code: def test_apply_with_arrow_dtype_execution(setup):
      df1 = pd.DataFrame({"a": [1, 2, 1], "b": ["a", "b", "a"]})
      df = from_pandas_df(df1)
      df["b"] = df["b"].astype("Arrow[string]")
  
      r = df.apply(lambda row: str(row[0]) + row[1], axis=1)
      result = r.execute().fetch()
      expected = df1.apply(lambda row: str(row[0]) + row[1], axis=1)
      pd.testing.assert_series_equal(result, expected)
  
      s1 = df1["b"]
      s = from_pandas_series(s1)
      s = s.astype("arrow_string")
  
      r = s.apply(lambda x: x + "_suffix")
      result = r.execute().fetch()
      expected = s1.apply(lambda x: x + "_suffix")
      pd.testing.assert_series_equal(result, expected)
  
imports: import random
  from collections import OrderedDict
  import numpy
  import pandas
  import pytest
  import mars
  from ....config import options, option_context
  from ....dataframe import DataFrame, Series
  from ....tensor import arange, tensor
  from ....tensor.random import rand
  from ....tests.core import require_cudf
  from ....utils import lazy_import, pd_release_version, no_default
  from ...None import eval, cut, qcut, get_dummies
  from ...core import DATAFRAME_OR_SERIES_TYPE
  from ...datasource.dataframe import from_pandas
  from ...datasource.series import from_pandas
  from ...datasource.index import from_pandas
  from ..None import to_gpu, to_cpu
  from ..bloom_filter import filter_by_bloom_filter
  from ..shift import _enable_no_default, _with_column_freq_bug
  from ..to_numeric import to_numeric
  from ..rebalance import DataFrameRebalance
label_desc: Use image node_id 11 for calling a global function with example usage: test_apply_with_arrow_dtype_execution(setup) without return types