fix docstrings and remove from code_checks.sh

Author: root

ci/code_checks.sh

@@ -98,9 +98,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \
         -i "pandas.core.groupby.SeriesGroupBy.indices SA01" \
-        -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
-        -i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
-        -i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
         -i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
         -i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
         -i "pandas.core.resample.Resampler.get_group RT03,SA01" \

pandas/core/groupby/generic.py

@@ -1443,6 +1443,11 @@ def is_monotonic_increasing(self) -> Series:
         -------
         Series
 
+        See Also
+        --------
+        SeriesGroupBy.is_monotonic_decreasing : Return whether each group's values
+            are monotonically decreasing.
+
         Examples
         --------
         >>> s = pd.Series([2, 1, 3, 4], index=["Falcon", "Falcon", "Parrot", "Parrot"])
@@ -1462,6 +1467,11 @@ def is_monotonic_decreasing(self) -> Series:
         -------
         Series
 
+        See Also
+        --------
+        SeriesGroupBy.is_monotonic_decreasing : Return whether each group's values
+            are monotonically decreasing.
+
         Examples
         --------
         >>> s = pd.Series([2, 1, 3, 4], index=["Falcon", "Falcon", "Parrot", "Parrot"])

pandas/core/groupby/groupby.py

@@ -3983,19 +3983,6 @@ def nth(self) -> GroupByNthSelector:
         'all' or 'any'; this is equivalent to calling dropna(how=dropna)
         before the groupby.
 
-        Parameters
-        ----------
-        n : int, slice or list of ints and slices
-            A single nth value for the row or a list of nth values or slices.
-
-            .. versionchanged:: 1.4.0
-                Added slice and lists containing slices.
-                Added index notation.
-
-        dropna : {'any', 'all', None}, default None
-            Apply the specified dropna operation before counting which row is
-            the nth row. Only supported if n is an int.
-
         Returns
         -------
         Series or DataFrame