code: def test_create_train_X_y_ValueError_when_len_y_is_lower_than_maximum_lag_plus_steps():
      """
      Test ValueError is raised when length of y is lower than maximum lag plus
      number of steps included in the forecaster.
      """
      y = pd.Series(np.arange(5), name="y")
      forecaster = ForecasterAutoregDirect(
          LinearRegression(), lags=3, steps=3
      )
  
      err_msg = re.escape(
          (
              f"Minimum length of `y` for training this forecaster is "
              f"{forecaster.max_lag + forecaster.steps}. Got {len(y)}. Reduce the "
              f"number of predicted steps, {forecaster.steps}, or the maximum "
              f"lag, {forecaster.max_lag}, if no more data is available."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.create_train_X_y(y=y)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregDirect import ForecasterAutoregDirect
  from skforecast.exceptions import MissingValuesExogWarning
  from sklearn.linear_model import LinearRegression
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
label_desc: Use image node_id 3 for calling a global function with example usage: test_create_train_X_y_ValueError_when_len_y_is_lower_than_maximum_lag_plus_steps() without return types