code: def h2o_H2OFrame_quantile():
      """
      Python API test: h2o.frame.H2OFrame.quantile(prob=None, combine_method='interpolate', weights_column=None)
  
      Copied from pyunit_quantile.py
      """
      data = [[random.uniform(-10000, 10000)] for c in range(1000)]
      h2o_data = h2o.H2OFrame(data)
      np_data = np.array(data)
      h2o_quants = h2o_data.quantile(
          prob=None, combine_method="interpolate", weights_column=None
      )
      assert_is_type(h2o_quants, H2OFrame)
  
      np_quants = np.percentile(
          np_data, [1, 10, 25, 33.3, 50, 66.7, 75, 90, 99], axis=0
      )
  
      for e in range(9):
          h2o_val = h2o_quants[e, 1]
          np_val = np_quants[e][0]
          assert abs(h2o_val - np_val) < 1e-06, (
              "check unsuccessful! h2o computed {0} and numpy computed {1}. expected equal quantile values between h2o "
              "and numpy".format(h2o_val, np_val)
          )
  
      h2o.remove(h2o_data)
  
imports: import sys
  from tests import pyunit_utils
  import h2o
  import numpy
  from h2o.utils.typechecks import assert_is_type
  from h2o.frame import H2OFrame
  import random
label_desc: Use image node_id 1 for calling a global function with example usage: h2o_H2OFrame_quantile() without return types