BUG: GH25495 incorrect dtype when using .loc to set Categorical value for column in 1-row DataFrame

pandas/core/internals/blocks.py

@@ -882,6 +882,14 @@ def setitem(self, indexer, value):
             and arr_value.size == values.size
         ):
             values[indexer] = value
+
+            if self.is_categorical_astype(arr_value.dtype) and not is_categorical_dtype(
+                values
+            ):
+                # GH25495 - If the current dtype is not categorical,
+                # we need to create a new categorical block
+                return self.make_block(Categorical(self.values, dtype=arr_value.dtype))
+
             try:
                 values = values.astype(arr_value.dtype)
             except ValueError:

pandas/tests/frame/test_indexing.py

@@ -204,6 +204,15 @@ def test_setitem_list_of_tuples(self, float_frame):
         expected = Series(tuples, index=float_frame.index, name="tuples")
         tm.assert_series_equal(result, expected)
 
+    def test_setitem_single_row_categorical(self):
+        df = DataFrame({"Alpha": ["a"], "Numeric": [0]})
+        categories = pd.Categorical(df["Alpha"], categories=["a", "b", "c"])
+        df.loc[:, "Alpha"] = categories
+
+        result = df["Alpha"]
+        expected = Series(categories, index=df.index, name="Alpha")
+        tm.assert_series_equal(result, expected)
+
     def test_setitem_mulit_index(self):
         # GH7655, test that assigning to a sub-frame of a frame
         # with multi-index columns aligns both rows and columns