code: def test_pca_importance():
      arrestsH2O = h2o.upload_file(
          pyunit_utils.locate("smalldata/pca_test/USArrests.csv")
      )
      fitH2O = H2OPrincipalComponentAnalysisEstimator(
          k=4, transform="DEMEAN"
      )
      fitH2O.train(x=list(range(4)), training_frame=arrestsH2O)
      assert fitH2O.varimp()
  
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.pca import H2OPrincipalComponentAnalysisEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_pca_importance() without return types