code: def rank():
      """Ranking datasets from lightgbm repository."""
      rank_data_url = "https://raw.githubusercontent.com/Microsoft/LightGBM/master/examples/lambdarank/"
      x_train, y_train = sklearn.datasets.load_svmlight_file(
          cache(rank_data_url + "rank.train")
      )
      x_test, y_test = sklearn.datasets.load_svmlight_file(
          cache(rank_data_url + "rank.test")
      )
      q_train = np.loadtxt(cache(rank_data_url + "rank.train.query"))
      q_test = np.loadtxt(cache(rank_data_url + "rank.test.query"))
  
      return x_train, y_train, x_test, y_test, q_train, q_test
  
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 13 for calling a global function with example usage: rank() and returns: x_train,  y_train,  x_test,  y_test,  q_train,  q_test