FIX: REGR: setting numeric value in Categorical Series with enlargement raise internal error

doc/source/whatsnew/v1.5.0.rst

@@ -908,7 +908,7 @@ Indexing
 - Bug in :meth:`NDFrame.xs`, :meth:`DataFrame.iterrows`, :meth:`DataFrame.loc` and :meth:`DataFrame.iloc` not always propagating metadata (:issue:`28283`)
 - Bug in :meth:`DataFrame.sum` min_count changes dtype if input contains NaNs (:issue:`46947`)
 - Bug in :class:`IntervalTree` that lead to an infinite recursion. (:issue:`46658`)
--
+- Bug in :meth:`DataFrame.loc` when creating a new element on a :class:`Series` with dtype :class:`CategoricalDtype` (:issue:`47677`)
 
 Missing
 ^^^^^^^

pandas/core/dtypes/cast.py

@@ -646,6 +646,9 @@ def _maybe_promote(dtype: np.dtype, fill_value=np.nan):
 
         return np.dtype("object"), fill_value
 
+    elif isinstance(dtype, CategoricalDtype):
+        return object, ensure_object(fill_value)
+
     elif is_float(fill_value):
         if issubclass(dtype.type, np.bool_):
             dtype = np.dtype(np.object_)

pandas/core/indexing.py

@@ -1777,6 +1777,7 @@ def _setitem_with_indexer(self, indexer, value, name="iloc"):
             indexer, missing = convert_missing_indexer(indexer)
 
             if missing:
+                # import pdb; pdb.set_trace()
                 self._setitem_with_indexer_missing(indexer, value)
                 return
 
@@ -2111,6 +2112,7 @@ def _setitem_with_indexer_missing(self, indexer, value):
                 # We should not cast, if we have object dtype because we can
                 # set timedeltas into object series
                 curr_dtype = self.obj.dtype
+                # import pdb; pdb.set_trace()
                 curr_dtype = getattr(curr_dtype, "numpy_dtype", curr_dtype)
                 new_dtype = maybe_promote(curr_dtype, value)[0]
             else:

pandas/tests/indexing/test_indexing.py

@@ -1019,3 +1019,10 @@ def test_ser_list_indexer_exceeds_dimensions(indexer_li):
     res = indexer_li(ser)[[0, 0]]
     exp = Series([10, 10], index=Index([0, 0]))
     tm.assert_series_equal(res, exp)
+
+
+def test_additional_element_to_categorical_series_loc():
+    result = Series(["a", "b", "c"], dtype="category")
+    result.loc[3] = 0
+    expected = Series(["a", "b", "c", 0], dtype="object")
+    tm.assert_series_equal(result, expected)