code: def test_append_levels():
      species = "C5"
      iris = h2o.import_file(
          path=pyunit_utils.locate("smalldata/iris/iris.csv")
      )
      iris[species] = iris[species].asfactor()
      assert iris[species].levels()[0] == [
          "Iris-setosa",
          "Iris-versicolor",
          "Iris-virginica",
      ]
  
      iris[species] = iris[species].append_levels(["levelA", "levelB"])
      assert iris[species].levels()[0] == [
          "Iris-setosa",
          "Iris-versicolor",
          "Iris-virginica",
          "levelA",
          "levelB",
      ]
  
      # appending new levels allows me to use them
      iris[0, species] = "levelA"
      iris[iris.nrow - 1, species] = "levelB"
  
      counts = iris[species].table().as_data_frame()
      expected_counts = {
          "C5": [
              "Iris-setosa",
              "Iris-versicolor",
              "Iris-virginica",
              "levelA",
              "levelB",
          ],
          "Count": [49, 50, 49, 1, 1],
      }
      expected = pd.DataFrame.from_dict(expected_counts)
      assert_frame_equal(expected, counts)
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  import pandas
  from pandas.testing import assert_frame_equal
label_desc: Use image node_id 1 for calling a global function with example usage: test_append_levels() without return types