PHPMem v2.0.1

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1.6.45
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7 days 11 hours 39 minutes 55 seconds

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512MB
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13,32MB (2.6%)
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498,68MB

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10 162
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11 092
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0
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157
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llm:bd64c1085ee2d07f918163aadf7d98e24a5e8c839b99486c6f6600df69320435
TTL 3 days 14 hours 40 minutes 14 seconds Size 1,28KB Export
Edit
I need to identify the most strongly correlated columns in this dataset. I already have correlation data for the beer_ratings table's rating dimensions from step-2, which shows very strong correlations. Let me explore correlations in other key tables as well. ```json { "action": "tool_call", "reasoning": "I have correlations for beer_ratings rating dimensions. Now I should check correlations in the beers table, particularly between rating metrics (avg_rating, real_avg_rating, rating_count, view_count) and other numeric measures.", "tool": "query_sql", "args": { "sql": "SELECT CORR(avg_rating, real_avg_rating) as avg_vs_real, CORR(avg_rating, rating_count) as avg_vs_count, CORR(avg_rating, view_count) as avg_vs_views, CORR(rating_count, view_count) as count_vs_views, CORR(alcohol_pct, avg_rating) as alcohol_vs_rating, CORR(ibu, avg_rating) as ibu_vs_rating, CORR(alcohol_pct, ibu) as alcohol_vs_ibu, CORR(rating_std_dev, rating_count) as stddev_vs_count, CORR(overall_percentile, style_percentile) as overall_vs_style_pct FROM raw.beers WHERE avg_rating IS NOT NULL", "purpose": "Calculate correlations between key numeric columns in the beers table" } } ```