diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 1e9250fd77fe5..a6148b0314218 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -330,7 +330,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.groupby.DataFrameGroupBy.hist RT03" \
         -i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.max SA01" \
-        -i "pandas.core.groupby.DataFrameGroupBy.median SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.min SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \
         -i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
@@ -349,7 +348,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.max SA01" \
-        -i "pandas.core.groupby.SeriesGroupBy.median SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.min SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
         -i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
@@ -364,7 +362,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.resample.Resampler.indices SA01" \
         -i "pandas.core.resample.Resampler.max PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.mean SA01" \
-        -i "pandas.core.resample.Resampler.median SA01" \
         -i "pandas.core.resample.Resampler.min PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.ohlc SA01" \
         -i "pandas.core.resample.Resampler.prod SA01" \
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index bf71bb80b3623..4c8b8dcc35387 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2338,6 +2338,12 @@ def median(self, numeric_only: bool = False) -> NDFrameT:
         Series or DataFrame
             Median of values within each group.
 
+        See Also
+        --------
+        Series.groupby : Apply a function groupby to a Series.
+        DataFrame.groupby : Apply a function groupby to each row or column of a
+            DataFrame.
+
         Examples
         --------
         For SeriesGroupBy: