code: def test_create_train_X_y_ValueError_when_series_values_are_missing(
      values,
  ):
      """
      Test ValueError is raised when series values are missing in different
      locations.
      """
      series = pd.DataFrame(
          {"1": pd.Series(values), "2": pd.Series(np.arange(7))}
      )
      series.index = pd.date_range(
          start="2022-01-01", periods=7, freq="1D"
      )
      forecaster = ForecasterAutoregMultiSeries(
          LinearRegression(), lags=5
      )
  
      err_msg = re.escape(
          (
              "'1' Time series has missing values in between or "
              "at the end of the time series. When working with series "
              "of different lengths, all series must be complete after "
              "the first non-null value."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.create_train_X_y(series=series)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiSeries import ForecasterAutoregMultiSeries
  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 8 for calling a global function with example usage: test_create_train_X_y_ValueError_when_series_values_are_missing(values) without return types