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BUG: boolean indexer with NA raising when reindex is necessary #47623

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Merged
merged 4 commits into from
Jul 8, 2022
Merged

BUG: boolean indexer with NA raising when reindex is necessary #47623

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16c712e
BUG: boolean indexer with NA raising when reindex is necessary
phofl Jul 7, 2022
7d946d6
Add tests
phofl Jul 7, 2022
184681a
Remove space
phofl Jul 8, 2022
53d437b
Use indexer
phofl Jul 8, 2022
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v1.5.0.rst
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@

.. _whatsnew_150:

What's new in 1.5.0 (??)
Expand Down Expand Up @@ -885,6 +886,7 @@ Indexing
- Bug when setting a value too large for a :class:`Series` dtype failing to coerce to a common type (:issue:`26049`, :issue:`32878`)
- Bug in :meth:`loc.__setitem__` treating ``range`` keys as positional instead of label-based (:issue:`45479`)
- Bug in :meth:`Series.__setitem__` when setting ``boolean`` dtype values containing ``NA`` incorrectly raising instead of casting to ``boolean`` dtype (:issue:`45462`)
- Bug in :meth:`Series.loc` raising with boolean indexer containing ``NA`` when :class:`Index` did not match (:issue:`46551`)
- Bug in :meth:`Series.__setitem__` where setting :attr:`NA` into a numeric-dtype :class:`Series` would incorrectly upcast to object-dtype rather than treating the value as ``np.nan`` (:issue:`44199`)
- Bug in :meth:`DataFrame.loc` when setting values to a column and right hand side is a dictionary (:issue:`47216`)
- Bug in :meth:`DataFrame.loc` when setting a :class:`DataFrame` not aligning index in some cases (:issue:`47578`)
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4 changes: 4 additions & 0 deletions pandas/core/indexing.py
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Expand Up @@ -30,6 +30,7 @@
from pandas.core.dtypes.common import (
is_array_like,
is_bool_dtype,
is_extension_array_dtype,
is_hashable,
is_integer,
is_iterator,
Expand Down Expand Up @@ -2531,6 +2532,9 @@ def check_bool_indexer(index: Index, key) -> np.ndarray:
"""
result = key
if isinstance(key, ABCSeries) and not key.index.equals(index):
if is_extension_array_dtype(result):
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I think checking the indexer approach may be more robust here instead. Would this hit 3rd party EA dtypes and _mask may not be defined?

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Not sure if this hit in a code path where ExtensionDtype._is_boolean = True

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agree here

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Also much more performant to check result.dtype than just result

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Switched to indexer

result[result.values._mask] = False

result = result.reindex(index)
mask = isna(result._values)
if mask.any():
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19 changes: 19 additions & 0 deletions pandas/tests/series/indexing/test_indexing.py
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Expand Up @@ -5,7 +5,10 @@
import numpy as np
import pytest

from pandas.errors import IndexingError

from pandas import (
NA,
DataFrame,
IndexSlice,
MultiIndex,
Expand Down Expand Up @@ -330,6 +333,22 @@ def test_loc_setitem_all_false_indexer():
tm.assert_series_equal(ser, expected)


def test_loc_boolean_indexer_non_matching_index():
# GH#46551
ser = Series([1])
result = ser.loc[Series([NA, False], dtype="boolean")]
expected = Series([], dtype="int64")
tm.assert_series_equal(result, expected)


def test_loc_boolean_indexer_miss_matching_index():
# GH#46551
ser = Series([1])
indexer = Series([NA, False], dtype="boolean", index=[1, 2])
with pytest.raises(IndexingError, match="Unalignable"):
ser.loc[indexer]


class TestDeprecatedIndexers:
@pytest.mark.parametrize("key", [{1}, {1: 1}])
def test_getitem_dict_and_set_deprecated(self, key):
Expand Down