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1 change: 1 addition & 0 deletions pandas-stubs/core/indexes/datetimes.pyi
Original file line number Diff line number Diff line change
Expand Up @@ -97,6 +97,7 @@ class DatetimeIndex( # type: ignore[misc]
def tzinfo(self) -> tzinfo | None: ...
@property
def dtype(self) -> np.dtype | DatetimeTZDtype: ...
def intersection(self, other: DatetimeIndex | list) -> DatetimeIndex: ...
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list is too broad. I think Sequence[DatetimeLike] will work where you import DatetimeLike from pandas._typing


def date_range(
start: str | DateAndDatetimeLike | None = ...,
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9 changes: 9 additions & 0 deletions tests/test_indexes.py
Original file line number Diff line number Diff line change
Expand Up @@ -978,3 +978,12 @@ def test_index_constructors():
# to specify all the possible dtype options. For right now, we will leave the
# test here as a reminder that we would like this to be seen as incorrect usage.
pd.Index(flist, dtype=np.float16)


def test_datetimeindex_intersection():
idx1 = pd.DatetimeIndex(["2022-01-01", "2022-01-02"])
idx2 = pd.DatetimeIndex(["2022-01-02", "2022-01-03"])

result = idx1.intersection(idx2)

check(assert_type(result, pd.DatetimeIndex), pd.DatetimeIndex)
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If you include the list[DatetimeLike] as I suggested, then you should include tests that do intersection() with lists of those 3 different types. E.g., idx1.intersection([pd.Timestamp(x) for x in idx2]) and something similar for dt.datetime and np.datetime64