code: def nhanesi(display=False, n_points=None):
      """A nicely packaged version of NHANES I data with surivival times as labels."""
      X = pd.read_csv(
          cache(github_data_url + "NHANESI_X.csv"), index_col=0
      )
      y = pd.read_csv(
          cache(github_data_url + "NHANESI_y.csv"), index_col=0
      )["y"]
  
      if n_points is not None:
          X = shap.utils.sample(X, n_points, random_state=0)
          y = shap.utils.sample(y, n_points, random_state=0)
  
      if display:
          X_display = X.copy()
          # X_display["sex_isFemale"] = ["Female" if v else "Male" for v in X["sex_isFemale"]]
          return X_display, np.array(y)
      return X, np.array(y)
  
file_path: shap/shap/datasets.py
imports: import os
  from urllib.request import urlretrieve
  import numpy
  import pandas
  import sklearn.datasets
  import shap
label_desc: Use image node_id 9 for calling a global function with example usage: nhanesi(display, n_points) and returns: X,  np, X_display,  np