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BUG: Index.drop raising Error when Index has duplicates #38070

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Merged
merged 13 commits into from
Dec 2, 2020
2 changes: 2 additions & 0 deletions doc/source/whatsnew/v1.2.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -689,6 +689,7 @@ MultiIndex
- Bug in :meth:`DataFrame.reset_index` with ``NaT`` values in index raises ``ValueError`` with message ``"cannot convert float NaN to integer"`` (:issue:`36541`)
- Bug in :meth:`DataFrame.combine_first` when used with :class:`MultiIndex` containing string and ``NaN`` values raises ``TypeError`` (:issue:`36562`)
- Bug in :meth:`MultiIndex.drop` dropped ``NaN`` values when non existing key was given as input (:issue:`18853`)
- Bug in :meth:`MultiIndex.drop` dropping more values than expected when index has duplicates and is not sorted (:issue:`33494`)

I/O
^^^
Expand Down Expand Up @@ -821,6 +822,7 @@ Other
- Bug in :meth:`Index.intersection` with non-matching numeric dtypes casting to ``object`` dtype instead of minimal common dtype (:issue:`38122`)
- Passing an array with 2 or more dimensions to the :class:`Series` constructor now raises the more specific ``ValueError`` rather than a bare ``Exception`` (:issue:`35744`)
- Bug in ``dir`` where ``dir(obj)`` wouldn't show attributes defined on the instance for pandas objects (:issue:`37173`)
- Bug in :meth:`Index.drop` raising ``InvalidIndexError`` when index has duplicates (:issue:`38051`)
- Bug in :meth:`RangeIndex.difference` returning :class:`Int64Index` in some cases where it should return :class:`RangeIndex` (:issue:`38028`)

.. ---------------------------------------------------------------------------
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2 changes: 1 addition & 1 deletion pandas/core/indexes/base.py
Original file line number Diff line number Diff line change
Expand Up @@ -5564,7 +5564,7 @@ def drop(self, labels, errors: str_t = "raise"):
"""
arr_dtype = "object" if self.dtype == "object" else None
labels = com.index_labels_to_array(labels, dtype=arr_dtype)
indexer = self.get_indexer(labels)
indexer = self.get_indexer_for(labels)
mask = indexer == -1
if mask.any():
if errors != "ignore":
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3 changes: 2 additions & 1 deletion pandas/core/indexes/multi.py
Original file line number Diff line number Diff line change
Expand Up @@ -2165,7 +2165,8 @@ def drop(self, codes, level=None, errors="raise"):
if isinstance(loc, int):
inds.append(loc)
elif isinstance(loc, slice):
inds.extend(range(loc.start, loc.stop))
step = loc.step if loc.step is not None else 1
inds.extend(range(loc.start, loc.stop, step))
elif com.is_bool_indexer(loc):
if self.lexsort_depth == 0:
warnings.warn(
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12 changes: 12 additions & 0 deletions pandas/tests/indexes/multi/test_drop.py
Original file line number Diff line number Diff line change
@@ -1,3 +1,5 @@
import warnings

import numpy as np
import pytest

Expand Down Expand Up @@ -149,6 +151,16 @@ def test_drop_with_nan_in_index(nulls_fixture):
mi.drop(pd.Timestamp("2001"), level="date")


def test_drop_with_non_monotonic_duplicates():
# GH#33494
mi = MultiIndex.from_tuples([(1, 2), (2, 3), (1, 2)])
with warnings.catch_warnings():
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could maybe use @pytest.mark.filterwarnings as a follow-up

warnings.simplefilter("ignore", PerformanceWarning)
result = mi.drop((1, 2))
expected = MultiIndex.from_tuples([(2, 3)])
tm.assert_index_equal(result, expected)


def test_single_level_drop_partially_missing_elements():
# GH 37820

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13 changes: 13 additions & 0 deletions pandas/tests/indexes/test_base.py
Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import pytest

from pandas._libs.tslib import Timestamp
from pandas.compat import IS64
from pandas.compat.numpy import np_datetime64_compat
from pandas.util._test_decorators import async_mark

Expand All @@ -19,6 +20,7 @@
DatetimeIndex,
Float64Index,
Int64Index,
IntervalIndex,
PeriodIndex,
RangeIndex,
Series,
Expand Down Expand Up @@ -1505,6 +1507,17 @@ def test_drop_tuple(self, values, to_drop):
with pytest.raises(KeyError, match=msg):
removed.drop(drop_me)

def test_drop_with_duplicates_in_index(self, index):
# GH38051
if len(index) == 0 or isinstance(index, MultiIndex):
return
if isinstance(index, IntervalIndex) and not IS64:
pytest.skip("Cannot test IntervalIndex with int64 dtype on 32 bit platform")
index = index.unique().repeat(2)
expected = index[2:]
result = index.drop(index[0])
tm.assert_index_equal(result, expected)

@pytest.mark.parametrize(
"attr",
[
Expand Down