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Compute aggregate statistics (mean, median, sum, count, min, max) grouped by a column.
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Basado en la clasificación ocupacional SOC
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Export pandas DataFrames or processed datasets to well-formatted CSV files with configurable encoding, delimiter, quoting, and column ordering.
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Comprehensive data cleaning toolkit — handles missing values, duplicate removal, type coercion, whitespace trimming, and outlier detection in a single pass over the dataset.
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| name | stats-aggregator |
| description | Compute aggregate statistics (mean, median, sum, count, min, max) grouped by a column. |
| version | 1.0.0 |
Groups records by a specified column and computes configurable aggregate statistics on a numeric value column. Supports six standard statistical metrics: mean, median, sum, count, min, and max.
--input / -i: Path to JSON records file (required)--group-by / -g: Column name to group records by (required)--value-column / -v: Numeric column to aggregate (required)--metrics: Comma-separated metrics to compute (default: mean,median,sum,count,min,max)--output / -o: Output directory (required)| Metric | Description | Python Function |
|---|---|---|
mean | Arithmetic mean | statistics.mean() |
median | Middle value | statistics.median() |
sum | Sum of all values | sum() |
count | Number of records | len() |
min | Minimum value | min() |
max | Maximum value | max() |
stats_report.jsonstats_report.json with structure:
{
"group_column": "region",
"groups": {
"North": {"mean": 150.5, "median": 140.0, "sum": 3010, "count": 20, "min": 80, "max": 250},
"South": {"mean": 120.3, ...}
}
}
python3 stats-aggregator/aggregator.py -i <file> -g region -v revenue -o <dir>json, statistics, argparse, os)