I need to identify the main categorical columns and find their most common values with frequencies. From the evidence, I can see several categorical columns in matches_1930_2022. Let me query the most common values for the key categorical dimensions. ```json { "action": "tool_call", "reasoning": "I'll query the most common values for the main categorical columns: home_team, away_team, Referee, Round, Host, and Venue. I'll get the top 10 values for each with their frequencies in a single query.", "tool": "query_sql", "args": { "sql": "WITH home_teams AS (SELECT 'home_team' as column_name, home_team as value, COUNT(*) as frequency FROM raw.matches_1930_2022 GROUP BY home_team ORDER BY frequency DESC LIMIT 10), away_teams AS (SELECT 'away_team' as column_name, away_team as value, COUNT(*) as frequency FROM raw.matches_1930_2022 GROUP BY away_team ORDER BY frequency DESC LIMIT 10), referees AS (SELECT 'Referee' as column_name, Referee as value, COUNT(*) as frequency FROM raw.matches_1930_2022 GROUP BY Referee ORDER BY frequency DESC LIMIT 10), rounds AS (SELECT 'Round' as column_name, Round as value, COUNT(*) as frequency FROM raw.matches_1930_2022 GROUP BY Round ORDER BY frequency DESC LIMIT 10), hosts AS (SELECT 'Host' as column_name, Host as value, COUNT(*) as frequency FROM raw.matches_1930_2022 GROUP BY Host ORDER BY frequency DESC LIMIT 10), venues AS (SELECT 'Venue' as column_name, Venue as value, COUNT(*) as frequency FROM raw.matches_1930_2022 GROUP BY Venue ORDER BY frequency DESC LIMIT 10) SELECT * FROM home_teams UNION ALL SELECT * FROM away_teams UNION ALL SELECT * FROM referees UNION ALL SELECT * FROM rounds UNION ALL SELECT * FROM hosts UNION ALL SELECT * FROM venues ORDER BY column_name, frequency DESC", "purpose": "Get the top 10 most common values and their frequencies for the main categorical columns: home_team, away_team, Referee, Round, Host, and Venue" } } ```