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REGR: Fix comparison broadcasting over array of Intervals #35938

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Merged
merged 9 commits into from
Aug 31, 2020
Merged

REGR: Fix comparison broadcasting over array of Intervals #35938

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9d962dd
Don't set Interval __array_priority__
dsaxton Aug 28, 2020
8c93c55
Add xfailing test
dsaxton Aug 28, 2020
1b87f7e
Merge remote-tracking branch 'upstream/master' into interval-array-pr…
dsaxton Aug 28, 2020
5eaf357
Add array broadcast test
dsaxton Aug 28, 2020
5882821
Merge remote-tracking branch 'upstream/master' into interval-array-pr…
dsaxton Aug 28, 2020
83f2a59
Merge remote-tracking branch 'upstream/master' into interval-array-pr…
dsaxton Aug 30, 2020
4b4e4f7
__richcmp__
dsaxton Aug 30, 2020
10bcf39
Param over types
dsaxton Aug 31, 2020
49ae271
Merge remote-tracking branch 'upstream/master' into interval-array-pr…
dsaxton Aug 31, 2020
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.1.2.rst
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Expand Up @@ -16,6 +16,7 @@ Fixed regressions
~~~~~~~~~~~~~~~~~
- Regression in :meth:`DatetimeIndex.intersection` incorrectly raising ``AssertionError`` when intersecting against a list (:issue:`35876`)
- Performance regression for :meth:`RangeIndex.format` (:issue:`35712`)
- Regression in :meth:`DataFrame.replace` where a ``TypeError`` would be raised when attempting to replace elements of type :class:`Interval` (:issue:`35931`)
-


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1 change: 0 additions & 1 deletion pandas/_libs/interval.pyx
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Expand Up @@ -299,7 +299,6 @@ cdef class Interval(IntervalMixin):
True
"""
_typ = "interval"
__array_priority__ = 1000

cdef readonly object left
"""
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7 changes: 7 additions & 0 deletions pandas/tests/frame/methods/test_replace.py
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Expand Up @@ -1581,3 +1581,10 @@ def test_replace_with_compiled_regex(self):
result = df.replace({regex: "z"}, regex=True)
expected = pd.DataFrame(["z", "b", "c"])
tm.assert_frame_equal(result, expected)

def test_replace_intervals(self):
# https://github.com/pandas-dev/pandas/issues/35931
df = pd.DataFrame({"a": [pd.Interval(0, 1), pd.Interval(0, 1)]})
result = df.replace({"a": {pd.Interval(0, 1): "x"}})
expected = pd.DataFrame({"a": ["x", "x"]})
tm.assert_frame_equal(result, expected)