code: def test_accumulated(self):
      self.helper_test("accumulated")
      case1 = self.exp2.model_profile(
          type="accumulated", center=False, verbose=False
      )
      case2 = self.exp2.model_profile(
          type="accumulated",
          variable_type="categorical",
          center=False,
          verbose=False,
      )
      alias = self.exp2.model_profile(
          type="ale", center=False, verbose=False
      )
  
      self.assertIsInstance(
          case1, dx.model_explanations.AggregatedProfiles
      )
      self.assertIsInstance(
          case2, dx.model_explanations.AggregatedProfiles
      )
      self.assertIsInstance(
          alias, dx.model_explanations.AggregatedProfiles
      )
  
      fig1 = case1.plot(show=False)
      fig2 = case2.plot(show=False)
  
      self.assertIsInstance(fig1, Figure)
      self.assertIsInstance(fig2, Figure)
  
      test1 = (
          case1.result.groupby("_vname_")
          .apply(lambda x: x["_yhat_"].abs().min())
          .tolist()
      )
      test2 = (
          case2.result.groupby("_vname_")
          .apply(lambda x: x["_yhat_"].abs().min())
          .tolist()
      )
  
      self.assertListEqual(test1, np.zeros(len(test1)).tolist())
      self.assertListEqual(test2, np.zeros(len(test2)).tolist())
  
file_path: DALEX/python/dalex/test/test_aggregated_profiles.py
imports: import unittest
  import numpy
  import pandas
  from plotly.graph_objs import Figure
  from sklearn.compose import ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.neural_network import MLPClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
  import dalex
label_desc: Use image node_id 3 for calling the AggregatedProfilesTestTitanic obj's underlying member method code with example usage: obj.test_accumulated() without return types