REF: re-use maybe_cast_result in Series.combine

pandas/core/dtypes/cast.py

@@ -102,7 +102,6 @@
 if TYPE_CHECKING:
     from typing import Literal
 
-    from pandas import Series
     from pandas.core.arrays import (
         DatetimeArray,
         ExtensionArray,
@@ -375,7 +374,11 @@ def trans(x):
 
 
 def maybe_cast_result(
-    result: ArrayLike, obj: Series, numeric_only: bool = False, how: str = ""
+    result: ArrayLike,
+    dtype: DtypeObj,
+    numeric_only: bool = False,
+    how: str = "",
+    same_dtype: bool = True,
 ) -> ArrayLike:
     """
     Try casting result to a different type if appropriate
@@ -384,19 +387,20 @@ def maybe_cast_result(
     ----------
     result : array-like
         Result to cast.
-    obj : Series
+    dtype : np.dtype or ExtensionDtype
         Input Series from which result was calculated.
     numeric_only : bool, default False
         Whether to cast only numerics or datetimes as well.
     how : str, default ""
         How the result was computed.
+    same_dtype : bool, default True
+        Specify dtype when calling _from_sequence
 
     Returns
     -------
     result : array-like
         result maybe casted to the dtype.
     """
-    dtype = obj.dtype
     dtype = maybe_cast_result_dtype(dtype, how)
 
     assert not is_scalar(result)
@@ -407,7 +411,10 @@ def maybe_cast_result(
             # things like counts back to categorical
 
             cls = dtype.construct_array_type()
-            result = maybe_cast_to_extension_array(cls, result, dtype=dtype)
+            if same_dtype:
+                result = maybe_cast_to_extension_array(cls, result, dtype=dtype)
+            else:
+                result = maybe_cast_to_extension_array(cls, result)
 
     elif (numeric_only and is_numeric_dtype(dtype)) or not numeric_only:
         result = maybe_downcast_to_dtype(result, dtype)

pandas/core/groupby/ops.py

@@ -788,7 +788,7 @@ def _aggregate_series_pure_python(self, obj: Series, func: F):
             result[label] = res
 
         out = lib.maybe_convert_objects(result, try_float=False)
-        out = maybe_cast_result(out, obj, numeric_only=True)
+        out = maybe_cast_result(out, obj.dtype, numeric_only=True)
 
         return out, counts
 

pandas/core/series.py

@@ -60,15 +60,13 @@
 from pandas.core.dtypes.cast import (
     convert_dtypes,
     maybe_box_native,
-    maybe_cast_to_extension_array,
+    maybe_cast_result,
     validate_numeric_casting,
 )
 from pandas.core.dtypes.common import (
     ensure_platform_int,
     is_bool,
-    is_categorical_dtype,
     is_dict_like,
-    is_extension_array_dtype,
     is_integer,
     is_iterator,
     is_list_like,
@@ -3079,22 +3077,9 @@ def combine(self, other, func, fill_value=None) -> Series:
                 new_values = [func(lv, other) for lv in self._values]
             new_name = self.name
 
-        if is_categorical_dtype(self.dtype):
-            pass
-        elif is_extension_array_dtype(self.dtype):
-            # TODO: can we do this for only SparseDtype?
-            # The function can return something of any type, so check
-            # if the type is compatible with the calling EA.
-
-            # error: Incompatible types in assignment (expression has type
-            # "Union[ExtensionArray, ndarray]", variable has type "List[Any]")
-            new_values = maybe_cast_to_extension_array(  # type: ignore[assignment]
-                # error: Argument 2 to "maybe_cast_to_extension_array" has incompatible
-                # type "List[Any]"; expected "Union[ExtensionArray, ndarray]"
-                type(self._values),
-                new_values,  # type: ignore[arg-type]
-            )
-        return self._constructor(new_values, index=new_index, name=new_name)
+        res_values = sanitize_array(new_values, None)
+        res_values = maybe_cast_result(res_values, self.dtype, same_dtype=False)
+        return self._constructor(res_values, index=new_index, name=new_name)
 
     def combine_first(self, other) -> Series:
         """

pandas/tests/extension/decimal/test_decimal.py

@@ -362,13 +362,18 @@ def _create_arithmetic_method(cls, op):
 DecimalArrayWithoutCoercion._add_arithmetic_ops()
 
 
-def test_combine_from_sequence_raises():
+def test_combine_from_sequence_raises(monkeypatch):
     # https://github.com/pandas-dev/pandas/issues/22850
-    ser = pd.Series(
-        DecimalArrayWithoutFromSequence(
-            [decimal.Decimal("1.0"), decimal.Decimal("2.0")]
-        )
-    )
+    cls = DecimalArrayWithoutFromSequence
+
+    @classmethod
+    def construct_array_type(cls):
+        return DecimalArrayWithoutFromSequence
+
+    monkeypatch.setattr(DecimalDtype, "construct_array_type", construct_array_type)
+
+    arr = cls([decimal.Decimal("1.0"), decimal.Decimal("2.0")])
+    ser = pd.Series(arr)
     result = ser.combine(ser, operator.add)
 
     # note: object dtype