code: def setUp(self):
      data = dx.datasets.load_titanic()
      data.loc[:, "survived"] = LabelEncoder().fit_transform(
          data.survived
      )
  
      self.X = data.loc[:, ["age", "fare", "sibsp", "parch"]]
      self.y = data.survived
  
      clf = RandomForestClassifier(n_estimators=100, random_state=123)
      clf.fit(self.X, self.y)
  
      self.exp = dx.Explainer(clf, self.X, self.y, verbose=False)
  
file_path: DALEX/python/dalex/test/test_shap_wrapper.py
imports: import unittest
  from sklearn.compose import ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.neural_network import MLPRegressor
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
  from sklearn.ensemble import RandomForestClassifier
  from dalex.wrappers import ShapWrapper
  import dalex
label_desc: Use image node_id 1 for calling the TestShapWrapperRandomForestClassifierTitanicNumericalDataset obj's underlying member method code with example usage: obj.setUp() without return types