class_docstr: Holds the grouping information for a single key
  
  Parameters
  ----------
  index : Index
  grouper :
  obj : DataFrame or Series
  name : Label
  level :
  observed : bool, default False
      If we are a Categorical, use the observed values
  in_axis : if the Grouping is a column in self.obj and hence among
      Groupby.exclusions list
  dropna : bool, default True
      Whether to drop NA groups.
  uniques : Array-like, optional
      When specified, will be used for unique values. Enables including empty groups
      in the result for a BinGrouper. Must not contain duplicates.
  
  Attributes
  -------
  indices : dict
      Mapping of {group -> index_list}
  codes : ndarray
      Group codes
  group_index : Index or None
      unique groups
  groups : dict
      Mapping of {group -> label_list}
code: def group_index(self) -> Index:
      warnings.warn(
          "group_index is deprecated and will be removed in a future "
          "version of pandas",
          category=FutureWarning,
          stacklevel=find_stack_level(),
      )
      return self._group_index
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, final
  import warnings
  import numpy
  from pandas._config import using_copy_on_write, warn_copy_on_write
  from pandas._libs import lib
  from pandas._libs.tslibs import OutOfBoundsDatetime
  from pandas.errors import InvalidIndexError
  from pandas.util._decorators import cache_readonly
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import is_list_like, is_scalar
  from pandas.core.dtypes.dtypes import CategoricalDtype
  from pandas.core import algorithms
  from pandas.core.arrays import Categorical, ExtensionArray
  import pandas.core.common
  from pandas.core.frame import DataFrame
  from pandas.core.groupby import ops
  from pandas.core.groupby.categorical import recode_for_groupby
  from pandas.core.indexes.api import CategoricalIndex, Index, MultiIndex
  from pandas.core.series import Series
  from pandas.io.formats.printing import pprint_thing
label_desc: Use image node_id 15 for calling the Grouping obj's underlying member method code with example usage: obj.group_index() and returns: self