REF: share ExtensionIndex.insert-> Index.insert

pandas/core/dtypes/missing.py

@@ -37,6 +37,7 @@
     needs_i8_conversion,
 )
 from pandas.core.dtypes.dtypes import (
+    CategoricalDtype,
     ExtensionDtype,
     IntervalDtype,
     PeriodDtype,
@@ -641,5 +642,8 @@ def is_valid_na_for_dtype(obj, dtype: DtypeObj) -> bool:
     elif isinstance(dtype, IntervalDtype):
         return lib.is_float(obj) or obj is None or obj is libmissing.NA
 
+    elif isinstance(dtype, CategoricalDtype):
+        return is_valid_na_for_dtype(obj, dtype.categories.dtype)
+
     # fallback, default to allowing NaN, None, NA, NaT
     return not isinstance(obj, (np.datetime64, np.timedelta64, Decimal))

pandas/core/indexes/base.py

@@ -6432,14 +6432,21 @@ def insert(self, loc: int, item) -> Index:
         if is_valid_na_for_dtype(item, self.dtype) and self.dtype != object:
             item = self._na_value
 
+        arr = self._values
+
         try:
-            item = self._validate_fill_value(item)
-        except TypeError:
+            if isinstance(arr, ExtensionArray):
+                res_values = arr.insert(loc, item)
+                return type(self)._simple_new(res_values, name=self.name)
+            else:
+                item = self._validate_fill_value(item)
+        except (TypeError, ValueError):
+            # e.g. trying to insert an integer into a DatetimeIndex
+            #  We cannot keep the same dtype, so cast to the (often object)
+            #  minimal shared dtype before doing the insert.
             dtype = self._find_common_type_compat(item)
             return self.astype(dtype).insert(loc, item)
 
-        arr = self._values
-
         if arr.dtype != object or not isinstance(
             item, (tuple, np.datetime64, np.timedelta64)
         ):

pandas/core/indexes/extension.py

@@ -134,31 +134,6 @@ class ExtensionIndex(Index):
 
     # ---------------------------------------------------------------------
 
-    def insert(self, loc: int, item) -> Index:
-        """
-        Make new Index inserting new item at location. Follows
-        Python list.append semantics for negative values.
-
-        Parameters
-        ----------
-        loc : int
-        item : object
-
-        Returns
-        -------
-        new_index : Index
-        """
-        try:
-            result = self._data.insert(loc, item)
-        except (ValueError, TypeError):
-            # e.g. trying to insert an integer into a DatetimeIndex
-            #  We cannot keep the same dtype, so cast to the (often object)
-            #  minimal shared dtype before doing the insert.
-            dtype = self._find_common_type_compat(item)
-            return self.astype(dtype).insert(loc, item)
-        else:
-            return type(self)._simple_new(result, name=self.name)
-
     def _validate_fill_value(self, value):
         """
         Convert value to be insertable to underlying array.

pandas/tests/dtypes/test_missing.py

@@ -18,6 +18,7 @@
     is_scalar,
 )
 from pandas.core.dtypes.dtypes import (
+    CategoricalDtype,
     DatetimeTZDtype,
     IntervalDtype,
     PeriodDtype,
@@ -739,3 +740,11 @@ def test_is_valid_na_for_dtype_interval(self):
 
         dtype = IntervalDtype("datetime64[ns]", "both")
         assert not is_valid_na_for_dtype(NaT, dtype)
+
+    def test_is_valid_na_for_dtype_categorical(self):
+        dtype = CategoricalDtype(categories=[0, 1, 2])
+        assert is_valid_na_for_dtype(np.nan, dtype)
+
+        assert not is_valid_na_for_dtype(NaT, dtype)
+        assert not is_valid_na_for_dtype(np.datetime64("NaT", "ns"), dtype)
+        assert not is_valid_na_for_dtype(np.timedelta64("NaT", "ns"), dtype)