REF: move _wrap_joined_index up to NDarrayBackedExtensionIndex

pandas/core/indexes/category.py

@@ -29,7 +29,6 @@
 from pandas.core.indexes.base import Index, _index_shared_docs, maybe_extract_name
 from pandas.core.indexes.extension import NDArrayBackedExtensionIndex, inherit_names
 import pandas.core.missing as missing
-from pandas.core.ops import get_op_result_name
 
 _index_doc_kwargs = dict(ibase._index_doc_kwargs)
 _index_doc_kwargs.update(dict(target_klass="CategoricalIndex"))
@@ -669,10 +668,3 @@ def _delegate_method(self, name: str, *args, **kwargs):
         if is_scalar(res):
             return res
         return CategoricalIndex(res, name=self.name)
-
-    def _wrap_joined_index(
-        self, joined: np.ndarray, other: "CategoricalIndex"
-    ) -> "CategoricalIndex":
-        name = get_op_result_name(self, other)
-        cat = self._data._from_backing_data(joined)
-        return type(self)._simple_new(cat, name=name)

pandas/core/indexes/datetimelike.py

@@ -38,7 +38,6 @@
     make_wrapped_arith_op,
 )
 from pandas.core.indexes.numeric import Int64Index
-from pandas.core.ops import get_op_result_name
 from pandas.core.tools.timedeltas import to_timedelta
 
 if TYPE_CHECKING:
@@ -629,20 +628,23 @@ def insert(self, loc: int, item):
     def _can_union_without_object_cast(self, other) -> bool:
         return is_dtype_equal(self.dtype, other.dtype)
 
-    def _wrap_joined_index(self, joined: np.ndarray, other):
-        assert other.dtype == self.dtype, (other.dtype, self.dtype)
-        name = get_op_result_name(self, other)
-
+    def _get_join_freq(self, other):
+        """
+        Get the freq to attach to the result of a join operation.
+        """
         if is_period_dtype(self.dtype):
             freq = self.freq
         else:
             self = cast(DatetimeTimedeltaMixin, self)
             freq = self.freq if self._can_fast_union(other) else None
+        return freq
 
-        new_data = self._data._from_backing_data(joined)
-        new_data._freq = freq
+    def _wrap_joined_index(self, joined: np.ndarray, other):
+        assert other.dtype == self.dtype, (other.dtype, self.dtype)
 
-        return type(self)._simple_new(new_data, name=name)
+        result = super()._wrap_joined_index(joined, other)
+        result._data._freq = self._get_join_freq(other)
+        return result
 
     @doc(Index._convert_arr_indexer)
     def _convert_arr_indexer(self, keyarr):

pandas/core/indexes/extension.py

@@ -1,7 +1,7 @@
 """
 Shared methods for Index subclasses backed by ExtensionArray.
 """
-from typing import List
+from typing import List, TypeVar
 
 import numpy as np
 
@@ -18,6 +18,8 @@
 from pandas.core.indexes.base import Index
 from pandas.core.ops import get_op_result_name
 
+_T = TypeVar("_T", bound="NDArrayBackedExtensionIndex")
+
 
 def inherit_from_data(name: str, delegate, cache: bool = False, wrap: bool = False):
     """
@@ -338,3 +340,8 @@ def putmask(self, mask, value):
         np.putmask(new_values, mask, value)
         new_arr = self._data._from_backing_data(new_values)
         return type(self)._simple_new(new_arr, name=self.name)
+
+    def _wrap_joined_index(self: _T, joined: np.ndarray, other: _T) -> _T:
+        name = get_op_result_name(self, other)
+        arr = self._data._from_backing_data(joined)
+        return type(self)._simple_new(arr, name=name)