diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index dde98a01cc770..71ab2ac35cb1a 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -88,19 +88,15 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.arrays.TimedeltaArray PR07,SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \
-        -i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
-        -i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
-        -i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
         -i "pandas.core.resample.Resampler.get_group RT03,SA01" \
         -i "pandas.core.resample.Resampler.max PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.mean SA01" \
         -i "pandas.core.resample.Resampler.min PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.prod SA01" \
         -i "pandas.core.resample.Resampler.quantile PR01,PR07" \
-        -i "pandas.core.resample.Resampler.sem SA01" \
         -i "pandas.core.resample.Resampler.std SA01" \
         -i "pandas.core.resample.Resampler.transform PR01,RT03,SA01" \
         -i "pandas.core.resample.Resampler.var SA01" \
diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 35ec09892ede6..3a917e0147396 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -2453,6 +2453,10 @@ def nunique(self, dropna: bool = True) -> DataFrame:
         nunique: DataFrame
             Counts of unique elements in each position.
 
+        See Also
+        --------
+        DataFrame.nunique : Count number of distinct elements in specified axis.
+
         Examples
         --------
         >>> df = pd.DataFrame(
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 48d4e0456d4fa..e750c606a4c44 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2658,6 +2658,11 @@ def sem(self, ddof: int = 1, numeric_only: bool = False) -> NDFrameT:
         Series or DataFrame
             Standard error of the mean of values within each group.
 
+        See Also
+        --------
+        DataFrame.sem : Return unbiased standard error of the mean over requested axis.
+        Series.sem : Return unbiased standard error of the mean over requested axis.
+
         Examples
         --------
         For SeriesGroupBy: