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BUG: is_string_dtype(pd.Index([], dtype='O')) returns False #54997

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merged 11 commits into from
Oct 4, 2023
Merged

BUG: is_string_dtype(pd.Index([], dtype='O')) returns False #54997

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1426611
correct def is_all_strings
natmokval Sep 4, 2023
73962fd
Merge branch 'main' into bug-is_string_dtype-obj-empty
natmokval Sep 6, 2023
91c8b2a
add a test, correct whatsnew/v2.2.0.rst
natmokval Sep 7, 2023
96680cb
move the test and add parametrization, correct v2.2.0.rst
natmokval Sep 11, 2023
db0dcdd
remove the line from v2.2.0.rst
natmokval Sep 13, 2023
d163e71
Merge branch 'main' into bug-is_string_dtype-obj-empty
natmokval Sep 13, 2023
46aafed
add the note to v2.1.1.rst
natmokval Sep 19, 2023
d076edb
correct the whatsnew note and move it to 2.2.0
natmokval Sep 26, 2023
d4a54b4
resolve conflict
natmokval Sep 26, 2023
8ea61bd
Merge branch 'main' into bug-is_string_dtype-obj-empty
natmokval Oct 3, 2023
3945bb0
Merge branch 'main' into bug-is_string_dtype-obj-empty
natmokval Oct 3, 2023
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.1.1.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,7 @@ Fixed regressions
Bug fixes
~~~~~~~~~
- Fixed bug for :class:`ArrowDtype` raising ``NotImplementedError`` for fixed-size list (:issue:`55000`)
- Fixed bug in :func:`is_string_dtype` while checking object array with no elements is of the string dtype (:issue:`54661`)
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I think you'll need this to be

:func:`pandas.api.types.is_string_dtype`

and to move this to 2.2

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thanks, I corrected the note in whatsnew and moved it to 2.2.0

- Fixed bug in :meth:`DataFrame.stack` with ``future_stack=True`` and columns a non-:class:`MultiIndex` consisting of tuples (:issue:`54948`)
- Fixed bug in :meth:`Series.pct_change` and :meth:`DataFrame.pct_change` showing unnecessary ``FutureWarning`` (:issue:`54981`)

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9 changes: 6 additions & 3 deletions pandas/core/dtypes/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1664,9 +1664,12 @@ def is_all_strings(value: ArrayLike) -> bool:
dtype = value.dtype

if isinstance(dtype, np.dtype):
return dtype == np.dtype("object") and lib.is_string_array(
np.asarray(value), skipna=False
)
if len(value) == 0:
return dtype == np.dtype("object")
else:
return dtype == np.dtype("object") and lib.is_string_array(
np.asarray(value), skipna=False
)
elif isinstance(dtype, CategoricalDtype):
return dtype.categories.inferred_type == "string"
return dtype == "string"
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25 changes: 17 additions & 8 deletions pandas/tests/dtypes/test_common.py
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Expand Up @@ -301,14 +301,23 @@ def test_is_categorical_dtype():
assert com.is_categorical_dtype(pd.CategoricalIndex([1, 2, 3]))


def test_is_string_dtype():
assert not com.is_string_dtype(int)
assert not com.is_string_dtype(pd.Series([1, 2]))

assert com.is_string_dtype(str)
assert com.is_string_dtype(object)
assert com.is_string_dtype(np.array(["a", "b"]))
assert com.is_string_dtype(pd.StringDtype())
@pytest.mark.parametrize(
"dtype, expected",
[
(int, False),
(pd.Series([1, 2]), False),
(str, True),
(object, True),
(np.array(["a", "b"]), True),
(pd.StringDtype(), True),
(pd.Index([], dtype="O"), True),
],
)
def test_is_string_dtype(dtype, expected):
# GH#54661

result = com.is_string_dtype(dtype)
assert result is expected


@pytest.mark.parametrize(
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