code: def test_transform_and_inverse_transform(df_vartypes):
      transformer = ArcsinTransformer(variables=["Marks"])
      X = transformer.fit_transform(df_vartypes)
  
      # expected output
      transf_df = df_vartypes.copy()
      transf_df["Marks"] = [1.24905, 1.10715, 0.99116, 0.88607]
  
      # 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["Marks"] = Xit["Marks"].round(1)
  
      # test
      pd.testing.assert_frame_equal(Xit, df_vartypes)
  
file_path: feature_engine/tests/test_transformation/test_arcsin_transformer.py
imports: import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.transformation import ArcsinTransformer
label_desc: Use image node_id 1 for calling a global function with example usage: test_transform_and_inverse_transform(df_vartypes) without return types