class_docstr: Class for computing metrics based on a single
  :obj:`~aif360.datasets.BinaryLabelDataset`.
class_docstr_tok: ["Class","for","computing","metrics","based","on","a","single",":","obj",":","`","~aif360.datasets.BinaryLabelDataset","`","."]
docstr: .. math::
     Pr(Y = 1 | D = \text{unprivileged})
     - Pr(Y = 1 | D = \text{privileged})
docstr_tok: ["..","math",":",":","Pr","(","Y","=","1","|","D","=","\\text","{","unprivileged","}",")","-","Pr","(","Y","=","1","|","D","=","\\text","{","privileged","}",")"]
code: def statistical_parity_difference(self):
      r"""
      .. math::
         Pr(Y = 1 | D = \text{unprivileged})
         - Pr(Y = 1 | D = \text{privileged})
      """
      return self.difference(self.base_rate)
  
imports: import numpy
  from sklearn.neighbors import NearestNeighbors
  from aif360.algorithms.inprocessing.gerryfair.auditor import Auditor
  from aif360.datasets import BinaryLabelDataset
  from aif360.datasets.multiclass_label_dataset import MulticlassLabelDataset
  from aif360.metrics import DatasetMetric, utils
  from aif360.algorithms.inprocessing.gerryfair.clean import *
label_desc: Use image node_id 6 for calling the BinaryLabelDatasetMetric obj's underlying member method code with example usage: obj.statistical_parity_difference() and returns: self