code: def test_frame_conversion(h2oFrame, original_pandas_frame):
      print(
          "h2o frame to pandas frame conversion using polars and pyarrow"
      )
      new_pandas_frame = h2oFrame.as_data_frame()
      # compare two frames column types
      new_types = new_pandas_frame.dtypes
      old_types = original_pandas_frame.dtypes
      ncol = h2oFrame.ncol
      colNames = new_pandas_frame.columns
  
      for ind in list(range(ncol)):
          assert new_types[colNames[ind]] == old_types[colNames[ind]], (
              "Expected column types: {0}, actual column types: "
              "{1}".format(
                  old_types[colNames[ind]], new_types[colNames[ind]]
              )
          )
          if new_types[colNames[ind]] == "object":
              diff = (
                  new_pandas_frame[colNames[ind]]
                  == original_pandas_frame[colNames[ind]]
              )
              if (
                  not diff.all()
              ):  # difference caused by the presence of NAs
                  newSeries = pd.Series(new_pandas_frame[colNames[ind]])
                  newNA = newSeries.isna()
                  oldSeries = pd.Series(
                      original_pandas_frame[colNames[ind]]
                  )
                  oldNA = oldSeries.isna()
                  assert (newNA == oldNA).all()
          else:
              diff = (
                  new_pandas_frame[colNames[ind]]
                  - original_pandas_frame[colNames[ind]]
              ).abs()
              assert diff.max() < 1e-10
  
file_path: h2o-3/h2o-py/tests/testdir_misc/pyunit_gh_15936_polars2pandas_error.py
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.utils.shared_utils import can_use_polars, can_use_pyarrow, can_install_polars
  import pandas
  from h2o.utils.threading import local_context
label_desc: Use image node_id 1 for calling a global function with example usage: test_frame_conversion(h2oFrame, original_pandas_frame) without return types