BUG: Fix groupby.apply() dropping _metadata from subclassed DataFrame #62135
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When extending pandas.DataFrame by subclassing, most operations preserve the _metadata attributes. This fix ensures that groupby.apply() also preserves these fields, making it consistent with other groupby operations like groupby.sum(). Fixes pandas-dev#62134
rhshadrach
reviewed
Aug 18, 2025
- Update metadata preservation logic for DataFrames and Series in groupby operations - Fix DataFrame.__setitem__ with MultiIndex columns and scalar indexer - Adjust formatting and naming conventions in the code
Thanks! |
… scalar value - Address issue where name attribute was lost when setting new column with scalar value and tuple key in MultiIndex DataFrame - Implement check for tuple key and scalar value in MultiIndex DataFrame - Create Series with proper name to ensure name attribute matches the key - Update test case to assert Series name in scalar assignment with MultiIndex
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@rhshadrach Why this failed? Unit Tests / Linux-32-bit (pull_request) and Unit Tests / Pyodide build (pull_request) |
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Seems related to the change you're making here in |
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When extending pandas.DataFrame by subclassing, most operations preserve the _metadata attributes. This fix ensures that groupby.apply() also preserves these fields, making it consistent with other groupby operations like groupby.sum().
Fixes #62134