code: def create_adult_census_data(string_labels=False):
      """Create Adult census dataset for classification.
  
      param string_labels: Whether to return labels as strings.
      type string_labels: bool
      return: Tuple of X_train, X_test, y_train, y_test, categorical_features.
      rtype: Tuple of pandas.DataFrame, pandas.DataFrame, numpy.ndarray,
             numpy.ndarray, list
      """
      X, y = shap.datasets.adult()
      if string_labels:
          y = [">=50K" if r else "<50K" for r in y]
      else:
          y = [1 if r else 0 for r in y]
  
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, test_size=0.2, random_state=7, stratify=y
      )
  
      categorical_features = [
          "Workclass",
          "Education-Num",
          "Marital Status",
          "Occupation",
          "Relationship",
          "Race",
          "Sex",
          "Country",
      ]
      return X_train, X_test, y_train, y_test, categorical_features
  
file_path: responsible-ai-toolbox/rai_test_utils/rai_test_utils/datasets/tabular/classification_data_utils.py
imports: import numpy
  import pandas
  import shap
  from pandas import read_csv
  from sklearn.datasets import load_breast_cancer, load_iris, load_wine, make_classification
  from sklearn.model_selection import train_test_split
  from rai_test_utils.utilities import retrieve_dataset
label_desc: Use image node_id 3 for calling a global function with example usage: create_adult_census_data(string_labels) and returns: X_train,  X_test,  y_train,  y_test,  categorical_features