class_docstr: Holds the grouping information for a single key
  
  Parameters
  ----------
  index : Index
  grouper :
  obj :
  name :
  level :
  observed : boolean, 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
  
  Returns
  -------
  **Attributes**:
    * indices : dict of {group -> index_list}
    * labels : ndarray, group labels
    * ids : mapping of label -> group
    * counts : array of group counts
    * group_index : unique groups
    * groups : dict of {group -> label_list}
code: def labels(self):
      if self._labels is None:
          self._make_labels()
      return self._labels
  
imports: import warnings
  import numpy
  import pandas.compat
  from pandas.compat import callable, zip
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.common import ensure_categorical, is_categorical_dtype, is_datetime64_dtype, is_hashable, is_list_like, is_scalar, is_timedelta64_dtype
  from pandas.core.dtypes.generic import ABCSeries
  import pandas.core.algorithms
  from pandas.core.arrays import Categorical, ExtensionArray
  import pandas.core.common
  from pandas.core.frame import DataFrame
  from pandas.core.groupby.ops import BaseGrouper
  from pandas.core.index import CategoricalIndex, Index, MultiIndex
  from pandas.core.series import Series
  from pandas.io.formats.printing import pprint_thing
label_desc: Use image node_id 6 for calling the Grouping obj's underlying member method code with example usage: obj.labels() and returns: self