code: def test_create_train_X_y_ValueError_when_all_series_values_are_missing():
      """
      Test ValueError is raised when all series values are missing.
      """
      series = pd.DataFrame(
          {"1": pd.Series(np.arange(7)), "2": pd.Series([np.nan] * 7)}
      )
      series.index = pd.date_range(
          start="2022-01-01", periods=7, freq="1D"
      )
      forecaster = ForecasterAutoregMultiSeries(
          LinearRegression(), lags=5
      )
  
      err_msg = re.escape("All values of series '2' are NaN.")
      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 7 for calling a global function with example usage: test_create_train_X_y_ValueError_when_all_series_values_are_missing() without return types