code: def test_scaler():
      iris = h2o.import_file(
          pyunit_utils.locate("smalldata/iris/iris.csv")
      )
  
      scaler = H2OScaler()
      scaler.fit(iris)
  
      iris_transformed = scaler.transform(iris)
  
      assert [
          ["Iris-setosa", "Iris-versicolor", "Iris-virginica"]
      ] == iris_transformed["C5"].levels()
      assert (
          max(
              iris_transformed[["C1", "C2", "C3", "C4"]]
              .mean()
              .as_data_frame()
              .transpose()[0]
              .tolist()
          )
          < 1e-10
      )
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.transforms.preprocessing import H2OScaler
label_desc: Use image node_id 1 for calling a global function with example usage: test_scaler() without return types