class_docstr: Calculates absolute metrics for a given dataframe with model scores and
  labels, divided by different values on protected attributes.
  
  Attributes
  ----------
  absolute_metrics : List[str]
      Calculated bias metrics.
  
  Methods
  -------
  get_crosstabs(df, score_thresholds=None, attr_cols=None, score_col="score", label_col="label_value")
      Calculates metrics for a given dataframe.
  get_multimodel_crosstabs(df, score_thresholds=None, attr_cols=None, score_col="score", label_col="label_value")
      Calculates metrics for a given dataframe with multiple models.
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code: def __init__(self, input_group_metrics=all_group_metrics):
      self.absolute_metrics = input_group_metrics
  
file_path: aequitas/src/aequitas/group.py
imports: import logging
  import uuid
  from typing import Any, Dict, List, Tuple, Union
  from collections import OrderedDict
  import numpy
  import pandas
  from .bias import Bias
  from .plot import summary, disparity, absolute
label_desc: Use image node_id 1 to create a new Group object from inherited base classes: object with example: obj = Group(input_group_metrics)