code: def insert_missing():
      # Connect to a pre-existing cluster
  
      data = [
          [1, 2, 3, 1, "a", 1, 9],
          [1, 6, 4, 2, "a", 1, 9],
          [2, 3, 8, 6, "b", 1, 9],
          [3, 4, 3, 2, "b", 3, 8],
          [4, 5, 9, 5, "c", 2, 8],
          [5, 7, 10, 7, "b", 8, 8],
      ]
      h2o_data = h2o.H2OFrame(data)
  
      h2o_data.insert_missing_values(fraction=0.0)
      print(h2o_data)
      num_nas = sum([v.isna().sum() for v in h2o_data])
      assert (
          num_nas == 0
      ), "Expected no missing values inserted, but got {0}".format(
          num_nas
      )
  
      h2o_data.insert_missing_values(fraction=1.0)
      print(h2o_data)
      num_nas = sum([v.isna().sum() for v in h2o_data])
      assert (
          num_nas == h2o_data.nrow * h2o_data.ncol
      ), "Expected all missing values inserted, but got {0}".format(
          num_nas
      )
  
imports: from builtins import zip
  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: insert_missing() without return types