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REGR: MultiIndex.append raising for overlapping IntervalIndex levels #54945

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Merged
merged 3 commits into from
Sep 2, 2023
Merged

REGR: MultiIndex.append raising for overlapping IntervalIndex levels #54945

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ee7b3f6
fix regression in MultiIndex.append for overlapping IntervalIndex levels
lukemanley Sep 2, 2023
28e9065
use get_indexer_for
lukemanley Sep 2, 2023
68ba819
Merge branch 'main' into mi-append-overlapping-intervals
phofl Sep 2, 2023
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.1.1.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@ Fixed regressions
- Fixed regression in :func:`read_csv` when ``usecols`` is given and ``dtypes`` is a dict for ``engine="python"`` (:issue:`54868`)
- Fixed regression in :meth:`.GroupBy.get_group` raising for ``axis=1`` (:issue:`54858`)
- Fixed regression in :meth:`DataFrame.__setitem__` raising ``AssertionError`` when setting a :class:`Series` with a partial :class:`MultiIndex` (:issue:`54875`)
- Fixed regression in :meth:`MultiIndex.append` raising when appending overlapping :class:`IntervalIndex` levels (:issue:`54934`)
- Fixed regression in :meth:`Series.drop_duplicates` for PyArrow strings (:issue:`54904`)
- Fixed regression in :meth:`Series.value_counts` raising for numeric data if ``bins`` was specified (:issue:`54857`)
- Fixed regression when comparing a :class:`Series` with ``datetime64`` dtype with ``None`` (:issue:`54870`)
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2 changes: 1 addition & 1 deletion pandas/core/arrays/categorical.py
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Expand Up @@ -2948,7 +2948,7 @@ def recode_for_categories(
return codes

indexer = coerce_indexer_dtype(
new_categories.get_indexer(old_categories), new_categories
new_categories.get_indexer_for(old_categories), new_categories
)
new_codes = take_nd(indexer, codes, fill_value=-1)
return new_codes
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22 changes: 22 additions & 0 deletions pandas/tests/indexes/multi/test_reshape.py
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Expand Up @@ -169,6 +169,28 @@ def test_append_names_dont_match():
tm.assert_index_equal(result, expected)


def test_append_overlapping_interval_levels():
# GH 54934
ivl1 = pd.IntervalIndex.from_breaks([0.0, 1.0, 2.0])
ivl2 = pd.IntervalIndex.from_breaks([0.5, 1.5, 2.5])
mi1 = MultiIndex.from_product([ivl1, ivl1])
mi2 = MultiIndex.from_product([ivl2, ivl2])
result = mi1.append(mi2)
expected = MultiIndex.from_tuples(
[
(pd.Interval(0.0, 1.0), pd.Interval(0.0, 1.0)),
(pd.Interval(0.0, 1.0), pd.Interval(1.0, 2.0)),
(pd.Interval(1.0, 2.0), pd.Interval(0.0, 1.0)),
(pd.Interval(1.0, 2.0), pd.Interval(1.0, 2.0)),
(pd.Interval(0.5, 1.5), pd.Interval(0.5, 1.5)),
(pd.Interval(0.5, 1.5), pd.Interval(1.5, 2.5)),
(pd.Interval(1.5, 2.5), pd.Interval(0.5, 1.5)),
(pd.Interval(1.5, 2.5), pd.Interval(1.5, 2.5)),
]
)
tm.assert_index_equal(result, expected)


def test_repeat():
reps = 2
numbers = [1, 2, 3]
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