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

doc/source/whatsnew/v1.0.0.rst

@@ -367,7 +367,7 @@ Indexing
 - Bug in :meth:`Float64Index.astype` where ``np.inf`` was not handled properly when casting to an integer dtype (:issue:`28475`)
 - :meth:`Index.union` could fail when the left contained duplicates (:issue:`28257`)
 - :meth:`Index.get_indexer_non_unique` could fail with `TypeError` in some cases, such as when searching for ints in a string index (:issue:`28257`)
--
+- Bug in :meth:`DataFrame.loc` with incorrect dtype when setting Categorical value in 1-row DataFrame (:issue:`25495`)
 
 Missing
 ^^^^^^^

pandas/core/internals/blocks.py

@@ -860,7 +860,11 @@ def setitem(self, indexer, value):
 
         # length checking
         check_setitem_lengths(indexer, value, values)
-
+        exact_match = (
+            len(arr_value.shape)
+            and arr_value.shape[0] == values.shape[0]
+            and arr_value.size == values.size
+        )
         if is_empty_indexer(indexer, arr_value):
             # GH#8669 empty indexers
             pass
@@ -870,14 +874,21 @@ def setitem(self, indexer, value):
             #  be e.g. a list; see GH#6043
             values[indexer] = value
 
-        # if we are an exact match (ex-broadcasting),
-        # then use the resultant dtype
         elif (
-            len(arr_value.shape)
-            and arr_value.shape[0] == values.shape[0]
-            and arr_value.size == values.size
+            self.is_categorical_astype(arr_value.dtype)
+            and not is_categorical_dtype(values)
+            and exact_match
         ):
+            # GH25495 - If the current dtype is not categorical,
+            # we need to create a new categorical block
             values[indexer] = value
+            return self.make_block(Categorical(self.values, dtype=arr_value.dtype))
+
+        # if we are an exact match (ex-broadcasting),
+        # then use the resultant dtype
+        elif exact_match:
+            values[indexer] = value
+
             try:
                 values = values.astype(arr_value.dtype)
             except ValueError:

pandas/tests/frame/test_indexing.py

@@ -3849,6 +3849,16 @@ def test_assigning_ops(self):
         df.loc[2:3, "b"] = Categorical(["b", "b"], categories=["a", "b"])
         tm.assert_frame_equal(df, exp)
 
+    def test_setitem_single_row_categorical(self):
+        # GH 25495
+        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_functions_no_warnings(self):
         df = DataFrame({"value": np.random.randint(0, 100, 20)})
         labels = ["{0} - {1}".format(i, i + 9) for i in range(0, 100, 10)]