code: def test_isna_filters(tmpdir, null, numeric):
      tmp_path = str(tmpdir)
      df = pd.DataFrame(
          {
              "x": range(10),
              "y": list("aabbccddee"),
              "i": [0] * 4 + [np.nan] * 2 + [0] * 4,
              "j": [""] * 4 + [None] * 2 + [""] * 4,
          }
      )
      ddf = dd.from_pandas(df, npartitions=5)
      assert ddf.npartitions == 5
      ddf.to_parquet(tmp_path, engine="pyarrow")
  
      # Test "is"
      col = "i" if numeric else "j"
      filters = [(col, "is", null)]
      out = dask_cudf.read_parquet(
          tmp_path, filters=filters, split_row_groups=True
      )
      assert len(out) == 2
      assert list(out.x.compute().values) == [4, 5]
  
      # Test "is not"
      filters = [(col, "is not", null)]
      out = dask_cudf.read_parquet(
          tmp_path, filters=filters, split_row_groups=True
      )
      assert len(out) == 8
      assert list(out.x.compute().values) == [0, 1, 2, 3, 6, 7, 8, 9]
  
imports: import glob
  import math
  import os
  import numpy
  import pandas
  import pytest
  import dask
  from dask import dataframe
  from dask.utils import natural_sort_key
  import cudf
  import dask_cudf
label_desc: Use image node_id 14 for calling a global function with example usage: test_isna_filters(tmpdir, null, numeric) without return types