DEPR: slicing with a date object

doc/source/whatsnew/v3.0.0.rst

@@ -666,6 +666,7 @@ Other Deprecations
 - Deprecated using ``epoch`` date format in :meth:`DataFrame.to_json` and :meth:`Series.to_json`, use ``iso`` instead. (:issue:`57063`)
 - Deprecated allowing ``fill_value`` that cannot be held in the original dtype (excepting NA values for integer and bool dtypes) in :meth:`Series.unstack` and :meth:`DataFrame.unstack` (:issue:`12189`, :issue:`53868`)
 - Deprecated allowing ``fill_value`` that cannot be held in the original dtype (excepting NA values for integer and bool dtypes) in :meth:`Series.shift` and :meth:`DataFrame.shift` (:issue:`53802`)
+- Deprecated slicing on a :class:`Series` or :class:`DataFrame` with a :class:`DatetimeIndex` using a ``datetime.date`` object, explicitly cast to :class:`Timestamp` instead (:issue:`35830`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_300.prior_deprecations:

pandas/core/indexes/datetimes.py

@@ -26,11 +26,13 @@
     to_offset,
 )
 from pandas._libs.tslibs.offsets import prefix_mapping
+from pandas.errors import Pandas4Warning
 from pandas.util._decorators import (
     cache_readonly,
     doc,
     set_module,
 )
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_scalar
 from pandas.core.dtypes.dtypes import (
@@ -645,6 +647,13 @@ def _maybe_cast_slice_bound(self, label, side: str):
             # Pandas supports slicing with dates, treated as datetimes at midnight.
             # https://github.com/pandas-dev/pandas/issues/31501
             label = Timestamp(label).to_pydatetime()
+            warnings.warn(
+                # GH#35830 deprecate last remaining inconsistent date treatment
+                "Slicing with a datetime.date object is deprecated. "
+                "Explicitly cast to Timestamp instead.",
+                Pandas4Warning,
+                stacklevel=find_stack_level(),
+            )
 
         label = super()._maybe_cast_slice_bound(label, side)
         self._data._assert_tzawareness_compat(label)

pandas/tests/indexes/datetimes/test_indexing.py

@@ -10,6 +10,7 @@
 
 from pandas._libs import index as libindex
 from pandas.compat.numpy import np_long
+from pandas.errors import Pandas4Warning
 import pandas.util._test_decorators as td
 
 import pandas as pd
@@ -654,13 +655,16 @@ def test_get_slice_bounds_datetime_within(
         index = bdate_range("2000-01-03", "2000-02-11").tz_localize(tz)
         key = box(year=2000, month=1, day=7)
 
-        if tz is not None:
-            with pytest.raises(TypeError, match="Cannot compare tz-naive"):
-                # GH#36148 we require tzawareness-compat as of 2.0
-                index.get_slice_bound(key, side=side)
-        else:
-            result = index.get_slice_bound(key, side=side)
-            assert result == expected
+        warn = None if box is not date else Pandas4Warning
+        msg = "Slicing with a datetime.date object is deprecated"
+        with tm.assert_produces_warning(warn, match=msg):
+            if tz is not None:
+                with pytest.raises(TypeError, match="Cannot compare tz-naive"):
+                    # GH#36148 we require tzawareness-compat as of 2.0
+                    index.get_slice_bound(key, side=side)
+            else:
+                result = index.get_slice_bound(key, side=side)
+                assert result == expected
 
     @pytest.mark.parametrize("box", [datetime, Timestamp])
     @pytest.mark.parametrize("side", ["left", "right"])

pandas/tests/series/indexing/test_getitem.py

@@ -16,6 +16,7 @@
     timezones,
 )
 from pandas.compat.numpy import np_version_gt2
+from pandas.errors import Pandas4Warning
 
 from pandas.core.dtypes.common import is_scalar
 
@@ -314,7 +315,9 @@ def test_getitem_slice_date(self, slc, positions):
             [0, 1, 2],
             DatetimeIndex(["2019-01-01", "2019-01-01T06:00:00", "2019-01-02"]),
         )
-        result = ser[slc]
+        msg = "Slicing with a datetime.date object is deprecated"
+        with tm.assert_produces_warning(Pandas4Warning, match=msg):
+            result = ser[slc]
         expected = ser.take(positions)
         tm.assert_series_equal(result, expected)