code: def test1():
      df = h2o.upload_file(
          pyunit_utils.locate("smalldata/jira/pubdev_2020.csv")
      )
      splits = df.split_frame(ratios=[0.75])
  
      part0 = splits[0]
      part1 = splits[1]
      assert part0.nrow > 0, "First part of the split has no rows"
      assert part1.nrow > 0, "Second part of the split has no rows"
      assert df.nrow == (part0.nrow + part1.nrow), (
          "Original frame has %d rows, after splitting it has %d + %d rows"
          % (df.nrow, part0.nrow, part1.nrow)
      )
  
      split_was_sequential = True
      i = 0
      while i < part0.nrow:
          value = part0[i, "C1"]
          print(value)
          if value != (i + 1):
              split_was_sequential = False
          i += 1
  
      assert (
          not split_was_sequential
      ), "Split should be random, not sequential"
  
imports: import sys
  import h2o
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test1() without return types