```json { "action": "tool_call", "reasoning": "I have comprehensive statistics showing no nulls and no negative values, and I found 2 duplicate rows. Now I need to investigate potential outliers more systematically. I'll check for statistical outliers using the IQR method (values beyond 1.5×IQR from Q1/Q3) for each measurement dimension, and also look at the species distribution to see if the duplicates or any extreme values are concentrated in one species.", "tool": "query_sql", "args": { "sql": "WITH stats AS (SELECT 'SepalLength' as measure, PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY SepalLengthCm) as q1, PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY SepalLengthCm) as q3, PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY SepalLengthCm) - PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY SepalLengthCm) as iqr FROM raw.Iris UNION ALL SELECT 'SepalWidth', PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY SepalWidthCm), PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY SepalWidthCm), PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY SepalWidthCm) - PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY SepalWidthCm) FROM raw.Iris UNION ALL SELECT 'PetalLength', PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY PetalLengthCm), PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY PetalLengthCm), PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY PetalLengthCm) - PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY PetalLengthCm) FROM raw.Iris UNION ALL SELECT 'PetalWidth', PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY PetalWidthCm), PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY PetalWidthCm), PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY PetalWidthCm) - PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY PetalWidthCm) FROM raw.Iris) SELECT measure, q1, q3, iqr, ROUND(q1 - 1.5 * iqr, 2) as lower_fence, ROUND(q3 + 1.5 * iqr, 2) as upper_fence FROM stats", "purpose": "Calculate IQR-based outlier fences for each measurement to identify statistical outliers", "source": "raw" } } ```