When getting the numpy datatype, return datetime64[D] for pa.Date32 and return datetime64[ms] for pa.Date64 #62913
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added 2 commits
October 29, 2025 20:42
…ly one common type. Return objects for date32 and date64 types when converting those types to numpy types.
jbrockmendel
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Nov 4, 2025
pandas/core/dtypes/common.py
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| # try a pyarrow dtype | ||
| from pandas.core.dtypes.dtypes import ArrowDtype | ||
| if isinstance(dtype, ArrowDtype): | ||
| return ArrowDtype(dtype) |
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do we ever get here? Seems like these cases would be caught above
jbrockmendel
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Nov 4, 2025
pandas/core/dtypes/dtypes.py
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| if pa.types.is_date32(self.pyarrow_dtype) or pa.types.is_date64( | ||
| self.pyarrow_dtype | ||
| ): | ||
| # date32 and date64 are pyarrow timestamps but do not have a |
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nitpick they are not "pyarrow timestamps"
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Removed comment and also replaced code
jbrockmendel
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Nov 4, 2025
pandas/core/dtypes/dtypes.py
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| ): | ||
| # date32 and date64 are pyarrow timestamps but do not have a | ||
| # corresponding numpy dtype. | ||
| return np.dtype(object) |
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np.datetime64[D] might be more reasonable?
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Replaced date32 with np.datetime64[D], good catch!
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@jbrockmendel
Should date64 also be cast to np.datetime64[D], or should it be kept as a timestamp[ms]?
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November 8, 2025 12:43
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linicole74
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…ests in test_arrow
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When getting the numpy datatype, return datetime64[D] for pa.Date32 and return datetime64[ms] for pa.Date64.
pa.Date64 still will not roundtrip properly since either both datetime64[ms] and date64 must convert to date64, or both datetime64[ms] and date64 must convert to timestamp64[ms].
#62343
doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.