code: def test_imputer():
      input_df = pd.DataFrame(
          {"col1": [10, 13, 10], "col2": [50, 100, None]}
      )
  
      input_df2 = pd.DataFrame(
          {"col1": [10, None], "col2": [None, 100]}
      )
  
      expected1 = pd.DataFrame(
          {"col1": [10.0, 13.0, 10.0], "col2": [50.0, 100.0, 75.0]}
      )
  
      expected2 = pd.DataFrame(
          {"col1": [10, 11.0], "col2": [75.0, 100]}
      )
  
      pred_fn, data, log = imputer(input_df, ["col1", "col2"], "mean")
  
      assert expected1.equals(data)
      assert expected2.equals(pred_fn(input_df2))
  
imports: import pandas
  from fklearn.training.imputation import imputer, placeholder_imputer
label_desc: Use image node_id 1 for calling a global function with example usage: test_imputer() without return types