Add support for Pandas 3#2295
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ihnorton
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Feb 5, 2026
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LGTM overall but I'm nervous about the changes around string types (see inline) based on past experience.
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| if col_dtypes: | ||
| df = df.astype(col_dtypes, copy=False) | ||
| # Use str instead of '<U0' so pandas uses its native string type |
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Is our type-mapping wrong now? I don't quite follow why we need this change
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…ndling - _update_df_from_meta: casting to the zero-width '<U0'/'|S0' dtypes stored in the metadata breaks on pandas 3 (str columns turn into object, bytes into fixed-width '|S<n>' that cannot be used as an index). Replace it with an explicit bytes<->str conversion restoring the type the dimension was written with, and skip no-op casts so that dropping `copy=False` (removed in pandas 3) does not introduce extra copies on pandas 2. - ColumnInfo: distinguish the two StringDtype variants by `na_value` (per the pandas migration guide) and reuse from_dtype in from_values instead of duplicating the mapping. - _df_to_np_arrays: restore unconditional nullmap creation; the data scan guard was unnecessary and the explicit vectorized nullmap is cheaper than the per-element fallback in the write path. - Add a str/bytes dimension .df roundtrip regression test covering both the arrow and non-arrow read paths.
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This PR adds Pandas 3 support while maintaining Pandas 2 compatibility. The main change is handling the new
StringDtypethat Pandas 3 uses by default for strings.Also, added a CI step to continue on running tests using Pandas 2.
Closes CORE-487