code: def ozoneKM():
      # Connect to a pre-existing cluster
      # connect to localhost:54321
  
      train = h2o.import_file(
          path=pyunit_utils.locate("smalldata/glm_test/ozone.csv")
      )
  
      # See that the data is ready
      print(train.describe())
  
      # Run KMeans
  
      from h2o.estimators.kmeans import H2OKMeansEstimator
  
      my_km = H2OKMeansEstimator(
          k=10, init="PlusPlus", max_iterations=100
      )
      my_km.train(x=list(range(train.ncol)), training_frame=train)
      my_km.show()
      my_km.summary()
  
      my_pred = my_km.predict(train)
      my_pred.describe()
  
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: ozoneKM() without return types