code: def test_automatically_select_variables(df_enc):
      encoder = WoEEncoder(variables=None)
      encoder.fit(df_enc[["var_A", "var_B"]], df_enc["target"])
      X = encoder.transform(df_enc[["var_A", "var_B"]])
  
      # transformed dataframe
      transf_df = df_enc.copy()
      transf_df["var_A"] = VAR_A
      transf_df["var_B"] = VAR_B
  
      assert encoder.encoder_dict_ == {
          "var_A": {
              "A": 0.15415067982725836,
              "B": -0.5389965007326869,
              "C": 0.8472978603872037,
          },
          "var_B": {
              "A": -0.5389965007326869,
              "B": 0.15415067982725836,
              "C": 0.8472978603872037,
          },
      }
      pd.testing.assert_frame_equal(X, transf_df[["var_A", "var_B"]])
  
file_path: feature_engine/tests/test_encoding/test_woe_encoder.py
imports: import pandas
  import pytest
  from feature_engine.encoding import WoEEncoder
label_desc: Use image node_id 1 for calling a global function with example usage: test_automatically_select_variables(df_enc) without return types