code: def test_check_na_execution(setup):
      df_raw = pd.DataFrame(
          np.nan, index=range(0, 20), columns=list("ABCDEFGHIJ")
      )
      for _ in range(20):
          df_raw.iloc[
              random.randint(0, 19), random.randint(0, 9)
          ] = random.randint(0, 99)
  
      df = md.DataFrame(df_raw, chunk_size=4)
  
      pd.testing.assert_frame_equal(
          df.isna().execute().fetch(), df_raw.isna()
      )
      pd.testing.assert_frame_equal(
          df.notna().execute().fetch(), df_raw.notna()
      )
  
      series_raw = pd.Series(np.nan, index=range(20))
      for _ in range(3):
          series_raw.iloc[random.randint(0, 19)] = random.randint(0, 99)
  
      series = md.Series(series_raw, chunk_size=4)
  
      pd.testing.assert_series_equal(
          series.isna().execute().fetch(), series_raw.isna()
      )
      pd.testing.assert_series_equal(
          series.notna().execute().fetch(), series_raw.notna()
      )
  
      idx_data = np.array([np.nan] * 20)
      for _ in range(3):
          idx_data[random.randint(0, 19)] = random.randint(0, 99)
      idx_raw = pd.Index(idx_data)
  
      idx = md.Index(idx_raw, chunk_size=4)
  
      np.testing.assert_array_equal(
          idx.isna().execute().fetch(), idx_raw.isna()
      )
      np.testing.assert_array_equal(
          idx.notna().execute().fetch(), idx_raw.notna()
      )
  
file_path: mars/mars/dataframe/missing/tests/test_missing_execution.py
imports: import random
  import re
  import string
  import numpy
  import pandas
  from ....None import dataframe
label_desc: Use image node_id 1 for calling a global function with example usage: test_check_na_execution(setup) without return types