I need to identify the main categorical columns and find their most common values with frequencies. Let me start by examining the dataset structure. From the dataset card, I can see the main categorical columns are: - `raw.fighters.stance` (~3 distinct values) - `raw.fighters.country` (spatial axis) - `raw.popular_matches.opponent_1` (~134 distinct) - `raw.popular_matches.opponent_2` (~67 distinct) - `raw.popular_matches.place` (spatial axis) - `raw.popular_matches.verdict` Let me query the most common values for each of these categorical columns. ```json { "action": "tool_call", "reasoning": "Query the most common values and their frequencies for the main categorical columns in the fighters table: stance and country. I'll get the top 10 values for each to show the distribution.", "tool": "query_sql", "args": { "sql": "SELECT 'stance' as column_name, stance as value, COUNT(*) as frequency, ROUND(COUNT(*) * 100.0 / (SELECT COUNT(*) FROM raw.fighters), 2) as percentage FROM raw.fighters WHERE stance IS NOT NULL GROUP BY stance ORDER BY frequency DESC UNION ALL SELECT 'country' as column_name, country as value, COUNT(*) as frequency, ROUND(COUNT(*) * 100.0 / (SELECT COUNT(*) FROM raw.fighters), 2) as percentage FROM raw.fighters WHERE country IS NOT NULL GROUP BY country ORDER BY frequency DESC LIMIT 10", "purpose": "Get the most common values and frequencies for stance and country columns in the fighters table" } } ```