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BUG: Bug in xs ignored droplevel #37776

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Merged
merged 7 commits into from
Nov 13, 2020
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Merged

BUG: Bug in xs ignored droplevel #37776

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c9e5e81
[BUG]: DataFrame.xs ignored droplevel for columns
phofl Nov 11, 2020
3205e8d
Move whatsnew
phofl Nov 11, 2020
6614f5e
Fix typo
phofl Nov 12, 2020
f3d54f7
Add test
phofl Nov 12, 2020
5c5eee1
Refactor code
phofl Nov 12, 2020
0f0bb77
Modify if else condition
phofl Nov 13, 2020
c0ac9b2
Merge branch 'master' of https://github.com/pandas-dev/pandas into 19056
phofl Nov 13, 2020
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.2.0.rst
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Expand Up @@ -470,6 +470,7 @@ Indexing
- Bug in :meth:`Index.where` incorrectly casting numeric values to strings (:issue:`37591`)
- Bug in :meth:`Series.loc` and :meth:`DataFrame.loc` raises when numeric label was given for object :class:`Index` although label was in :class:`Index` (:issue:`26491`)
- Bug in :meth:`DataFrame.loc` returned requested key plus missing values when ``loc`` was applied to single level from :class:`MultiIndex` (:issue:`27104`)
- Bug in :meth:`DataFrame.xs` ignored ``droplevel=False`` for columnsm (:issue:`19056`)

Missing
^^^^^^^
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4 changes: 3 additions & 1 deletion pandas/core/generic.py
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Expand Up @@ -3708,7 +3708,9 @@ class animal locomotion
return result

if axis == 1:
return self[key]
if drop_level:
return self[key]
return self[[key]]
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PITA but this causes us to make a copy instead of a view. can we re-use any of the code in the rest of the method to keep this consistent?

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Would make this pretty complex probably, but will have a look tomorrow

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This should work, but got a bit more complex. Using iloc now to select the data if droplevel=False


index = self.index
if isinstance(index, MultiIndex):
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15 changes: 15 additions & 0 deletions pandas/tests/frame/indexing/test_xs.py
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Expand Up @@ -297,3 +297,18 @@ def test_xs_levels_raises(self, klass):
msg = "Index must be a MultiIndex"
with pytest.raises(TypeError, match=msg):
obj.xs(0, level="as")

def test_xs_droplevel_false(self):
# GH: 19056
mi = MultiIndex.from_tuples(
[("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"]
)
df = DataFrame([[1, 2, 3]], columns=mi)
result = df.xs("a", axis=1, drop_level=False)
expected = DataFrame(
[[1, 2]],
columns=MultiIndex.from_tuples(
[("a", "x"), ("a", "y")], names=["level1", "level2"]
),
)
tm.assert_frame_equal(result, expected)