diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index f9020a192e5b7..bf0711dcc0581 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -110,10 +110,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas_object \
         pandas.api.interchange.from_dataframe \
         pandas.DatetimeIndex.snap \
-        pandas.core.window.rolling.Window.mean \
-        pandas.core.window.rolling.Window.sum \
-        pandas.core.window.rolling.Window.var \
-        pandas.core.window.rolling.Window.std \
         pandas.core.window.ewm.ExponentialMovingWindow.mean \
         pandas.core.window.ewm.ExponentialMovingWindow.sum \
         pandas.core.window.ewm.ExponentialMovingWindow.std \
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 9778651814b23..5fd9930da4463 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -1270,7 +1270,32 @@ def aggregate(self, func, *args, **kwargs):
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
-        template_see_also[:-1],
+        template_see_also,
+        create_section_header("Examples"),
+        dedent(
+            """\
+        >>> ser = pd.Series([0, 1, 5, 2, 8])
+
+        To get an instance of :class:`~pandas.core.window.rolling.Window` we need
+        to pass the parameter `win_type`.
+
+        >>> type(ser.rolling(2, win_type='gaussian'))
+        <class 'pandas.core.window.rolling.Window'>
+
+        In order to use the `SciPy` Gaussian window we need to provide the parameters
+        `M` and `std`. The parameter `M` corresponds to 2 in our example.
+        We pass the second parameter `std` as a parameter of the following method
+        (`sum` in this case):
+
+        >>> ser.rolling(2, win_type='gaussian').sum(std=3)
+        0         NaN
+        1    0.986207
+        2    5.917243
+        3    6.903450
+        4    9.862071
+        dtype: float64
+        """
+        ),
         window_method="rolling",
         aggregation_description="weighted window sum",
         agg_method="sum",
@@ -1295,7 +1320,31 @@ def sum(self, numeric_only: bool = False, **kwargs):
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
-        template_see_also[:-1],
+        template_see_also,
+        create_section_header("Examples"),
+        dedent(
+            """\
+        >>> ser = pd.Series([0, 1, 5, 2, 8])
+
+        To get an instance of :class:`~pandas.core.window.rolling.Window` we need
+        to pass the parameter `win_type`.
+
+        >>> type(ser.rolling(2, win_type='gaussian'))
+        <class 'pandas.core.window.rolling.Window'>
+
+        In order to use the `SciPy` Gaussian window we need to provide the parameters
+        `M` and `std`. The parameter `M` corresponds to 2 in our example.
+        We pass the second parameter `std` as a parameter of the following method:
+
+        >>> ser.rolling(2, win_type='gaussian').mean(std=3)
+        0    NaN
+        1    0.5
+        2    3.0
+        3    3.5
+        4    5.0
+        dtype: float64
+        """
+        ),
         window_method="rolling",
         aggregation_description="weighted window mean",
         agg_method="mean",
@@ -1320,7 +1369,31 @@ def mean(self, numeric_only: bool = False, **kwargs):
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
-        template_see_also[:-1],
+        template_see_also,
+        create_section_header("Examples"),
+        dedent(
+            """\
+        >>> ser = pd.Series([0, 1, 5, 2, 8])
+
+        To get an instance of :class:`~pandas.core.window.rolling.Window` we need
+        to pass the parameter `win_type`.
+
+        >>> type(ser.rolling(2, win_type='gaussian'))
+        <class 'pandas.core.window.rolling.Window'>
+
+        In order to use the `SciPy` Gaussian window we need to provide the parameters
+        `M` and `std`. The parameter `M` corresponds to 2 in our example.
+        We pass the second parameter `std` as a parameter of the following method:
+
+        >>> ser.rolling(2, win_type='gaussian').var(std=3)
+        0     NaN
+        1     0.5
+        2     8.0
+        3     4.5
+        4    18.0
+        dtype: float64
+        """
+        ),
         window_method="rolling",
         aggregation_description="weighted window variance",
         agg_method="var",
@@ -1338,7 +1411,31 @@ def var(self, ddof: int = 1, numeric_only: bool = False, **kwargs):
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
-        template_see_also[:-1],
+        template_see_also,
+        create_section_header("Examples"),
+        dedent(
+            """\
+        >>> ser = pd.Series([0, 1, 5, 2, 8])
+
+        To get an instance of :class:`~pandas.core.window.rolling.Window` we need
+        to pass the parameter `win_type`.
+
+        >>> type(ser.rolling(2, win_type='gaussian'))
+        <class 'pandas.core.window.rolling.Window'>
+
+        In order to use the `SciPy` Gaussian window we need to provide the parameters
+        `M` and `std`. The parameter `M` corresponds to 2 in our example.
+        We pass the second parameter `std` as a parameter of the following method:
+
+        >>> ser.rolling(2, win_type='gaussian').std(std=3)
+        0         NaN
+        1    0.707107
+        2    2.828427
+        3    2.121320
+        4    4.242641
+        dtype: float64
+        """
+        ),
         window_method="rolling",
         aggregation_description="weighted window standard deviation",
         agg_method="std",