BUG: freq invalidation in DatetimeIndex.where (#62850)

Author: jbrockmendel

doc/source/whatsnew/v3.0.0.rst

@@ -980,6 +980,7 @@ Datetimelike
 - Bug in :meth:`DatetimeIndex.is_year_start` and :meth:`DatetimeIndex.is_quarter_start` does not raise on Custom business days frequencies bigger then "1C" (:issue:`58664`)
 - Bug in :meth:`DatetimeIndex.is_year_start` and :meth:`DatetimeIndex.is_quarter_start` returning ``False`` on double-digit frequencies (:issue:`58523`)
 - Bug in :meth:`DatetimeIndex.union` and :meth:`DatetimeIndex.intersection` when ``unit`` was non-nanosecond (:issue:`59036`)
+- Bug in :meth:`DatetimeIndex.where` and :meth:`TimedeltaIndex.where` failing to set ``freq=None`` in some cases (:issue:`24555`)
 - Bug in :meth:`Index.union` with a ``pyarrow`` timestamp dtype incorrectly returning ``object`` dtype (:issue:`58421`)
 - Bug in :meth:`Series.dt.microsecond` producing incorrect results for pyarrow backed :class:`Series`. (:issue:`59154`)
 - Bug in :meth:`Timestamp.normalize` and :meth:`DatetimeArray.normalize` returning incorrect results instead of raising on integer overflow for very small (distant past) values (:issue:`60583`)
@@ -996,7 +997,6 @@ Datetimelike
 - 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`)
 
-
 Timedelta
 ^^^^^^^^^
 - Accuracy improvement in :meth:`Timedelta.to_pytimedelta` to round microseconds consistently for large nanosecond based Timedelta (:issue:`57841`)

pandas/core/arrays/datetimelike.py

@@ -393,7 +393,9 @@ def __getitem__(self, key: PositionalIndexer2D) -> Self | DTScalarOrNaT:
         else:
             # At this point we know the result is an array.
             result = cast(Self, result)
-        result._freq = self._get_getitem_freq(key)
+        # error: Incompatible types in assignment (expression has type
+        # "BaseOffset | None", variable has type "None")
+        result._freq = self._get_getitem_freq(key)  # type: ignore[assignment]
         return result
 
     def _get_getitem_freq(self, key) -> BaseOffset | None:
@@ -527,6 +529,10 @@ def view(self, dtype: Dtype | None = None) -> ArrayLike:
         #  are present in this file.
         return super().view(dtype)
 
+    def _putmask(self, mask: npt.NDArray[np.bool_], value) -> None:
+        super()._putmask(mask, value)
+        self._freq = None  # GH#24555
+
     # ------------------------------------------------------------------
     # Validation Methods
     # TODO: try to de-duplicate these, ensure identical behavior
@@ -2042,7 +2048,7 @@ def _maybe_pin_freq(self, freq, validate_kwds: dict) -> None:
             if self._freq is None:
                 # Set _freq directly to bypass duplicative _validate_frequency
                 # check.
-                self._freq = to_offset(self.inferred_freq)
+                self._freq = to_offset(self.inferred_freq)  # type: ignore[assignment]
         elif freq is lib.no_default:
             # user did not specify anything, keep inferred freq if the original
             #  data had one, otherwise do nothing
@@ -2442,7 +2448,7 @@ def take(
 
         if isinstance(maybe_slice, slice):
             freq = self._get_getitem_freq(maybe_slice)
-            result._freq = freq
+            result._freq = freq  # type: ignore[assignment]
 
         return result
 

pandas/tests/indexes/datetimes/test_indexing.py

@@ -119,6 +119,17 @@ def test_getitem_int_list(self):
 
 
 class TestWhere:
+    @pytest.mark.parametrize("is_td", [True, False])
+    def test_where_freq_invalidation(self, is_td):
+        # GH#24555
+        index = date_range("20130101", periods=3, tz="US/Eastern")
+        if is_td:
+            index = index - index[0]
+        other = Index([pd.NaT, pd.NaT] + index[2:].tolist())
+
+        result = index.where(notna(other), other)
+        assert result.freq is None
+
     def test_where_doesnt_retain_freq(self):
         dti = date_range("20130101", periods=3, freq="D", name="idx")
         cond = [True, True, False]