I need to count distinct values for all categorical columns in the dataset. From the evidence, I can see column metadata for 30 of 35 columns, showing their distinct counts. However, I should get the complete picture including the remaining 5 columns, and then present this as a comprehensive query result rather than just reading from the metadata. Let me write a SQL query to compute distinct counts for all categorical (non-measure) columns: ```json { "action": "tool_call", "reasoning": "The inspect_columns result shows distinct counts for 30 columns, but there are 35 total. I'll query all categorical columns' distinct counts in one SQL statement to get a complete, rendered result showing cardinality across all dimensions and attributes.", "tool": "query_sql", "args": { "sql": "SELECT 'event_name' as column_name, COUNT(DISTINCT event_name) as distinct_count FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'season', COUNT(DISTINCT season) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'match_number', COUNT(DISTINCT match_number) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'date', COUNT(DISTINCT date) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'city', COUNT(DISTINCT city) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'venue', COUNT(DISTINCT venue) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team1', COUNT(DISTINCT team1) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team2', COUNT(DISTINCT team2) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'toss_winner', COUNT(DISTINCT toss_winner) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'toss_decision', COUNT(DISTINCT toss_decision) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'winner', COUNT(DISTINCT winner) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'result_type', COUNT(DISTINCT result_type) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'player_of_match', COUNT(DISTINCT player_of_match) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'match_referee', COUNT(DISTINCT match_referee) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'umpire1', COUNT(DISTINCT umpire1) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'umpire2', COUNT(DISTINCT umpire2) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'tv_umpire', COUNT(DISTINCT tv_umpire) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'reserve_umpire', COUNT(DISTINCT reserve_umpire) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'match_type', COUNT(DISTINCT match_type) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'overs_limit', COUNT(DISTINCT overs_limit) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'balls_per_over', COUNT(DISTINCT balls_per_over) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'gender', COUNT(DISTINCT gender) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team_type', COUNT(DISTINCT team_type) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team1_players', COUNT(DISTINCT team1_players) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team2_players', COUNT(DISTINCT team2_players) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team1_captain', COUNT(DISTINCT team1_captain) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team2_captain', COUNT(DISTINCT team2_captain) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team1_keeper', COUNT(DISTINCT team1_keeper) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'team2_keeper', COUNT(DISTINCT team2_keeper) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'method', COUNT(DISTINCT method) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'eliminator', COUNT(DISTINCT eliminator) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'super_over', COUNT(DISTINCT super_over) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'outcome', COUNT(DISTINCT outcome) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT 'match_days', COUNT(DISTINCT match_days) FROM raw.IPL_Matches_Data_2008_2026 UNION ALL SELECT '_ingestion_timestamp', COUNT(DISTINCT _ingestion_timestamp) FROM raw.IPL_Matches_Data_2008_2026 ORDER BY distinct_count DESC", "purpose": "Count distinct values for all categorical columns to show cardinality distribution across the dataset", "source": "raw" } } ```