code: def test_log_base_10_plus_user_passes_var_list(df_vartypes):
      # test case 2: log base 10, user passes variables
      transformer = LogTransformer(base="10", variables="Age")
      X = transformer.fit_transform(df_vartypes)
  
      # expected output
      transf_df = df_vartypes.copy()
      transf_df["Age"] = [1.30103, 1.32222, 1.27875, 1.25527]
  
      # test init params
      assert transformer.base == "10"
      assert transformer.variables == "Age"
      # test fit attr
      assert transformer.variables_ == ["Age"]
      assert transformer.n_features_in_ == 5
      # test transform output
      pd.testing.assert_frame_equal(X, transf_df)
  
      # test inverse_transform
      Xit = transformer.inverse_transform(X)
  
      # convert numbers to original format.
      Xit["Age"] = Xit["Age"].round().astype("int64")
  
      # test
      pd.testing.assert_frame_equal(Xit, df_vartypes)
  
file_path: feature_engine/tests/test_transformation/test_log_transformer.py
imports: import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.transformation import LogTransformer
label_desc: Use image node_id 2 for calling a global function with example usage: test_log_base_10_plus_user_passes_var_list(df_vartypes) without return types