I need to identify the main categorical columns and find their most common values with frequencies. From the dataset card, the main classifiers are: - Player1 (~635 distinct values) - Player2 (~635 distinct values) - HomeWinner (~2 distinct values) Let me query the most common values for each of these columns in a single efficient query. ```json { "action": "tool_call", "reasoning": "I'll write one SQL query to get the top 10 most common values and their frequencies for each of the three main categorical columns (Player1, Player2, HomeWinner). This is more efficient than querying each column separately.", "tool": "query_sql", "args": { "sql": "WITH player1_top AS (SELECT 'Player1' as column_name, Player1 as value, COUNT(*) as frequency FROM raw.table_tennis_sept2022 GROUP BY Player1 ORDER BY COUNT(*) DESC LIMIT 10), player2_top AS (SELECT 'Player2' as column_name, Player2 as value, COUNT(*) as frequency FROM raw.table_tennis_sept2022 GROUP BY Player2 ORDER BY COUNT(*) DESC LIMIT 10), homewinner_top AS (SELECT 'HomeWinner' as column_name, CAST(HomeWinner AS VARCHAR) as value, COUNT(*) as frequency FROM raw.table_tennis_sept2022 GROUP BY HomeWinner ORDER BY COUNT(*) DESC) SELECT * FROM player1_top UNION ALL SELECT * FROM player2_top UNION ALL SELECT * FROM homewinner_top ORDER BY column_name, frequency DESC", "purpose": "Get the top 10 most common values and their frequencies for each main categorical column (Player1, Player2, HomeWinner)", "source": "raw" } } ```