code: def _make_classification_y(
      n_instances=20, n_classes=2, return_numpy=True, random_state=None
  ):
      if not n_instances > n_classes:
          raise ValueError("n_instances must be bigger than n_classes")
      rng = check_random_state(random_state)
      n_repeats = int(np.ceil(n_instances / n_classes))
      y = np.tile(np.arange(n_classes), n_repeats)[:n_instances]
      rng.shuffle(y)
      if return_numpy:
          return y
      else:
          return pd.Series(y)
  
file_path: sktime/sktime/utils/_testing/panel.py
imports: import numpy
  import pandas
  from sklearn.utils.validation import check_random_state
  from sktime.datatypes import convert
label_desc: Use image node_id 4 for calling a global function with example usage: _make_classification_y(n_instances, n_classes, return_numpy, random_state) and returns: y, pd