code: def test_prediction_ranger():
      input_df = pd.DataFrame(
          {
              "feat1": [10, 13, 10, 15],
              "prediction": [100, 200, 300, None],
          }
      )
  
      pred_fn, data, log = prediction_ranger(input_df, 150, 250)
  
      expected = pd.DataFrame(
          {
              "feat1": [10, 13, 10, 15],
              "prediction": [150, 200, 250, None],
          }
      )
  
      assert expected.equals(data)
  
imports: from collections import OrderedDict
  import math
  import pandas
  import pytest
  from numpy import nan, round, sqrt, floor, log
  from numpy.testing import assert_almost_equal
  from pandas.testing import assert_frame_equal
  from fklearn.training.transformation import selector, capper, floorer, prediction_ranger, count_categorizer, label_categorizer, quantile_biner, truncate_categorical, rank_categorical, onehot_categorizer, target_categorizer, standard_scaler, ecdfer, discrete_ecdfer, custom_transformer, value_mapper, null_injector, missing_warner
label_desc: Use image node_id 4 for calling a global function with example usage: test_prediction_ranger() without return types