code: def test_local_dask_cluster_extraction_two_worker(self):
      Distributor = LocalDaskDistributor(n_workers=2)
  
      df = self.create_test_data_sample()
      extracted_features = extract_features(
          df,
          column_id="id",
          column_sort="sort",
          column_kind="kind",
          column_value="val",
          distributor=Distributor,
      )
  
      self.assertIsInstance(extracted_features, pd.DataFrame)
      self.assertTrue(
          np.all(extracted_features.a__maximum == np.array([71, 77]))
      )
      self.assertTrue(
          np.all(
              extracted_features.a__sum_values == np.array([691, 1017])
          )
      )
      self.assertTrue(
          np.all(
              extracted_features.a__abs_energy
              == np.array([32211, 63167])
          )
      )
      self.assertTrue(
          np.all(
              extracted_features.b__sum_values == np.array([757, 695])
          )
      )
      self.assertTrue(
          np.all(extracted_features.b__minimum == np.array([3, 1]))
      )
      self.assertTrue(
          np.all(
              extracted_features.b__abs_energy
              == np.array([36619, 35483])
          )
      )
      self.assertTrue(
          np.all(extracted_features.b__mean == np.array([37.85, 34.75]))
      )
      self.assertTrue(
          np.all(extracted_features.b__median == np.array([39.5, 28.0]))
      )
  
imports: import sys
  from unittest import TestCase, skipIf
  import numpy
  import pandas
  from distributed import Client, LocalCluster
  from tests.fixtures import DataTestCase
  from tsfresh import extract_features
  from tsfresh.utilities.distribution import ClusterDaskDistributor, LocalDaskDistributor, MultiprocessingDistributor
  from tsfresh.utilities.profiling import get_n_jobs, set_n_jobs
label_desc: Use image node_id 2 for calling the LocalDaskDistributorTestCase obj's underlying member method code with example usage: obj.test_local_dask_cluster_extraction_two_worker() without return types