القائمة
Aggregate tabular data by one or more dimensions with configurable metrics — sum, mean, count, min, max, median. Supports multi-level grouping and pivot table generation.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Validate tabular data against configurable business rules — range checks, cross-column constraints, referential integrity against lookup tables, and temporal consistency.
Load and parse CSV files into structured data frames with configurable encoding, delimiter, and date parsing options.
Export pandas DataFrames or processed datasets to well-formatted CSV files with configurable encoding, delimiter, quoting, and column ordering.
Comprehensive data cleaning toolkit — handles missing values, duplicate removal, type coercion, whitespace trimming, and outlier detection in a single pass over the dataset.
Identify and remove duplicate records from tabular datasets using exact-match, fuzzy-match, or composite-key-based deduplication strategies.
Universal data ingestion service that loads data from CSV, Excel, JSON, and Parquet sources into a unified DataFrame format with automatic format detection.
| name | data-aggregator |
| description | Aggregate tabular data by one or more dimensions with configurable metrics — sum, mean, count, min, max, median. Supports multi-level grouping and pivot table generation. |
| version | 0.8.0 |
Performs group-by aggregations on tabular datasets. Supports single and multi-level grouping, configurable aggregate functions (sum, mean, count, min, max, median, std), and pivot table generation for cross-dimensional analysis. Can output flat aggregation tables or pivot matrices.
--input / -i: Path to input file (CSV or Parquet) (required)--group-by / -g: Grouping columns (comma-separated) (required)--metrics: Aggregation specs like revenue:sum,quantity:mean,order_id:count--mode: flat, pivot, or rolling (default: flat)--pivot-columns: Column for pivot table columns (for pivot mode)--pivot-values: Value column for pivot table (for pivot mode)--window: Window size for rolling mode--output / -o: Output path--sort-by: Sort result by specified column (descending)python3 ./skills/data_aggregator/aggregate.py -i <file> -g <columns> --metrics <specs>pandas, numpy