code: def test_sparse_dataframe(version):
      if not pa.pandas_compat._pandas_api.has_sparse:
          pytest.skip(
              "version of pandas does not support SparseDataFrame"
          )
      # GH #221
      data = {"A": [0, 1, 2], "B": [1, 0, 1]}
      df = pd.DataFrame(data).to_sparse(fill_value=1)
      expected = df.to_dense()
      _check_pandas_roundtrip(df, expected, version=version)
  
imports: import io
  import os
  import sys
  import tempfile
  import pytest
  import hypothesis
  import hypothesis.strategies
  import numpy
  import pyarrow
  import pyarrow.tests.strategies
  from pyarrow.feather import read_feather, write_feather, read_table, FeatherDataset
label_desc: Use image node_id 41 for calling a global function with example usage: test_sparse_dataframe(version) without return types