GH-49875: [Python] Fix timezone dropped when converting tz-aware Categorical to Arrow array#49878
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… Categorical to Arrow array
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Hi @AlenkaF |
AlenkaF
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I think this change makes sense but the PR is lacking a test. The reproducible example from the issue can be reused and added to https://github.com/apache/arrow/blob/main/python/pyarrow/tests/test_pandas.py mimicking existing categorical tests.
cc @jorisvandenbossche in case of any opinions.
Thank you for the review! |
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CI failures are related, could you have a look? |
Fixed:
Please retrigger the CI |
jorisvandenbossche
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@github-actions crossbow submit pandas |
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Revision: 0f1f595 Submitted crossbow builds: ursacomputing/crossbow @ actions-3f725ba4fc
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AlenkaF
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Thanks! The failing extended builds are not connected. Will try to see if there is an issue opened already to track that.
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Opened an issue for the failing builds here: #49920 |
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@jorisvandenbossche mind having one more look before I merge? |
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Rationale for this change
When converting a pandas.Categorical with tz-aware datetime categories to a PyArrow array, the timezone information was silently dropped from the dictionary array's value type. This is a silent data loss bug — no warning or error is raised, but the timezone metadata is lost.
What changes are included in this PR?
In
python/pyarrow/array.pxi, the Categorical conversion was usingvalues.categories.values(raw numpy array)which strips timezone metadata since numpy does not support tz-aware datetimes. Changed to values.categories (pandas Index) and added from_pandas=True so PyArrow uses the pandas conversion path, which correctly preserves timezone metadata.Are these changes tested?
Yes. Verified manually
Are there any user-facing changes?
Yes — this is a bug fix. Users did #49875
This PR contains a "Critical Fix" — timezone information was lost silently during conversion without any warning or error.