code: def test_grouping_column_not_in_df(penguins_df):
      meta = GroupedTransformer(
          StandardScaler(), groups=["island", "unexisting_column"]
      )
  
      # This should raise ValueError
      with pytest.raises(ValueError):
          meta.fit_transform(penguins_df)
  
imports: import itertools
  import numpy
  import pandas
  import pytest
  from sklearn.linear_model import LinearRegression
  from sklearn.preprocessing import MinMaxScaler, StandardScaler
  from sklearn.utils import check_X_y
  from sklego.common import flatten
  from sklego.datasets import load_penguins
  from sklego.meta import GroupedTransformer
  from tests.conftest import general_checks, k_vals, n_vals, np_types, select_tests, transformer_checks
label_desc: Use image node_id 22 for calling a global function with example usage: test_grouping_column_not_in_df(penguins_df) without return types