code: def h2o_H2OFrame_sum():
      """
      Python API test: h2o.frame.H2OFrame.meansum(skipna=True, axis=0, **kwargs)
      """
      row_num = randrange(1, 10)
      col_num = randrange(1, 10)
      python_lists = np.random.randint(-5, 5, (row_num, col_num))
      h2oframe = h2o.H2OFrame(python_obj=python_lists)
  
      # axis = 0
      h2oSum = h2oframe.sum(skipna=False, axis=0)
      assert_is_type(h2oSum, H2OFrame)
      numpsum = list(np.sum(python_lists, axis=0))
      h2omean = h2oSum.as_data_frame(use_pandas=True, header=False)
      assert pyunit_utils.equal_two_arrays(
          numpsum, h2omean.values.tolist()[0], 1e-12, 1e-6
      ), ("h2o.H2OFrame.meansum()" " command is not working.")
  
      # axis = 1
      h2oSum = h2oframe.sum(skipna=False, axis=1)
      assert_is_type(h2oSum, H2OFrame)
      numpsum = list(np.sum(python_lists, axis=1))
      h2omean = h2oSum.as_data_frame(use_pandas=True, header=False)
      assert pyunit_utils.equal_two_arrays(
          numpsum, h2omean.values.T.tolist()[0], 1e-12, 1e-6
      ), ("h2o.H2OFrame.meansum()" " command is not working.")
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.utils.typechecks import assert_is_type
  from h2o.frame import H2OFrame
  from random import randrange
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: h2o_H2OFrame_sum() without return types