REF: implement putmask for CI/DTI/TDI/PI

pandas/core/arrays/categorical.py

@@ -1171,6 +1171,11 @@ def map(self, mapper):
     # -------------------------------------------------------------
     # Validators; ideally these can be de-duplicated
 
+    def _validate_where_value(self, value):
+        if is_scalar(value):
+            return self._validate_fill_value(value)
+        return self._validate_listlike(value)
+
     def _validate_insert_value(self, value) -> int:
         code = self.categories.get_indexer([value])
         if (code == -1) and not (is_scalar(value) and isna(value)):

pandas/core/indexes/base.py

@@ -4232,9 +4232,6 @@ def putmask(self, mask, value):
         try:
             converted = self._validate_fill_value(value)
             np.putmask(values, mask, converted)
-            if is_period_dtype(self.dtype):
-                # .values cast to object, so we need to cast back
-                values = type(self)(values)._data
             return self._shallow_copy(values)
         except (ValueError, TypeError) as err:
             if is_object_dtype(self):

pandas/core/indexes/category.py

@@ -422,6 +422,17 @@ def where(self, cond, other=None):
         cat = Categorical(values, dtype=self.dtype)
         return type(self)._simple_new(cat, name=self.name)
 
+    def putmask(self, mask, value):
+        try:
+            code_value = self._data._validate_where_value(value)
+        except (TypeError, ValueError):
+            return self.astype(object).putmask(mask, value)
+
+        codes = self._data._ndarray.copy()
+        np.putmask(codes, mask, code_value)
+        cat = self._data._from_backing_data(codes)
+        return type(self)._simple_new(cat, name=self.name)
+
     def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
         """
         Create index with target's values (move/add/delete values as necessary)

pandas/core/indexes/datetimelike.py

@@ -484,7 +484,18 @@ def where(self, cond, other=None):
             raise TypeError(f"Where requires matching dtype, not {oth}") from err
 
         result = np.where(cond, values, other).astype("i8")
-        arr = type(self._data)._simple_new(result, dtype=self.dtype)
+        arr = self._data._from_backing_data(result)
+        return type(self)._simple_new(arr, name=self.name)
+
+    def putmask(self, mask, value):
+        try:
+            value = self._data._validate_where_value(value)
+        except (TypeError, ValueError):
+            return self.astype(object).putmask(mask, value)
+
+        result = self._data._ndarray.copy()
+        np.putmask(result, mask, value)
+        arr = self._data._from_backing_data(result)
         return type(self)._simple_new(arr, name=self.name)
 
     def _summary(self, name=None) -> str:

pandas/tests/indexes/common.py

@@ -846,16 +846,17 @@ def test_map_str(self):
     def test_putmask_with_wrong_mask(self):
         # GH18368
         index = self.create_index()
+        fill = index[0]
 
         msg = "putmask: mask and data must be the same size"
         with pytest.raises(ValueError, match=msg):
-            index.putmask(np.ones(len(index) + 1, np.bool_), 1)
+            index.putmask(np.ones(len(index) + 1, np.bool_), fill)
 
         with pytest.raises(ValueError, match=msg):
-            index.putmask(np.ones(len(index) - 1, np.bool_), 1)
+            index.putmask(np.ones(len(index) - 1, np.bool_), fill)
 
         with pytest.raises(ValueError, match=msg):
-            index.putmask("foo", 1)
+            index.putmask("foo", fill)
 
     @pytest.mark.parametrize("copy", [True, False])
     @pytest.mark.parametrize("name", [None, "foo"])