class_docstr: Pickier version of MetricFrame.
  
  This holds the internal result from a disaggregated metric
  computation, and provides `apply_grouping()` (to cover min
  and max), `difference()` and `ratio()` methods.
  
  The main difference to the results computed by MetricFrame
  is that no account is made of whether the user supplied
  a bare function or a dictionary. Hence the results are
  always Series or DataFrame.
  
  Parameters
  ----------
  overall: Series or DataFrame
      The metric function(s) computed on the entire dataset, split by
      control features if supplied
  by_group: Series or DataFrame
      The metric function(s) computed on each subgroup identified by
      the sensitive and control features
class_docstr_tok: ["Pickier","version","of","MetricFrame",".","This","holds","the","internal","result","from","a","disaggregated","metric","computation",",","and","provides","`","apply_grouping","(",")","`","(","to","cover","min","and","max",")",",","`","difference","(",")","`","and","`","ratio","(",")","`","methods",".","The","main","difference","to","the","results","computed","by","MetricFrame","is","that","no","account","is","made","of","whether","the","user","supplied","a","bare","function","or","a","dictionary",".","Hence","the","results","are","always","Series","or","DataFrame",".","Parameters","--","--","--","--","--","overall",":","Series","or","DataFrame","The","metric","function","(","s",")","computed","on","the","entire","dataset",",","split","by","control","features","if","supplied","by_group",":","Series","or","DataFrame","The","metric","function","(","s",")","computed","on","each","subgroup","identified","by","the","sensitive","and","control","features"]
docstr: Return overall metrics.
docstr_tok: ["Return","overall","metrics","."]
code: def overall(self) -> Union[pd.Series, pd.DataFrame]:
      """Return overall metrics."""
      return self._overall
  
file_path: fairlearn/fairlearn/metrics/_disaggregated_result.py
imports: import logging
  from typing import Dict, List, Optional, Union
  import numpy
  import pandas
  from ._annotated_metric_function import AnnotatedMetricFunction
label_desc: Use image node_id 2 for calling the DisaggregatedResult obj's underlying member method code with example usage: obj.overall() and returns: self