I have already obtained the distribution summary for the numeric columns in this dataset. Let me present these findings: ```json { "action": "final", "content": "## Numeric Column Distribution Summary\n\nThe dataset contains **2 numeric columns** with the following distributions:\n\n### Player ID\n- **Range**: 90,000 to 146,262\n- **Mean**: 120,369.41\n- **Median**: 120,576.50\n- **Standard Deviation**: 12,184.90\n- **Coverage**: 37,620 non-null values (100% complete)\n\nThe Player ID distribution is nearly symmetric (mean ≈ median), with IDs spanning a range of ~56,000 values. The standard deviation of ~12,185 indicates moderate spread around the central tendency.\n\n### Birth Year\n- **Range**: 0 to 2014\n- **Mean**: 1975.87\n- **Median**: 1995.00\n- **Standard Deviation**: 179.58\n- **Coverage**: 28,184 non-null values (74.9% complete)\n\nThe Birth Year distribution shows:\n- A **19-year gap** between mean (1975.87) and median (1995.00), indicating a left-skewed distribution with older birth years pulling the mean down\n- The minimum value of **0** likely represents missing or placeholder data rather than actual birth years\n- The standard deviation of ~180 years suggests substantial spread, though this is inflated by the anomalous minimum value\n- **25.1% missing data** (9,436 players without birth year information)\n\nThe birth year data would benefit from cleaning to handle the zero values and investigate whether they represent truly unknown birth years or data quality issues." } ```