code: def test_4723():
      pandas_frame = pandas.read_csv(TEST_DATASET)
      frame = h2o.import_file(TEST_DATASET)
  
      # Ensure that the as_data_frame method does not modify the frame
      assert_frame_equal(pandas_frame, frame.as_data_frame())
  
      # Now insert some missing values
      expected_rows_count = frame["RACE"].shape[0]
  
      # Check that the shape of the data frames is not modified
      pandas_default_rows_count = (
          frame["RACE"].as_data_frame(use_pandas=True).shape[0]
      )
      assert pandas_default_rows_count == expected_rows_count, (
          "Result's rows count when using pandas with default na_value equal to expected_rows_count. Expected: %s, actual: %s"
          % (expected_rows_count, pandas_default_rows_count)
      )
      no_pandas_default_rows_count = len(
          frame["RACE"].as_data_frame(use_pandas=False, header=False)
      )
      assert no_pandas_default_rows_count == expected_rows_count, (
          "Result's rows count when NOT using pandas must be equal to expected_rows_count. Expected: %s, actual: %s"
          % (expected_rows_count, no_pandas_default_rows_count)
      )
  
imports: import pandas
  import h2o
  from tests import pyunit_utils
  from pandas.util.testing import assert_frame_equal
label_desc: Use image node_id 1 for calling a global function with example usage: test_4723() without return types