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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docstr: View list of all calculated absolute bias metrics in df.
  
  Parameters
  ----------
  df : pandas.DataFrame
      The result of the `get_crosstabs` methods.
  
  Returns
  -------
  List[Any]
      Absolute bias metrics.
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code: def list_absolute_metrics(self, df: pd.DataFrame) -> List[Any]:
      """
      View list of all calculated absolute bias metrics in df.
  
      Parameters
      ----------
      df : pandas.DataFrame
          The result of the `get_crosstabs` methods.
  
      Returns
      -------
      List[Any]
          Absolute bias metrics.
      """
      return df.columns.intersection(self.absolute_metrics).tolist()
  
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 6 for calling the Group obj's underlying member method code with example usage: obj.list_absolute_metrics(df) and returns: df