CLN: dont special-case DatetimeArray indexing

doc/source/whatsnew/v1.2.0.rst

@@ -393,6 +393,7 @@ Indexing
 - Bug in :meth:`Index.get_indexer` and :meth:`Index.get_indexer_non_unique` where int64 arrays are returned instead of intp. (:issue:`36359`)
 - Bug in :meth:`DataFrame.sort_index` where parameter ascending passed as a list on a single level index gives wrong result. (:issue:`32334`)
 - Bug in :meth:`DataFrame.reset_index` was incorrectly raising a ``ValueError`` for input with a :class:`MultiIndex` with missing values in a level with ``Categorical`` dtype (:issue:`24206`)
+- Bug in indexing with boolean masks on datetime-like values sometimes returning a view instead of a copy (:issue:`36210`)
 
 Missing
 ^^^^^^^

pandas/core/arrays/datetimelike.py

@@ -65,7 +65,7 @@
 from pandas.core.arrays._mixins import NDArrayBackedExtensionArray
 import pandas.core.common as com
 from pandas.core.construction import array, extract_array
-from pandas.core.indexers import check_array_indexer, check_setitem_lengths
+from pandas.core.indexers import check_setitem_lengths
 from pandas.core.ops.common import unpack_zerodim_and_defer
 from pandas.core.ops.invalid import invalid_comparison, make_invalid_op
 
@@ -284,23 +284,6 @@ def __getitem__(self, key):
         result._freq = self._get_getitem_freq(key)
         return result
 
-    def _validate_getitem_key(self, key):
-        if com.is_bool_indexer(key):
-            # first convert to boolean, because check_array_indexer doesn't
-            # allow object dtype
-            if is_object_dtype(key):
-                key = np.asarray(key, dtype=bool)
-
-            key = check_array_indexer(self, key)
-            key = lib.maybe_booleans_to_slice(key.view(np.uint8))
-        elif isinstance(key, list) and len(key) == 1 and isinstance(key[0], slice):
-            # see https://github.com/pandas-dev/pandas/issues/31299, need to allow
-            # this for now (would otherwise raise in check_array_indexer)
-            pass
-        else:
-            key = super()._validate_getitem_key(key)
-        return key
-
     def _get_getitem_freq(self, key):
         """
         Find the `freq` attribute to assign to the result of a __getitem__ lookup.
@@ -322,6 +305,10 @@ def _get_getitem_freq(self, key):
                 # GH#21282 indexing with Ellipsis is similar to a full slice,
                 #  should preserve `freq` attribute
                 freq = self.freq
+            elif com.is_bool_indexer(key):
+                new_key = lib.maybe_booleans_to_slice(key.view(np.uint8))
+                if isinstance(new_key, slice):
+                    return self._get_getitem_freq(new_key)
         return freq
 
     def __setitem__(

pandas/core/indexes/datetimelike.py

@@ -190,12 +190,14 @@ def take(self, indices, axis=0, allow_fill=True, fill_value=None, **kwargs):
         indices = ensure_int64(indices)
 
         maybe_slice = lib.maybe_indices_to_slice(indices, len(self))
-        if isinstance(maybe_slice, slice):
-            return self[maybe_slice]
 
-        return ExtensionIndex.take(
+        result = ExtensionIndex.take(
             self, indices, axis, allow_fill, fill_value, **kwargs
         )
+        if isinstance(maybe_slice, slice):
+            freq = self._data._get_getitem_freq(maybe_slice)
+            result._data._freq = freq
+        return result
 
     @doc(IndexOpsMixin.searchsorted, klass="Datetime-like Index")
     def searchsorted(self, value, side="left", sorter=None):

pandas/tests/series/indexing/test_boolean.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from pandas import Index, Series
+from pandas import Index, Series, date_range
 import pandas._testing as tm
 from pandas.core.indexing import IndexingError
 
@@ -128,3 +128,19 @@ def test_get_set_boolean_different_order(string_series):
     sel = string_series[ordered > 0]
     exp = string_series[string_series > 0]
     tm.assert_series_equal(sel, exp)
+
+
+def test_getitem_boolean_dt64_copies():
+    # GH#36210
+    dti = date_range("2016-01-01", periods=4, tz="US/Pacific")
+    key = np.array([True, True, False, False])
+
+    ser = Series(dti._data)
+
+    res = ser[key]
+    assert res._values._data.base is None
+
+    # compare with numeric case for reference
+    ser2 = Series(range(4))
+    res2 = ser2[key]
+    assert res2._values.base is None