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 name(self) -> Hashable:
      ilevel = self._ilevel
      if ilevel is not None:
          return self._index.names[ilevel]
  
      if isinstance(self._orig_grouper, (Index, Series)):
          return self._orig_grouper.name
  
      elif isinstance(self.grouping_vector, ops.BaseGrouper):
          return self.grouping_vector.result_index.name
  
      elif isinstance(self.grouping_vector, Index):
          return self.grouping_vector.name
  
      # otherwise we have ndarray or ExtensionArray -> no name
      return None
  
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 5 for calling the Grouping obj's underlying member method code with example usage: obj.name() and returns: None, self, self, self, self