DOC: Fix PR01 errors in multiple files (pandas-dev#57438)

Fixed PR01 errors (pandas-dev#57438) and added parameter descriptions for:
- `pandas.Grouper`
- `pandas.core.groupby.DataFrameGroupBy.cummax`
- `pandas.core.groupby.DataFrameGroupBy.cummin`
- `pandas.core.groupby.DataFrameGroupBy.cumprod`
- `pandas.core.groupby.DataFrameGroupBy.cumsum`
- `pandas.core.groupby.DataFrameGroupBy.filter`
- `pandas.core.groupby.DataFrameGroupBy.pct_change`
- `pandas.core.groupby.DataFrameGroupBy.rolling`
- `pandas.core.groupby.SeriesGroupBy.cummax`
- `pandas.core.groupby.SeriesGroupBy.cummin`
- `pandas.core.groupby.SeriesGroupBy.cumprod`
- `pandas.core.groupby.SeriesGroupBy.cumsum`
- `pandas.core.groupby.SeriesGroupBy.cumprod`

Fixed functions also removed from code_checks.sh

ci/code_checks.sh

@@ -1477,7 +1477,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.DatetimeIndex.std\
         pandas.ExcelFile\
         pandas.ExcelFile.parse\
-        pandas.Grouper\
         pandas.HDFStore.append\
         pandas.HDFStore.put\
         pandas.Index.get_indexer_for\
@@ -1538,21 +1537,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.api.types.is_float\
         pandas.api.types.is_hashable\
         pandas.api.types.is_integer\
-        pandas.core.groupby.DataFrameGroupBy.cummax\
-        pandas.core.groupby.DataFrameGroupBy.cummin\
-        pandas.core.groupby.DataFrameGroupBy.cumprod\
-        pandas.core.groupby.DataFrameGroupBy.cumsum\
-        pandas.core.groupby.DataFrameGroupBy.filter\
-        pandas.core.groupby.DataFrameGroupBy.pct_change\
-        pandas.core.groupby.DataFrameGroupBy.rolling\
-        pandas.core.groupby.SeriesGroupBy.cummax\
-        pandas.core.groupby.SeriesGroupBy.cummin\
-        pandas.core.groupby.SeriesGroupBy.cumprod\
-        pandas.core.groupby.SeriesGroupBy.cumsum\
         pandas.core.groupby.SeriesGroupBy.filter\
-        pandas.core.groupby.SeriesGroupBy.nunique\
-        pandas.core.groupby.SeriesGroupBy.pct_change\
-        pandas.core.groupby.SeriesGroupBy.rolling\
         pandas.core.resample.Resampler.max\
         pandas.core.resample.Resampler.min\
         pandas.core.resample.Resampler.quantile\

pandas/core/groupby/generic.py

@@ -723,6 +723,11 @@ def nunique(self, dropna: bool = True) -> Series | DataFrame:
         """
         Return number of unique elements in the group.
 
+        Parameters
+        ----------
+        dropna : bool, default True
+            Don't include NaN in the counts.
+
         Returns
         -------
         Series
@@ -1942,6 +1947,10 @@ def filter(self, func, dropna: bool = True, *args, **kwargs) -> DataFrame:
         dropna : bool
             Drop groups that do not pass the filter. True by default; if False,
             groups that evaluate False are filled with NaNs.
+        *args
+            Additional positional arguments to pass to `func`.
+        **kwargs
+            Additional keyword arguments to pass to `func`.
 
         Returns
         -------

pandas/core/groupby/groupby.py

@@ -4672,6 +4672,13 @@ def cumprod(self, *args, **kwargs) -> NDFrameT:
         """
         Cumulative product for each group.
 
+        Parameters
+        ----------
+        *args : tuple
+            Positional arguments to be passed to `func`.
+        **kwargs : dict
+            Additional/specific keyword arguments to be passed to the function, such as `numeric_only` and `skipna`.
+
         Returns
         -------
         Series or DataFrame
@@ -4721,6 +4728,13 @@ def cumprod(self, *args, **kwargs) -> NDFrameT:
     def cumsum(self, *args, **kwargs) -> NDFrameT:
         """
         Cumulative sum for each group.
+        
+        Parameters
+        ----------
+        *args : tuple
+            Positional arguments to be passed to `func`.
+        **kwargs : dict
+            Additional/specific keyword arguments to be passed to the function, such as `numeric_only` and `skipna`.
 
         Returns
         -------
@@ -4776,6 +4790,14 @@ def cummin(
         """
         Cumulative min for each group.
 
+        Parameters
+        ----------
+        numeric_only : bool, default False
+            Include only `float`, `int` or `boolean` data.
+        **kwargs : dict, optional
+            Additional keyword arguments to be passed to the function, such as `skipna`, to control whether
+            NA/null values are ignored.
+
         Returns
         -------
         Series or DataFrame
@@ -4838,6 +4860,14 @@ def cummax(
         """
         Cumulative max for each group.
 
+        Parameters
+        ----------
+        numeric_only : bool, default False
+            Include only `float`, `int` or `boolean` data.
+        **kwargs : dict, optional
+            Additional keyword arguments to be passed to the function, such as `skipna`, to control whether
+            NA/null values are ignored.
+
         Returns
         -------
         Series or DataFrame
@@ -5134,6 +5164,32 @@ def pct_change(
         """
         Calculate pct_change of each value to previous entry in group.
 
+        Parameters
+        ----------
+        periods : int, default 1
+            Periods to shift for calculating percentage change. (E.g., 1
+            compares adjacent elements, while a period of 2 compares every other element).
+
+        fill_method : FillnaOptions or None, default None
+            This parameter specifies how to handle missing values after the initial shift operation
+            that is necessary for calculating the percentage change. In future versions, users will be
+            encouraged to manually handle missing values prior to using `pct_change`. Options for fill methods
+            (when explicitly specified) are as follows:
+            
+            - A FillnaOptions value (e.g., 'ffill', 'bfill') to specify forward or backward filling.
+            - None to indicate that no filling should be performed.
+
+            Note: Direct use of this parameter is discouraged due to the impending deprecation.
+
+        limit : int or None, default None
+            The maximum number of consecutive NA values to forward or backward fill, depending on the
+            `fill_method` chosen. This parameter's functionality is also subject to deprecation, and it is 
+            recommended that NaN values be addressed prior to calling `pct_change`.
+
+        freq : str, pandas offset object or None, default None
+            Increment to use from time series API (e.g., 'M' for month-end frequency). This parameter is
+            only relevant if the data is time series. If None, the frequency inferred from the index will be used.
+
         Returns
         -------
         Series or DataFrame

pandas/core/groupby/grouper.py

@@ -68,6 +68,10 @@ class Grouper:
 
     Parameters
     ----------
+    *args
+        Currently unused, reserved for future use.
+    **kwargs
+        Dictionary of the keyword arguments to pass to Grouper.
     key : str, defaults to None
         Groupby key, which selects the grouping column of the target.
     level : name/number, defaults to None