FIX: Preserve dtypes when using scalar row + slice columns indexing #63081
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Signed-off-by: SoulSniper1212 <warush23@gmail.com>
rhshadrach
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Nov 20, 2025
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Thanks for the PR. Please always add tests.
added 5 commits
November 21, 2025 12:26
…-dataframe-loc-returns-object-type-instead-of-f
rhshadrach
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Nov 25, 2025
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| # For scalar row + slice columns, process by first getting the column slice | ||
| # to preserve dtypes, then extracting the row | ||
| # Otherwise, reverse tuple so that we are indexing along columns before rows |
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Don't these both say the same thing? To do columns first and then rows?
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Based on the contributor's history, I believe this is an AI generated PR so closing. |
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Overview
This PR fixes an issue where using scalar row + slice columns indexing (e.g.
df[scalar_row, slice_columns]) would not preserve column dtypes properly. The fix implements a special case for this indexing pattern to first extract the column slice, preserving dtypes, then extract the specific row.Checklist
Proof
The fix addresses issue #63071 by handling the scalar row + slice columns case specifically in
_LocationIndexer._getitem_lowerdim. The solution first gets the column slice to create a sub-DataFrame with preserved column dtypes, then extracts the required row from this sub-DataFrame. This ensures that the resulting Series maintains the original column dtypes as expected.Closes #63071