code: def test_pandas_no_pivot(self):
      df = self.df
  
      X = extract_features(
          df,
          column_id="my_id",
          column_sort="time",
          column_kind="dimension",
          column_value="value",
          pivot=False,
          default_fc_parameters=MinimalFCParameters(),
      )
      X = pd.DataFrame(X, columns=["my_id", "variable", "value"])
      self.assertIn("1__mean", X["variable"].values)
      self.assertAlmostEqual(
          X[(X["my_id"] == "5") & (X["variable"] == "1__mean")][
              "value"
          ].iloc[0],
          5.516e-05,
          4,
      )
      self.assertEqual(X.shape, (100 * 20, 3))
  
      X = extract_features(
          df,
          column_id="my_id",
          column_sort="time",
          column_kind="dimension",
          pivot=False,
          default_fc_parameters=MinimalFCParameters(),
      )
      X = pd.DataFrame(X, columns=["my_id", "variable", "value"])
      self.assertIn("1__mean", X["variable"].values)
      self.assertAlmostEqual(
          X[(X["my_id"] == "5") & (X["variable"] == "1__mean")][
              "value"
          ].iloc[0],
          5.516e-05,
          4,
      )
      self.assertEqual(X.shape, (100 * 20, 3))
  
      X = extract_features(
          df.drop(columns=["dimension"]),
          column_id="my_id",
          column_sort="time",
          pivot=False,
          default_fc_parameters=MinimalFCParameters(),
      )
      X = pd.DataFrame(X, columns=["my_id", "variable", "value"])
      self.assertIn("value__mean", X["variable"].values)
      self.assertAlmostEqual(
          X[(X["my_id"] == "5") & (X["variable"] == "value__mean")][
              "value"
          ].iloc[0],
          5.516e-05,
          4,
      )
      self.assertEqual(X.shape, (100 * 10, 3))
  
      X = extract_features(
          df.drop(columns=["dimension", "time"]),
          column_id="my_id",
          pivot=False,
          default_fc_parameters=MinimalFCParameters(),
      )
      X = pd.DataFrame(X, columns=["my_id", "variable", "value"])
      self.assertIn("value__mean", X["variable"].values)
      self.assertAlmostEqual(
          X[(X["my_id"] == "5") & (X["variable"] == "value__mean")][
              "value"
          ].iloc[0],
          5.516e-05,
          4,
      )
      self.assertEqual(X.shape, (100 * 10, 3))
  
file_path: tsfresh/tests/integrations/test_feature_extraction.py
imports: from unittest import TestCase
  import dask.dataframe
  import pandas
  from tsfresh import extract_features, extract_relevant_features
  from tsfresh.examples.driftbif_simulation import load_driftbif
  from tsfresh.feature_extraction import MinimalFCParameters
label_desc: Use image node_id 3 for calling the FeatureExtractionTestCase obj's underlying member method code with example usage: obj.test_pandas_no_pivot() without return types