code: def test_infogram_personal_loan_plot():
      """
      checking plotting function of infogram for fair model
      """
      fr = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/admissibleml_test/Bank_Personal_Loan_Modelling.csv"
          )
      )
      target = "Personal Loan"
      fr[target] = fr[target].asfactor()
      x = [
          "Experience",
          "Income",
          "Family",
          "CCAvg",
          "Education",
          "Mortgage",
          "Securities Account",
          "CD Account",
          "Online",
          "CreditCard",
      ]
      infogram_model = H2OInfogram(
          seed=12345, protected_columns=["Age", "ZIP Code"]
      )
      infogram_model.train(x=x, y=target, training_frame=fr)
      infogram_model.plot(server=True)
  
      infogram_model2 = H2OInfogram(
          seed=12345,
          protected_columns=["Age", "ZIP Code"],
          safety_index_threshold=0.05,
          relevance_index_threshold=0.05,
      )
      infogram_model2.train(x=x, y=target, training_frame=fr)
      infogram_model2.plot(server=True)
      assert len(infogram_model.get_admissible_cmi()) <= len(
          infogram_model2.get_admissible_cmi()
      )
  
imports: import os
  import sys
  import h2o
  from h2o.estimators.infogram import H2OInfogram
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_infogram_personal_loan_plot() without return types