"well" + 0.005*"plans" + 0.005*"West" + 0.004*"supported" + 0.004*"needs" + 0.004*"number" + 0.004*"quality" + 0.004*"24" + 0.004*"Sussex"
+2024-05-13 12:45:00,384 - topic diff=0.812448, rho=1.000000
+2024-05-13 12:45:00,384 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1233, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:00.384360', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:01,422 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:01,422 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:01,422 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:01,422 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:01,423 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:01,423 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:01,423 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:01,423 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:01,423 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:01,423 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:01,424 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:01,424 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:03,784 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:03,787 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)
+2024-05-13 12:45:03,787 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-05-13T12:45:03.787312', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:03,788 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:03,788 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:03,788 - using serial LDA version on this node
+2024-05-13 12:45:03,789 - 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
+2024-05-13 12:45:03,789 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:03,792 - -7.959 per-word bound, 248.8 perplexity estimate based on a held-out corpus of 1 documents with 2416 words
+2024-05-13 12:45:03,793 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:03,794 - topic #0 (0.333): 0.014*"’" + 0.007*"plans" + 0.007*"May" + 0.006*"quality" + 0.006*"needs" + 0.005*"leaders" + 0.005*"Wigan" + 0.005*"appropriate" + 0.005*"practice" + 0.004*"9"
+2024-05-13 12:45:03,794 - topic #1 (0.333): 0.011*"’" + 0.008*"practice" + 0.007*"May" + 0.006*"Wigan" + 0.005*"needs" + 0.005*"timely" + 0.005*"quality" + 0.005*"plans" + 0.005*"20" + 0.005*"9"
+2024-05-13 12:45:03,794 - topic #2 (0.333): 0.012*"’" + 0.007*"May" + 0.007*"plans" + 0.006*"practice" + 0.006*"needs" + 0.006*"appropriate" + 0.006*"Wigan" + 0.005*"quality" + 0.005*"leaders" + 0.005*"2022"
+2024-05-13 12:45:03,794 - topic diff=0.786948, rho=1.000000
+2024-05-13 12:45:03,795 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1064, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:03.795023', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:04,747 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:04,747 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:04,747 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:04,747 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:04,747 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:04,748 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:04,748 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:04,748 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:04,748 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:04,748 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:04,748 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:04,749 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:06,416 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:06,419 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)
+2024-05-13 12:45:06,419 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-05-13T12:45:06.419292', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:06,420 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:06,420 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:06,420 - using serial LDA version on this node
+2024-05-13 12:45:06,421 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:45:06,421 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:06,424 - -7.959 per-word bound, 248.9 perplexity estimate based on a held-out corpus of 1 documents with 2600 words
+2024-05-13 12:45:06,425 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:06,426 - topic #0 (0.333): 0.021*"’" + 0.012*"well" + 0.009*"needs" + 0.006*"progress" + 0.006*"parents" + 0.006*"including" + 0.006*"risk" + 0.006*"Wiltshire" + 0.005*"need" + 0.005*"plans"
+2024-05-13 12:45:06,426 - topic #1 (0.333): 0.013*"well" + 0.009*"’" + 0.007*"need" + 0.006*"progress" + 0.006*"Wiltshire" + 0.006*"needs" + 0.006*"risk" + 0.005*"including" + 0.005*"supported" + 0.005*"25"
+2024-05-13 12:45:06,426 - topic #2 (0.333): 0.014*"’" + 0.009*"well" + 0.007*"need" + 0.007*"quality" + 0.006*"supported" + 0.006*"plans" + 0.006*"ensure" + 0.005*"parents" + 0.005*"needs" + 0.005*"Wiltshire"
+2024-05-13 12:45:06,426 - topic diff=0.830828, rho=1.000000
+2024-05-13 12:45:06,427 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1090, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:06.427087', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:07,474 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:07,474 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:07,475 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:07,475 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:07,475 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:07,475 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:07,475 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:07,475 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:07,476 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:07,476 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:07,476 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:07,476 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:09,307 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:09,310 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
+2024-05-13 12:45:09,310 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-05-13T12:45:09.310813', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:09,312 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:09,312 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:09,320 - using serial LDA version on this node
+2024-05-13 12:45:09,321 - 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
+2024-05-13 12:45:09,321 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:09,330 - -7.908 per-word bound, 240.2 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
+2024-05-13 12:45:09,330 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:09,332 - topic #0 (0.333): 0.012*"’" + 0.010*"needs" + 0.007*"ensure" + 0.007*"Wirral" + 0.006*"well" + 0.006*"practice" + 0.006*"plans" + 0.005*"29" + 0.005*"18" + 0.005*"number"
+2024-05-13 12:45:09,333 - topic #1 (0.333): 0.011*"’" + 0.010*"needs" + 0.008*"Wirral" + 0.007*"ensure" + 0.007*"plans" + 0.006*"practice" + 0.005*"number" + 0.005*"response" + 0.005*"well" + 0.005*"risk"
+2024-05-13 12:45:09,333 - topic #2 (0.333): 0.010*"’" + 0.007*"needs" + 0.006*"ensure" + 0.006*"plans" + 0.006*"Wirral" + 0.005*"practice" + 0.005*"18" + 0.005*"number" + 0.004*"small" + 0.004*"appropriate"
+2024-05-13 12:45:09,333 - topic diff=0.806319, rho=1.000000
+2024-05-13 12:45:09,333 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1000, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:09.333620', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:10,446 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:10,447 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:10,447 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:10,447 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:10,448 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:10,448 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:10,448 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:10,448 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:10,448 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:10,449 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:10,449 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:10,449 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:12,139 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:12,141 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)
