py-data

Build and review reliable Python data workflows with pandas 3, Polars, NumPy, Arrow, DuckDB, CSV, Parquet, and ETL patterns. Use for DataFrame transformations, schema design, null handling, joins, aggregations, time series, lazy or streaming execution, large-file processing, migration from pandas 2, and data quality validation.

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