code: def test_calculate_variable_profile(self):
      splits = utils.calculate_variable_split(
          self.X, ["age", "gender"], 121
      )
      vp = utils.calculate_variable_profile(
          self.exp.predict_function,
          self.exp.model,
          self.X.iloc[[0], :],
          splits,
          1,
      )
      self.assertIsInstance(vp, pd.DataFrame)
  
      splits = utils.calculate_variable_split(self.X, ["gender"], 5)
      vp = utils.calculate_variable_profile(
          self.exp.predict_function,
          self.exp.model,
          self.X.iloc[[0], :],
          splits,
          1,
      )
      self.assertIsInstance(vp, pd.DataFrame)
  
      splits = utils.calculate_variable_split(
          self.X, self.X.columns, 15
      )
      vp = utils.calculate_variable_profile(
          self.exp.predict_function,
          self.exp.model,
          self.X.iloc[[0], :],
          splits,
          2,
      )
      self.assertIsInstance(vp, pd.DataFrame)
  
file_path: DALEX/python/dalex/test/test_ceteris_paribus.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
  from dalex.predict_explanations._ceteris_paribus import utils
label_desc: Use image node_id 4 for calling the CeterisParibusTestTitanic obj's underlying member method code with example usage: obj.test_calculate_variable_profile() without return types