+2024-05-13 12:45:12,141 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-05-13T12:45:12.141777', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:12,142 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:12,143 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:12,143 - using serial LDA version on this node
+2024-05-13 12:45:12,143 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:45:12,143 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:12,147 - -8.060 per-word bound, 266.9 perplexity estimate based on a held-out corpus of 1 documents with 2214 words
+2024-05-13 12:45:12,147 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:12,148 - topic #0 (0.333): 0.011*"’" + 0.006*"provided" + 0.006*"plans" + 0.005*"progress" + 0.005*"needs" + 0.005*"effective" + 0.005*"well" + 0.005*"17" + 0.005*"oversight" + 0.004*"ensure"
+2024-05-13 12:45:12,149 - topic #1 (0.333): 0.016*"’" + 0.007*"plans" + 0.006*"effective" + 0.006*"needs" + 0.005*"progress" + 0.005*"impact" + 0.005*"17" + 0.005*"6" + 0.005*"parents" + 0.004*"experiences"
+2024-05-13 12:45:12,149 - topic #2 (0.333): 0.010*"’" + 0.007*"plans" + 0.007*"effective" + 0.006*"needs" + 0.006*"well" + 0.005*"progress" + 0.005*"appropriate" + 0.005*"experiences" + 0.005*"quality" + 0.005*"provided"
+2024-05-13 12:45:12,149 - topic diff=0.755080, rho=1.000000
+2024-05-13 12:45:12,149 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1096, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:12.149499', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:13,054 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:13,054 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:13,055 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:13,055 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:13,055 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:13,055 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:13,056 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:13,056 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:13,056 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:13,056 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:13,057 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:13,057 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:14,964 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:14,967 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)
+2024-05-13 12:45:14,967 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-05-13T12:45:14.967175', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:14,968 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:14,968 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:14,968 - using serial LDA version on this node
+2024-05-13 12:45:14,969 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:45:14,969 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:14,972 - -8.049 per-word bound, 264.9 perplexity estimate based on a held-out corpus of 1 documents with 2233 words
+2024-05-13 12:45:14,972 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:14,974 - topic #0 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"effective" + 0.005*"plans" + 0.005*"Wolverhampton" + 0.004*"education" + 0.004*"quality" + 0.004*"experiences" + 0.004*"leaders" + 0.004*"risks"
+2024-05-13 12:45:14,974 - topic #1 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"Wolverhampton" + 0.006*"risks" + 0.005*"effective" + 0.005*"risk" + 0.005*"plans" + 0.004*"receive" + 0.004*"education" + 0.004*"practice"
+2024-05-13 12:45:14,974 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.006*"Wolverhampton" + 0.006*"quality" + 0.005*"effective" + 0.005*"leaders" + 0.005*"receive" + 0.005*"supported" + 0.005*"strong" + 0.005*"risks"
+2024-05-13 12:45:14,974 - topic diff=0.741121, rho=1.000000
+2024-05-13 12:45:14,975 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1095, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:14.975064', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:15,984 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:15,984 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:15,984 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:15,984 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:15,985 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:15,985 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:15,985 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:15,985 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:15,985 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:15,985 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:15,986 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:15,986 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:17,548 - adding document #0 to Dictionary<0 unique tokens: []>
+2024-05-13 12:45:17,550 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)
+2024-05-13 12:45:17,550 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-05-13T12:45:17.550586', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:17,551 - using symmetric alpha at 0.3333333333333333
+2024-05-13 12:45:17,551 - using symmetric eta at 0.3333333333333333
+2024-05-13 12:45:17,552 - using serial LDA version on this node
+2024-05-13 12:45:17,552 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000
+2024-05-13 12:45:17,552 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy
+2024-05-13 12:45:17,556 - -7.941 per-word bound, 245.8 perplexity estimate based on a held-out corpus of 1 documents with 2343 words
+2024-05-13 12:45:17,556 - PROGRESS: pass 0, at document #1/1
+2024-05-13 12:45:17,557 - topic #0 (0.333): 0.011*"’" + 0.006*"ensure" + 0.005*"well" + 0.005*"needs" + 0.005*"plans" + 0.005*"Worcestershire" + 0.005*"leaders" + 0.005*"15" + 0.005*"appropriate" + 0.004*"26"
+2024-05-13 12:45:17,557 - topic #1 (0.333): 0.024*"’" + 0.010*"well" + 0.010*"plans" + 0.009*"needs" + 0.009*"progress" + 0.008*"Worcestershire" + 0.008*"leaders" + 0.006*"appropriate" + 0.006*"ensure" + 0.005*"Senior"
+2024-05-13 12:45:17,557 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"plans" + 0.006*"leaders" + 0.005*"progress" + 0.005*"Worcestershire" + 0.005*"ensure" + 0.005*"making" + 0.005*"education"
+2024-05-13 12:45:17,558 - topic diff=0.825611, rho=1.000000
+2024-05-13 12:45:17,558 - LdaModel lifecycle event {'msg': 'trained LdaModel<num_terms=1041, num_topics=3, decay=0.5, chunksize=2000> in 0.01s', 'datetime': '2024-05-13T12:45:17.558200', 'gensim': '4.3.2', 'python': '3.10.13 (main, Apr  3 2024, 17:08:15) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1019-azure-x86_64-with-glibc2.31', 'event': 'created'}
+2024-05-13 12:45:18,606 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame.
+2024-05-13 12:45:18,606 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:18,606 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame.
+2024-05-13 12:45:18,606 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:18,607 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame.
+2024-05-13 12:45:18,607 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:18,607 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame.
+2024-05-13 12:45:18,607 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:18,607 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame.
+2024-05-13 12:45:18,607 - Index(['judgement', 'grade'], dtype='object')
+2024-05-13 12:45:18,607 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame.
+2024-05-13 12:45:18,608 - Index(['judgement', 'grade'], dtype='object')