I need to identify the main categorical columns and find their most common values with frequencies. Let me start by examining the dataset structure to understand which columns are categorical. ```json { "action": "tool_call", "reasoning": "The dataset card lists several classifiers (categorical columns): job_title, company_name, industry, education_required, employment_type, experience_level, company_size, remote_ratio, and salary_currency. I need to get the most common values and their frequencies for these main categorical columns. I'll write a single SQL query that gets the top values for each categorical column using UNION ALL to combine results efficiently.", "tool": "query_sql", "args": { "sql": "SELECT 'job_title' AS column_name, job_title AS value, COUNT(*) AS frequency, ROUND(COUNT(*) * 100.0 / (SELECT COUNT(*) FROM raw.ai_job_dataset), 2) AS percentage FROM raw.ai_job_dataset GROUP BY job_title ORDER BY frequency DESC LIMIT 5", "purpose": "Get top 5 most common job titles with frequencies and percentages", "source": "raw" } } ```