code: def prepare_covtype(dataset_folder, nrows=None):
      from sklearn.datasets import fetch_covtype
  
      print("Preparing dataset ...")
      X, y = fetch_covtype(
          return_X_y=True
      )  # pylint: disable=unexpected-keyword-arg
      if nrows is not None:
          X = X[0:nrows]
          y = y[0:nrows]
  
      X_train, X_test, y_train, y_test = train_test_split(
          X,
          y,
          random_state=77,
          test_size=0.2,
      )
      return Data(
          X_train.astype("|f4"),
          X_test.astype("|f4"),
          y_train,
          y_test,
          LearningTask.MULTICLASS_CLASSIFICATION,
      )
  
imports: import os
  from enum import Enum
  import pandas
  import pickle
  import numpy
  from sklearn.model_selection import train_test_split
  from sklearn.datasets import load_svmlight_file
  from urllib.request import urlretrieve
label_desc: Use image node_id 7 for calling a global function with example usage: prepare_covtype(dataset_folder, nrows) and returns: Data