code: def _gen_data_fraud(datasets_root_dir):
      local_url = os.path.join(datasets_root_dir, "creditcard.csv.zip")
  
      if not os.path.isfile(local_url):
          raise ValueError(
              "Fraud dataset not found (search path: %s)" % local_url
          )
  
      df = pd.read_csv(local_url, dtype=np.float32)
      X = df[[col for col in df.columns if col.startswith("V")]]
      y = df["Class"]
  
      return X, y
  
imports: from cuml.internals.import_utils import has_scipy
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals import input_utils
  from urllib.request import urlretrieve
  import sklearn.model_selection
  from sklearn.datasets import load_svmlight_file, fetch_covtype
  import cuml.datasets
  from cuml.internals.safe_imports import cpu_only_import
  import os
  import functools
  import gzip
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 10 for calling a global function with example usage: _gen_data_fraud(datasets_root_dir) and returns: X,  y