code: def _get_data(A_two_dim=False, y_as_scores=False, flip_y=False):
      X = pd.DataFrame({"X1": X1, "X2": X2, "X3": X3})
  
      if y_as_scores:
          y = pd.Series(scores)
      else:  # classification
          y = pd.Series(labels)
          if flip_y:
              y = pd.Series([int(not i) for i in labels])
  
      if A_two_dim:
          # Stacking the same column a few times will result in the identical groups
          # compared to using a single column, therefore results should be the same.
          A = np.stack((sensitive_features, sensitive_features), -1)
      else:
          A = pd.Series(sensitive_features)
      return X, y, A
  
label_desc: Use image node_id 1 for calling a global function with example usage: _get_data(A_two_dim, y_as_scores, flip_y) and returns: X,  y,  A