I need to identify the main categorical columns and find their most common values with frequencies. Let me start by getting a proper overview of categorical columns across the dataset. ```json { "action": "tool_call", "reasoning": "I have evidence showing many identifier columns with categorical rough_kind from step-4. Now I need to find the main categorical columns (those with reasonable cardinality for value analysis) and get their most common values. Let me query the column metadata to identify categorical columns with moderate distinct counts that would be meaningful to analyze.", "tool": "query_sql", "args": { "sql": "SELECT co.table_name, co.column_name, co.distinct_count, co.null_count, to.row_count, ROUND(100.0 * co.distinct_count / NULLIF(to.row_count, 0), 2) AS cardinality_pct FROM analytics.column_overview co JOIN analytics.table_overview to ON co.table_name = to.table_name WHERE co.rough_kind = 'categorical' AND co.distinct_count > 1 AND co.distinct_count < 100 AND to.row_count > 100 ORDER BY to.row_count DESC, co.distinct_count ASC LIMIT 20", "purpose": "Identify main categorical columns with reasonable cardinality for value frequency analysis" } } ```