diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 39fcfcbe2bff6..05cc996178051 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -377,23 +377,13 @@ def _prep_values(self, values: Optional[np.ndarray] = None) -> np.ndarray:
 
         return values
 
-    def _wrap_result(self, result, block=None, obj=None):
+    def _wrap_result(self, result: np.ndarray) -> "Series":
         """
-        Wrap a single result.
+        Wrap a single 1D result.
         """
-        if obj is None:
-            obj = self._selected_obj
-        index = obj.index
+        obj = self._selected_obj
 
-        if isinstance(result, np.ndarray):
-
-            if result.ndim == 1:
-                from pandas import Series
-
-                return Series(result, index, name=obj.name)
-
-            return type(obj)(result, index=index, columns=block.columns)
-        return result
+        return obj._constructor(result, obj.index, name=obj.name)
 
     def _wrap_results(self, results, obj, skipped: List[int]) -> FrameOrSeriesUnion:
         """
@@ -454,7 +444,7 @@ def _insert_on_column(self, result: "DataFrame", obj: "DataFrame"):
                 # insert at the end
                 result[name] = extra_col
 
-    def _center_window(self, result, window) -> np.ndarray:
+    def _center_window(self, result: np.ndarray, window) -> np.ndarray:
         """
         Center the result in the window.
         """
@@ -513,7 +503,6 @@ def _apply_series(self, homogeneous_func: Callable[..., ArrayLike]) -> "Series":
         Series version of _apply_blockwise
         """
         _, obj = self._create_blocks(self._selected_obj)
-        values = obj.values
 
         try:
             values = self._prep_values(obj.values)
@@ -535,7 +524,7 @@ def _apply_blockwise(
 
         # This isn't quite blockwise, since `blocks` is actually a collection
         #  of homogenenous DataFrames.
-        blocks, obj = self._create_blocks(self._selected_obj)
+        _, obj = self._create_blocks(self._selected_obj)
         mgr = obj._mgr
 
         def hfunc(bvalues: ArrayLike) -> ArrayLike: