code: def test_setitem_scalar_float(data_type):
      np.random.seed(0)
      scalar = np.random.randn(1).astype(data_type)[0]
      df = pd.DataFrame(
          {
              "x": np.random.randint(0, 5, size=20),
              "y": np.random.normal(size=20),
          }
      )
      dgf = dd.from_pandas(
          cudf.DataFrame.from_pandas(df), npartitions=2
      )
  
      df["z"] = scalar
      dgf["z"] = scalar
  
      got = dgf.compute().to_pandas()
      np.testing.assert_array_equal(got["z"], df["z"])
  
imports: import random
  import cupy
  import numpy
  import pandas
  import pytest
  from packaging import version
  import dask
  from dask import dataframe
  from dask.dataframe.core import make_meta, meta_nonempty
  from dask.utils import M
  import cudf
  import dask_cudf
label_desc: Use image node_id 21 for calling a global function with example usage: test_setitem_scalar_float(data_type) without return types