BUG: date comparison fails when series is all pd.NaT values

doc/source/whatsnew/v3.0.0.rst

@@ -660,6 +660,7 @@ Datetimelike
 - Bug in :meth:`to_datetime` reports incorrect index in case of any failure scenario. (:issue:`58298`)
 - Bug in :meth:`to_datetime` wrongly converts when ``arg`` is a ``np.datetime64`` object with unit of ``ps``. (:issue:`60341`)
 - Bug in setting scalar values with mismatched resolution into arrays with non-nanosecond ``datetime64``, ``timedelta64`` or :class:`DatetimeTZDtype` incorrectly truncating those scalars (:issue:`56410`)
+- Bug in :attr:`Series.dt.date` where Series with all NaT values would raise an error when compared to a datetime.date (:issue:`61188`)
 
 Timedelta
 ^^^^^^^^^

pandas/core/indexes/accessors.py

@@ -396,6 +396,53 @@ def freq(self):
         '2YS-JAN'
         """
         return self._get_values().inferred_freq
+
+    @property
+    def date(self):
+        """
+        Return the date component (year, month, day) of each datetime in the Series.
+
+        This property returns a Series of Python datetime.date objects corresponding to
+        the date portion of each datetime64[ns] value in the Series. For missing values
+        (NaT), the result will be NaT.
+
+        Returns
+        -------
+        Series
+            A Series of datetime.date objects or NaT, with dtype object.
+
+        Notes
+        -----
+        - The result is always returned with object dtype.
+        - This ensures comparisons with Python datetime.date values (e.g. using <=)
+        work even when the Series contains only missing values (NaT).
+
+        Examples
+        --------
+        >>> s = pd.Series(pd.to_datetime(["2020-01-01", pd.NaT]))
+        >>> s.dt.date
+        0    2020-01-01
+        1           NaT
+        dtype: object
+
+        >>> s.dt.date <= datetime.date(2024, 1, 1)
+        0     True
+        1    False
+        dtype: bool
+        """
+
+        from pandas import Series
+        import datetime
+
+        values = self._get_values()
+        as_dates = values.to_pydatetime()
+
+        def extract_date(x):
+            return x.date() if isinstance(x, datetime.datetime) else pd.NaT
+
+        result = [extract_date(v) for v in as_dates]
+
+        return Series(result, index=self._parent.index, name=self._parent.name, dtype=object).__finalize__(self._parent)
 
     def isocalendar(self) -> DataFrame:
         """

pandas/tests/series/indexing/test_datetime.py

@@ -491,3 +491,21 @@ def test_compare_datetime_with_all_none():
     result = ser > ser2
     expected = Series([False, False])
     tm.assert_series_equal(result, expected)
+
+def test_dt_date_dtype_all_nat_is_object():
+    # Ensure .dt.date on all-NaT Series returns object dtype and not datetime64
+    # GH#61188
+    s = pd.Series([pd.NaT, pd.NaT])
+    s = pd.to_datetime(s)
+    result = s.dt.date
+    assert result.dtype == object
+    assert result.isna().all()
+
+def test_dt_date_all_nat_le_date():
+    #All-NaT Series should not raise error when compared to a datetime.date
+    # GH#61188
+    s = pd.Series([pd.NaT, pd.NaT])
+    s = pd.to_datetime(s)
+    result = s.dt.date <= datetime.now().date()
+    expected = pd.Series([False, False])
+    tm.assert_series_equal(result, expected)