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BUG: infer_string not inferring string dtype when NA is first value #55655

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Merged
merged 2 commits into from
Oct 24, 2023
Merged

BUG: infer_string not inferring string dtype when NA is first value #55655

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BUG: infer_string not inferring string dtype when NA is first value
phofl Oct 23, 2023
5bdc5de
Update lib.pyx
phofl Oct 23, 2023
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.1.2.rst
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Expand Up @@ -35,6 +35,7 @@ Bug fixes
- Fixed bug in :meth:`Series.str.extractall` for :class:`ArrowDtype` dtype being converted to object (:issue:`53846`)
- Fixed bug where PDEP-6 warning about setting an item of an incompatible dtype was being shown when creating a new conditional column (:issue:`55025`)
- Silence ``Period[B]`` warnings introduced by :issue:`53446` during normal plotting activity (:issue:`55138`)
- Fixed bug in :class:`Series` constructor not inferring string dtype when ``NA`` is the first value and ``infer_string`` is set (:issue:` 55655`)

.. ---------------------------------------------------------------------------
.. _whatsnew_212.other:
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3 changes: 3 additions & 0 deletions pandas/_libs/lib.pyx
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Expand Up @@ -2665,6 +2665,9 @@ def maybe_convert_objects(ndarray[object] objects,
else:
seen.object_ = True
break
elif val is C_NA:
seen.object_ = True
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I think missing a break after this? See it in all the other branches at least

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No this is missing on purpose. We don't know which dtype we have with NA and infer-string set, so have to do another pass

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Ah OK. Does continue work here too? Assuming no difference with the current code setup, but continue would be more future-proof in case of a refactor, while also signaling intent

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Yeah sure

continue
else:
seen.object_ = True
break
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8 changes: 8 additions & 0 deletions pandas/tests/series/test_constructors.py
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Expand Up @@ -2131,6 +2131,14 @@ def test_series_constructor_infer_string_scalar(self):
tm.assert_series_equal(ser, expected)
assert ser.dtype.storage == "python"

def test_series_string_inference_na_first(self):
# GH#55655
pytest.importorskip("pyarrow")
expected = Series([pd.NA, "b"], dtype="string[pyarrow_numpy]")
with pd.option_context("future.infer_string", True):
result = Series([pd.NA, "b"])
tm.assert_series_equal(result, expected)


class TestSeriesConstructorIndexCoercion:
def test_series_constructor_datetimelike_index_coercion(self):
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