docstr: Sort each list by the values.
  Sort the lists in ascending or descending order by some criterion.
  
  Parameters
  ----------
  ascending : bool, default True
      If True, sort values in ascending order, otherwise descending.
  na_position : {'first', 'last'}, default 'last'
      'first' puts nulls at the beginning, 'last' puts nulls at the end.
  ignore_index : bool, default False
      If True, the resulting axis will be labeled 0, 1, ..., n - 1.
  
  Returns
  -------
  ListColumn with each list sorted
  
  Notes
  -----
  Difference from pandas:
    * Not supporting: `inplace`, `kind`
  
  Examples
  --------
  >>> s = cudf.Series([[4, 2, None, 9], [8, 8, 2], [2, 1]])
  >>> ds = dask_cudf.from_cudf(s, 2)
  >>> ds.list.sort_values(ascending=True, na_position="last").compute()
  0    [2.0, 4.0, 9.0, nan]
  1         [2.0, 8.0, 8.0]
  2              [1.0, 2.0]
  dtype: list
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code: def sort_values(
      self,
      ascending=True,
      inplace=False,
      kind="quicksort",
      na_position="last",
      ignore_index=False,
  ):
      """
      Sort each list by the values.
      Sort the lists in ascending or descending order by some criterion.
  
      Parameters
      ----------
      ascending : bool, default True
          If True, sort values in ascending order, otherwise descending.
      na_position : {'first', 'last'}, default 'last'
          'first' puts nulls at the beginning, 'last' puts nulls at the end.
      ignore_index : bool, default False
          If True, the resulting axis will be labeled 0, 1, ..., n - 1.
  
      Returns
      -------
      ListColumn with each list sorted
  
      Notes
      -----
      Difference from pandas:
        * Not supporting: `inplace`, `kind`
  
      Examples
      --------
      >>> s = cudf.Series([[4, 2, None, 9], [8, 8, 2], [2, 1]])
      >>> ds = dask_cudf.from_cudf(s, 2)
      >>> ds.list.sort_values(ascending=True, na_position="last").compute()
      0    [2.0, 4.0, 9.0, nan]
      1         [2.0, 8.0, 8.0]
      2              [1.0, 2.0]
      dtype: list
      """
      return self.d_series.map_partitions(
          lambda s: s.list.sort_values(
              ascending, inplace, kind, na_position, ignore_index
          ),
          meta=self.d_series._meta,
      )
  
file_path: cudf/python/dask_cudf/dask_cudf/accessors.py
label_desc: Use image node_id 8 for calling the ListMethods obj's underlying member method code with example usage: obj.sort_values(ascending, inplace, kind, na_position, ignore_index) and returns: self