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ENH/TST: Add BaseMethodsTests tests for ArrowExtensionArray #47552

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Merged
merged 10 commits into from
Jul 5, 2022
Merged

ENH/TST: Add BaseMethodsTests tests for ArrowExtensionArray #47552

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11f1213
ENH/TST: Add BaseMethodsTests tests for ArrowExtensionArray
mroeschke Jun 30, 2022
36b120a
Passing test now
mroeschke Jun 30, 2022
ab01083
Merge remote-tracking branch 'upstream/main' into arrow/method
mroeschke Jun 30, 2022
24670cd
add xfails for arraymanager
mroeschke Jun 30, 2022
9d29395
Fix typo
mroeschke Jun 30, 2022
30cddcf
Trigger CI
mroeschke Jun 30, 2022
f1fc664
Add xfails for min version and datamanger
mroeschke Jun 30, 2022
fce20ca
Merge remote-tracking branch 'upstream/main' into arrow/method
mroeschke Jul 1, 2022
5858824
Adjust more tests
mroeschke Jul 1, 2022
805ca5b
Merge remote-tracking branch 'upstream/main' into arrow/method
mroeschke Jul 5, 2022
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10 changes: 6 additions & 4 deletions pandas/core/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -983,10 +983,12 @@ def unique(self):

if not isinstance(values, np.ndarray):
result: ArrayLike = values.unique()
if self.dtype.kind in ["m", "M"] and isinstance(self, ABCSeries):
# GH#31182 Series._values returns EA, unpack for backward-compat
if getattr(self.dtype, "tz", None) is None:
result = np.asarray(result)
if (
isinstance(self.dtype, np.dtype) and self.dtype.kind in ["m", "M"]
) and isinstance(self, ABCSeries):
# GH#31182 Series._values returns EA
# unpack numpy datetime for backward-compat
result = np.asarray(result)
else:
result = unique1d(values)

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4 changes: 2 additions & 2 deletions pandas/tests/extension/base/methods.py
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Expand Up @@ -5,6 +5,7 @@
import pytest

from pandas.core.dtypes.common import is_bool_dtype
from pandas.core.dtypes.missing import na_value_for_dtype

import pandas as pd
import pandas._testing as tm
Expand Down Expand Up @@ -49,8 +50,7 @@ def test_value_counts_with_normalize(self, data):
else:
expected = pd.Series(0.0, index=result.index)
expected[result > 0] = 1 / len(values)

if isinstance(data.dtype, pd.core.dtypes.dtypes.BaseMaskedDtype):
if na_value_for_dtype(data.dtype) is pd.NA:
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not for this PR, but we probably need to find a way to let authors define na_value_for_dtype

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Probably similar to #27825

# TODO(GH#44692): avoid special-casing
expected = expected.astype("Float64")

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