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A senior-data-engineer-style skill for pandas: idiomatic DataFrame transformations, ETL pipelines, performance tuning, and time-series operations in Python.
Provides an expert-level pandas assistant that writes idiomatic, vectorized DataFrame code, designs reproducible ETL pipelines, and gives performance recommendations for datasets from small to very large. It covers merges, groupby patterns, time-series resampling, dtype tuning, chunked processing, and integration with PyArrow/Parquet.
Invoke this skill when you need code-first guidance for data cleaning, transformation, merging multiple tables, building ETL pipelines, or optimizing pandas workflows for memory and speed. Useful for analysts, data engineers, and ML feature engineering.
Best used with developer-focused LLM agents and coding assistants that can produce runnable Python snippets (Copilot, Cursor, Claude Code, etc.).
This skill has not been reviewed by our automated audit pipeline yet.
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