Merge branch 'master' of https://github.com/pandas-dev/pandas into cl…

…n-is_dtype_equal
pandas-dev · jreback · Nov 2, 2020 · Oct 31, 2020 · Oct 31, 2020 · Oct 31, 2020
commit 10cf22c13fa553607f98662047430254b8b38b61
diff --git a/doc/source/whatsnew/v1.2.0.rst b/doc/source/whatsnew/v1.2.0.rst
@@ -338,6 +338,7 @@ Deprecations
 - Deprecated slice-indexing on timezone-aware :class:`DatetimeIndex` with naive ``datetime`` objects, to match scalar indexing behavior (:issue:`36148`)
 - :meth:`Index.ravel` returning a ``np.ndarray`` is deprecated, in the future this will return a view on the same index (:issue:`19956`)
 - Deprecate use of strings denoting units with 'M', 'Y' or 'y' in :func:`~pandas.to_timedelta` (:issue:`36666`)
+- :class:`Index` methods ``&``, ``|``, and ``^`` behaving as the set operations :meth:`Index.intersection`, :meth:`Index.union`, and :meth:`Index.symmetric_difference`, respectively, are deprecated and in the future will behave as pointwise boolean operations matching :class:`Series` behavior.  Use the named set methods instead (:issue:`36758`)
 - :meth:`Categorical.is_dtype_equal` and :meth:`CategoricalIndex.is_dtype_equal` are deprecated, use :meth:`Categorical.categories_match_up_to_permutation` instead (:issue:`37545`)
 
 .. ---------------------------------------------------------------------------

diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
@@ -1706,17 +1706,9 @@ def _validate_listlike(self, target: ArrayLike) -> np.ndarray:
             # Indexing on codes is more efficient if categories are the same,
             #  so we can apply some optimizations based on the degree of
             #  dtype-matching.
-            if self.categories.equals(target.categories):
-                # We use the same codes, so can go directly to the engine
-                codes = target.codes
-            elif self.categories_match_up_to_permutation(target):
-                # We have the same categories up to a reshuffling of codes.
-                codes = recode_for_categories(
-                    target.codes, target.categories, self.categories
-                )
-            else:
-                code_indexer = self.categories.get_indexer(target.categories)
-                codes = take_1d(code_indexer, target.codes, fill_value=-1)
+            codes = recode_for_categories(
+                target.codes, target.categories, self.categories, copy=False
+            )
         else:
             codes = self.categories.get_indexer(target)