code: def get_adult_shap_dataset():
      X, y = shap.datasets.adult()
  
      target_feature = "income"
      y = [1 if y_i else 0 for y_i in y]
  
      full_data = X.copy()
      full_data[target_feature] = y
  
      data_train, data_test = train_test_split(
          full_data,
          test_size=1000,
          random_state=96132,
          stratify=full_data[target_feature],
      )
  
      data_train.reset_index(drop=True, inplace=True)
      data_test.reset_index(drop=True, inplace=True)
  
      treatment_features = ["Age", "Sex"]
      heterogeneity_features = ["Marital Status"]
  
      cat_cols = [
          "Race",
          "Sex",
          "Workclass",
          "Marital Status",
          "Country",
          "Occupation",
      ]
  
      return (
          data_train,
          data_test,
          treatment_features,
          heterogeneity_features,
          cat_cols,
          target_feature,
      )
  
file_path: responsible-ai-toolbox/responsibleai/tests/causal/conftest.py
imports: import copy
  from typing import List, Tuple
  import numpy
  import pandas
  import pytest
  import shap
  from sklearn.model_selection import train_test_split
  from tests.common_utils import create_adult_income_dataset
  from rai_test_utils.datasets.tabular import create_housing_data
label_desc: Use image node_id 6 for calling a global function with example usage: get_adult_shap_dataset() and returns: data_train,  data_test,  treatment_features,  heterogeneity_features,  cat_cols,  target_feature