code: def test_single_variable_profile(self):
      splits = utils.calculate_variable_split(
          self.X, self.X.columns, 101
      )
      new_data_age = utils.single_variable_profile(
          self.exp.predict_function,
          self.exp.model,
          self.X.iloc[[0], :],
          "age",
          splits["age"],
      )
  
      new_data_embarked = utils.single_variable_profile(
          self.exp.predict_function,
          self.exp.model,
          self.X.iloc[[0], :],
          "embarked",
          splits["embarked"],
      )
  
      self.assertIsInstance(new_data_age, (pd.DataFrame,))
      self.assertIsInstance(new_data_embarked, (pd.DataFrame,))
  
      self.assertLessEqual(new_data_age.shape[0], 101)
      self.assertLessEqual(new_data_embarked.shape[0], 101)
  
      self.assertTrue(
          np.isin(
              np.array(["_yhat_", "_vname_", "_ids_"]),
              new_data_age.columns,
          ).all()
      )
  
      self.assertTrue(
          np.isin(
              np.array(["_yhat_", "_vname_", "_ids_"]),
              new_data_embarked.columns,
          ).all()
      )
  
      self.assertTrue(
          pd.api.types.is_numeric_dtype(new_data_age.loc[:, "age"])
      )
  
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 3 for calling the CeterisParibusTestTitanic obj's underlying member method code with example usage: obj.test_single_variable_profile() without return types