diff --git a/pandas/core/base.py b/pandas/core/base.py
index d4a808f4d7dd1..3710a644c7826 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -77,6 +77,7 @@
     )
 
     from pandas import (
+        DataFrame,
         Index,
         Series,
     )
@@ -254,6 +255,21 @@ def _gotitem(self, key, ndim: int, subset=None):
         """
         raise AbstractMethodError(self)
 
+    @final
+    def _infer_selection(self, key, subset: Series | DataFrame):
+        """
+        Infer the `selection` to pass to our constructor in _gotitem.
+        """
+        # Shared by Rolling and Resample
+        selection = None
+        if subset.ndim == 2 and (
+            (lib.is_scalar(key) and key in subset) or lib.is_list_like(key)
+        ):
+            selection = key
+        elif subset.ndim == 1 and lib.is_scalar(key) and key == subset.name:
+            selection = key
+        return selection
+
     def aggregate(self, func, *args, **kwargs):
         raise AbstractMethodError(self)
 
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 8d3ff10ba91b3..9566a2f113b36 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -42,7 +42,10 @@
 
 import pandas.core.algorithms as algos
 from pandas.core.apply import ResamplerWindowApply
-from pandas.core.base import PandasObject
+from pandas.core.base import (
+    PandasObject,
+    SelectionMixin,
+)
 import pandas.core.common as com
 from pandas.core.generic import (
     NDFrame,
@@ -1293,7 +1296,7 @@ def quantile(self, q: float | AnyArrayLike = 0.5, **kwargs):
         return self._downsample("quantile", q=q, **kwargs)
 
 
-class _GroupByMixin(PandasObject):
+class _GroupByMixin(PandasObject, SelectionMixin):
     """
     Provide the groupby facilities.
     """
@@ -1385,13 +1388,7 @@ def _gotitem(self, key, ndim, subset=None):
         except IndexError:
             groupby = self._groupby
 
-        selection = None
-        if subset.ndim == 2 and (
-            (lib.is_scalar(key) and key in subset) or lib.is_list_like(key)
-        ):
-            selection = key
-        elif subset.ndim == 1 and lib.is_scalar(key) and key == subset.name:
-            selection = key
+        selection = self._infer_selection(key, subset)
 
         new_rs = type(self)(
             groupby=groupby,
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index a08ffcc9f7200..f4d733423b3ae 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -37,9 +37,7 @@
     ensure_float64,
     is_bool,
     is_integer,
-    is_list_like,
     is_numeric_dtype,
-    is_scalar,
     needs_i8_conversion,
 )
 from pandas.core.dtypes.generic import (
@@ -302,14 +300,7 @@ def _gotitem(self, key, ndim, subset=None):
         # with the same groupby
         kwargs = {attr: getattr(self, attr) for attr in self._attributes}
 
-        selection = None
-        if subset.ndim == 2 and (
-            (is_scalar(key) and key in subset) or is_list_like(key)
-        ):
-            selection = key
-        elif subset.ndim == 1 and is_scalar(key) and key == subset.name:
-            selection = key
-
+        selection = self._infer_selection(key, subset)
         new_win = type(self)(subset, selection=selection, **kwargs)
         return new_win