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761ac0e
DOC: Clarify list-like vs scalar in Series.eq docstring
Aniketsy Aug 24, 2025
29662c0
Merge branch 'main' of https://github.com/pandas-dev/pandas
Aniketsy Aug 26, 2025
2f98bd4
BUG: Remove special-casing for date objects in DatetimeIndex indexing…
Aniketsy Aug 26, 2025
69ae807
BUG: Remove special-casing for date objects in DatetimeIndex indexing…
Aniketsy Aug 26, 2025
7441046
Revert unintended changes in datetimes.py and test_asfreq.py
Aniketsy Aug 29, 2025
149b9c4
Revert unintended changes in datetimes.py and test_asfreq.py
Aniketsy Aug 29, 2025
6c8b76a
Remove unintended changes in pandas/core/indexes/datetimes.py
Aniketsy Aug 29, 2025
0a0f582
API: Remove implicit matching of datetime.date with DatetimeIndex/Tim…
Aniketsy Aug 31, 2025
30a87b4
API: Remove implicit matching of datetime.date with DatetimeIndex/Tim…
Aniketsy Aug 31, 2025
f8e4974
API: Remove implicit matching of datetime.date with DatetimeIndex/Tim…
Aniketsy Sep 1, 2025
610868f
BUG: Remove special-casing for Python date objects in DatetimeIndex.g…
Aniketsy Sep 11, 2025
6583c57
BUG: Remove special-casing for Python date objects in DatetimeIndex
Aniketsy Sep 29, 2025
1c59ae7
BUG: Remove special-casing for Python date objects in DatetimeIndex
Aniketsy Sep 29, 2025
19d0357
BUG: Remove special-casing for Python date objects in DatetimeIndex
Aniketsy Oct 17, 2025
ea62b68
BUG: Remove special-casing for Python date objects in DatetimeIndex
Aniketsy Oct 18, 2025
d03cb23
BUG: Remove special-casing for Python date objects in DatetimeIndex
Aniketsy Oct 18, 2025
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v3.0.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -889,6 +889,8 @@ Datetimelike
- Bug in constructing arrays with :class:`ArrowDtype` with ``timestamp`` type incorrectly allowing ``Decimal("NaN")`` (:issue:`61773`)
- Bug in constructing arrays with a timezone-aware :class:`ArrowDtype` from timezone-naive datetime objects incorrectly treating those as UTC times instead of wall times like :class:`DatetimeTZDtype` (:issue:`61775`)
- Bug in setting scalar values with mismatched resolution into arrays with non-nanosecond ``datetime64``, ``timedelta64`` or :class:`DatetimeTZDtype` incorrectly truncating those scalars (:issue:`56410`)
- Removed the special casing for sequences of Python ``date`` objects in ``DatetimeIndex.get_indexer`` and related indexing logic.
Indexing a ``DatetimeIndex`` with Python ``date`` objects now behaves consistently with other types. (:issue:`62158`)

Timedelta
^^^^^^^^^
Expand Down
6 changes: 0 additions & 6 deletions pandas/core/indexes/base.py
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,6 @@
no_default,
)
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
Timestamp,
tz_compare,
)
Expand Down Expand Up @@ -6204,11 +6203,6 @@ def _maybe_downcast_for_indexing(self, other: Index) -> tuple[Index, Index]:
# standardize on UTC
return self.tz_convert("UTC"), other.tz_convert("UTC")

elif self.inferred_type == "date" and isinstance(other, ABCDatetimeIndex):
try:
return type(other)(self), other
except OutOfBoundsDatetime:
return self, other
elif self.inferred_type == "timedelta" and isinstance(other, ABCTimedeltaIndex):
# TODO: we dont have tests that get here
return type(other)(self), other
Expand Down
23 changes: 23 additions & 0 deletions pandas/tests/frame/indexing/test_indexing.py
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
import re

import numpy as np
import pyarrow as pa
import pytest

from pandas._libs import iNaT
Expand Down Expand Up @@ -1880,6 +1881,28 @@ def test_add_new_column_infer_string():
tm.assert_frame_equal(df, expected)


def test_datetime_indexer_consistency_pyarrow_date32():
# GH#62158
pytest.importorskip("pyarrow", minversion="13.0.0")
ser = Series(["2016-01-01"], dtype="date32[pyarrow]")
ser3 = ser.astype("datetime64[ns]")
dti = Index(ser3)

# Make sure we don't treat Arrow date as timestamp
dtype = ser.dtype.arrow_dtype
assert not (dtype.kind == "M" and not pa.types.is_date(dtype))

with pytest.raises(KeyError):
dti.get_loc(ser[0])

# get_indexer returns -1 for both Arrow array and object-cast
result = dti.get_indexer(ser.values)
tm.assert_numpy_array_equal(result, np.array([-1], dtype=np.intp))

result_obj = dti.get_indexer(ser.values.astype(object))
tm.assert_numpy_array_equal(result_obj, np.array([-1], dtype=np.intp))


class TestSetitemValidation:
# This is adapted from pandas/tests/arrays/masked/test_indexing.py
def _check_setitem_invalid(self, df, invalid, indexer):
Expand Down
7 changes: 4 additions & 3 deletions pandas/tests/frame/methods/test_asfreq.py
Original file line number Diff line number Diff line change
Expand Up @@ -192,9 +192,10 @@ def test_asfreq_with_date_object_index(self, frame_or_series):
ts2 = ts.copy()
ts2.index = [x.date() for x in ts2.index]

result = ts2.asfreq("4h", method="ffill")
expected = ts.asfreq("4h", method="ffill")
tm.assert_equal(result, expected)
with pytest.raises(
TypeError, match="Cannot compare Timestamp with datetime.date"
):
ts2.asfreq("4h", method="ffill")

def test_asfreq_with_unsorted_index(self, frame_or_series):
# GH#39805
Expand Down
18 changes: 12 additions & 6 deletions pandas/tests/indexes/datetimes/test_indexing.py
Original file line number Diff line number Diff line change
Expand Up @@ -514,10 +514,11 @@ def test_contains_nonunique(self, vals):

class TestGetIndexer:
def test_get_indexer_date_objs(self):
# Behavior for get_indexer with date objects changed in GH#62158.
rng = date_range("1/1/2000", periods=20)

result = rng.get_indexer(rng.map(lambda x: x.date()))
expected = rng.get_indexer(rng)
expected = np.full(len(rng), -1, dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)

def test_get_indexer(self):
Expand Down Expand Up @@ -562,17 +563,22 @@ def test_get_indexer(self):
idx.get_indexer(idx[[0]], method="nearest", tolerance="foo")

@pytest.mark.parametrize(
"target",
"target, expected",
[
[date(2020, 1, 1), Timestamp("2020-01-02")],
[Timestamp("2020-01-01"), date(2020, 1, 2)],
(
[date(2020, 1, 1), Timestamp("2020-01-02")],
np.array([-1, 1], dtype=np.intp),
),
(
[Timestamp("2020-01-01"), Timestamp(date(2020, 1, 2))],
np.array([0, 1], dtype=np.intp),
),
],
)
def test_get_indexer_mixed_dtypes(self, target):
def test_get_indexer_mixed_dtypes(self, target, expected):
# https://github.com/pandas-dev/pandas/issues/33741
values = DatetimeIndex([Timestamp("2020-01-01"), Timestamp("2020-01-02")])
result = values.get_indexer(target)
expected = np.array([0, 1], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)

@pytest.mark.parametrize(
Expand Down
22 changes: 18 additions & 4 deletions pandas/tests/series/test_arithmetic.py
Original file line number Diff line number Diff line change
Expand Up @@ -758,6 +758,8 @@ def test_datetime_understood(self, unit):
tm.assert_series_equal(result, expected)

def test_align_date_objects_with_datetimeindex(self):
# GH#62158: v3.0.0 - DatetimeIndex no longer matches Python date labels.
# The result is always all-NaN and the union index.
rng = date_range("1/1/2000", periods=20)
ts = Series(np.random.default_rng(2).standard_normal(20), index=rng)

Expand All @@ -767,10 +769,22 @@ def test_align_date_objects_with_datetimeindex(self):

result = ts + ts2
result2 = ts2 + ts
expected = ts + ts[5:]
expected.index = expected.index._with_freq(None)
tm.assert_series_equal(result, expected)
tm.assert_series_equal(result2, expected)

date_labels = [x.date() for x in rng[5:]]
expected_index_result = Index(list(rng) + date_labels, dtype=object)
expected_index_result2 = Index(date_labels + list(rng), dtype=object)

# Length and index checks
assert len(result) == 35
tm.assert_index_equal(result.index, expected_index_result)
tm.assert_index_equal(result2.index, expected_index_result2)
assert result.index.dtype == object

# All NaN because there are no matching labels now
assert result.isna().all()
assert result2.isna().all()

tm.assert_series_equal(result, result2)


class TestNamePreservation:
Expand Down
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