PHPMem v2.0.1
Version
1.6.45
Uptime
18 days 6 hours 34 minutes 35 seconds
Memory
Total
512MB
Used
12,33MB (2.41%)
Free
499,67MB
Keys
Current
13 424
Total (since start)
40 994
Evictions
0
Reclaimed
762
Expired Unfetched
0
Evicted Unfetched
0
Connections
Current
2 / 1 024 max
Total
244 881
Rejected
0
llm:72ce081e5aa0ad7077c238584c4328ba69a262ce1c9398d711548589c09c6560
Edit
I need to identify the main categorical columns and find their most common values with frequencies. From the column inspection, I can see several categorical dimensions. Let me query the most common values for each key categorical column.
{"action": "tool_call", "reasoning": "I'll query the most common values for the main categorical columns: Cuisines, Currency, Rating color, Rating text, Price range, Has Table booking, Has Online delivery, and Is delivering now. I'll get the top 10 values for each along with their counts and percentages.", "tool": "query_sql", "source": "raw", "purpose": "Get the most common values and their frequencies for main categorical columns", "args": {"sql": "WITH cuisines_top AS (SELECT 'Cuisines' as category, Cuisines as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY Cuisines ORDER BY count DESC LIMIT 10), currency_top AS (SELECT 'Currency' as category, Currency as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY Currency ORDER BY count DESC LIMIT 10), rating_color_top AS (SELECT 'Rating color' as category, \"Rating color\" as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Rating color\" ORDER BY count DESC LIMIT 10), rating_text_top AS (SELECT 'Rating text' as category, \"Rating text\" as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Rating text\" ORDER BY count DESC LIMIT 10), price_range_top AS (SELECT 'Price range' as category, CAST(\"Price range\" AS VARCHAR) as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Price range\" ORDER BY count DESC LIMIT 10), table_booking_top AS (SELECT 'Has Table booking' as category, CAST(\"Has Table booking\" AS VARCHAR) as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Has Table booking\" ORDER BY count DESC LIMIT 10), online_delivery_top AS (SELECT 'Has Online delivery' as category, CAST(\"Has Online delivery\" AS VARCHAR) as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Has Online delivery\" ORDER BY count DESC LIMIT 10), delivering_now_top AS (SELECT 'Is delivering now' as category, CAST(\"Is delivering now\" AS VARCHAR) as value, COUNT(*) as count, ROUND(100.0 * COUNT(*) / SUM(COUNT(*)) OVER (), 2) as percentage FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Is delivering now\" ORDER BY count DESC LIMIT 10) SELECT * FROM cuisines_top UNION ALL SELECT * FROM currency_top UNION ALL SELECT * FROM rating_color_top UNION ALL SELECT * FROM rating_text_top UNION ALL SELECT * FROM price_range_top UNION ALL SELECT * FROM table_booking_top UNION ALL SELECT * FROM online_delivery_top UNION ALL SELECT * FROM delivering_now_top ORDER BY category, count DESC"}}