I need to identify the main categorical columns in this dataset and find their most common values with frequencies. Let me start by understanding the dataset structure better. ```json { "action": "tool_call", "reasoning": "The dataset card shows 51 tables with over 2 million rows. To identify the main categorical columns across the dataset, I should first look at the column overview metadata to see which columns are categorical and their characteristics. This will help me determine which are the 'main' categorical columns worth profiling.", "tool": "query_sql", "args": { "sql": "SELECT table_name, column_name, phys_type, semantic_role, rough_kind, distinct_count, null_count FROM analytics.column_overview WHERE rough_kind IN ('categorical', 'text') AND distinct_count > 0 ORDER BY distinct_count DESC LIMIT 50", "purpose": "Identify the main categorical columns across all tables by looking at their distinct counts and types" } } ```