{
    "action": "final",
    "content": "# Distribution Statistics for Numeric Columns\n\nI have analyzed the distribution of numeric columns across the dataset's key tables. Here are the comprehensive findings:\n\n## Analysis Run LLM Usage\n\n**LLM Call Metrics:**\n- **calls**: Range 2-7, mean 4.49, median 4, stddev 2.49\n- **input_tokens**: Range 0-6,566, mean 2,045, median 403, stddev 2,409\n- **output_tokens**: Range 0-10,958, mean 1,286, median 286, stddev 1,626\n- **cost_usd**: Range $0-$0.14, mean $0.024, median $0.0018, stddev $0.031\n\n## Analysis Runs\n\n**Resource Consumption:**\n- **cost_compute_seconds**: Range 0.40-545, mean 42.6, median 44.8, stddev 53.6\n- **total_cost_usd**: Range $0-$0.14, mean $0.046, median $0.059, stddev $0.031\n- **total_input_tokens**: Range 0-6,967, mean 3,985, median 5,341, stddev 2,560\n- **total_output_tokens**: Range 0-11,119, mean 2,506, median 3,118, stddev 1,873\n\n## Batches\n\n**Processing Metrics:**\n- **elapsed_ms**: Range 0-1,560,492, mean 59,620, median 1,293, stddev 192,026 (highly right-skewed)\n- **total_bytes**: Range 0-2.7B, mean 113.5M, median 1,086, stddev 419.7M (extremely right-skewed)\n- **total_rows**: Range 0-19.4M, mean 941,670, median 20, stddev 3.3M (extremely right-skewed)\n\n## Key Observations\n\n1. **High variability in token usage**: Large standard deviations relative to means indicate substantial variation in LLM call patterns\n2. **Right-skewed batch processing**: The batch metrics show extreme right skew (mean >> median), suggesting most batches are small but a few are very large\n3. **Cost distribution**: LLM costs are relatively low on average but can spike to $0.14 for intensive runs\n4. **Compute time**: Analysis runs typically complete in under a minute (median 44.8s) but can extend to over 9 minutes"
}