refactorpandas

Features and purpose

Refactor Pandas code to improve maintainability, readability, and performance. Identifies and fixes loops/.iterrows() that should be vectorized, overuse of .apply() where vectorized alternatives exist, chained indexing patterns, inplace=True usage, inefficient dtypes, missing method chaining opportunities, complex filters, merge operations without validation, and SettingWithCopyWarning patterns. Applies Pandas 2.0+ features including PyArrow backend, Copy-on-Write, vectorized operations, method chaining, .query()/.eval(), optimized dtypes, and pipeline patterns.

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