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BUG: loc raising error for MultiIndex with bool indexer #49766

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Merged
merged 1 commit into from
Nov 18, 2022
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BUG: loc raising error for MultiIndex with bool indexer #49766

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.0.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -661,6 +661,7 @@ Indexing
^^^^^^^^
- Bug in :meth:`DataFrame.reindex` filling with wrong values when indexing columns and index for ``uint`` dtypes (:issue:`48184`)
- Bug in :meth:`DataFrame.loc` coercing dtypes when setting values with a list indexer (:issue:`49159`)
- Bug in :meth:`DataFrame.loc` raising ``ValueError`` with ``bool`` indexer and :class:`MultiIndex` (:issue:`47687`)
- Bug in :meth:`DataFrame.__setitem__` raising ``ValueError`` when right hand side is :class:`DataFrame` with :class:`MultiIndex` columns (:issue:`49121`)
- Bug in :meth:`DataFrame.reindex` casting dtype to ``object`` when :class:`DataFrame` has single extension array column when re-indexing ``columns`` and ``index`` (:issue:`48190`)
- Bug in :func:`~DataFrame.describe` when formatting percentiles in the resulting index showed more decimals than needed (:issue:`46362`)
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7 changes: 5 additions & 2 deletions pandas/core/indexing.py
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Expand Up @@ -1115,9 +1115,12 @@ def _validate_key(self, key, axis: Axis):
# slice of labels (where start-end in labels)
# slice of integers (only if in the labels)
# boolean not in slice and with boolean index
ax = self.obj._get_axis(axis)
if isinstance(key, bool) and not (
is_bool_dtype(self.obj._get_axis(axis))
or self.obj._get_axis(axis).dtype.name == "boolean"
is_bool_dtype(ax)
or ax.dtype.name == "boolean"
or isinstance(ax, MultiIndex)
and is_bool_dtype(ax.get_level_values(0))
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So if one wanted to index the bools in the second level (and the first level was not boolean), does that take a different code path?

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@phofl phofl Nov 18, 2022 •
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You mean something like df.loc[(slice(None), True)]?

This runs through a different path, same reason why df.loc[(True, )] worked already.

We only get there with a scalar indexer, which by definition always refers to the first level

):
raise KeyError(
f"{key}: boolean label can not be used without a boolean index"
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18 changes: 18 additions & 0 deletions pandas/tests/frame/indexing/test_indexing.py
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Expand Up @@ -1436,6 +1436,24 @@ def test_loc_rhs_empty_warning(self):
df.loc[:, "a"] = rhs
tm.assert_frame_equal(df, expected)

@pytest.mark.parametrize("indexer", [True, (True,)])
@pytest.mark.parametrize("dtype", [bool, "boolean"])
def test_loc_bool_multiindex(self, dtype, indexer):
# GH#47687
midx = MultiIndex.from_arrays(
[
Series([True, True, False, False], dtype=dtype),
Series([True, False, True, False], dtype=dtype),
],
names=["a", "b"],
)
df = DataFrame({"c": [1, 2, 3, 4]}, index=midx)
result = df.loc[indexer]
expected = DataFrame(
{"c": [1, 2]}, index=Index([True, False], name="b", dtype=dtype)
)
tm.assert_frame_equal(result, expected)


class TestDataFrameIndexingUInt64:
def test_setitem(self, uint64_frame):
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