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BUG: Fix wrong error in df drop with non unique datetime index and in…
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…valid keys (#30446)
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fujiaxiang authored and jreback committed Dec 26, 2019
1 parent 114d552 commit e46026f
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Showing 3 changed files with 19 additions and 1 deletion.
2 changes: 2 additions & 0 deletions doc/source/whatsnew/v1.0.0.rst
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Expand Up @@ -715,8 +715,10 @@ Datetimelike
- Bug in :func:`pandas.to_datetime` failing for `deques` when using ``cache=True`` (the default) (:issue:`29403`)
- Bug in :meth:`Series.item` with ``datetime64`` or ``timedelta64`` dtype, :meth:`DatetimeIndex.item`, and :meth:`TimedeltaIndex.item` returning an integer instead of a :class:`Timestamp` or :class:`Timedelta` (:issue:`30175`)
- Bug in :class:`DatetimeIndex` addition when adding a non-optimized :class:`DateOffset` incorrectly dropping timezone information (:issue:`30336`)
- Bug in :meth:`DataFrame.drop` where attempting to drop non-existent values from a DatetimeIndex would yield a confusing error message (:issue:`30399`)
- Bug in :meth:`DataFrame.append` would remove the timezone-awareness of new data (:issue:`30238`)


Timedelta
^^^^^^^^^
- Bug in subtracting a :class:`TimedeltaIndex` or :class:`TimedeltaArray` from a ``np.datetime64`` object (:issue:`29558`)
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2 changes: 1 addition & 1 deletion pandas/core/indexes/base.py
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Expand Up @@ -4551,7 +4551,7 @@ def get_indexer_non_unique(self, target):

if is_categorical(target):
tgt_values = np.asarray(target)
elif self.is_all_dates:
elif self.is_all_dates and target.is_all_dates: # GH 30399
tgt_values = target.asi8
else:
tgt_values = target._ndarray_values
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16 changes: 16 additions & 0 deletions pandas/tests/indexes/multi/test_drop.py
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Expand Up @@ -139,3 +139,19 @@ def test_drop_not_lexsorted():
tm.assert_index_equal(lexsorted_mi, not_lexsorted_mi)
with tm.assert_produces_warning(PerformanceWarning):
tm.assert_index_equal(lexsorted_mi.drop("a"), not_lexsorted_mi.drop("a"))


def test_drop_with_non_unique_datetime_index_and_invalid_keys():
# GH 30399

# define dataframe with unique datetime index
df = pd.DataFrame(
np.random.randn(5, 3),
columns=["a", "b", "c"],
index=pd.date_range("2012", freq="H", periods=5),
)
# create dataframe with non-unique datetime index
df = df.iloc[[0, 2, 2, 3]].copy()

with pytest.raises(KeyError, match="not found in axis"):
df.drop(["a", "b"]) # Dropping with labels not exist in the index

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