from sklearn.svm import SVC
from sklearn.preprocessing import StandardScaler
from sklearn.impute import SimpleImputer
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline

X, y = make_classification(random_state=0)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)

# Create and train pipeline
pipe = Pipeline([('imputer', SimpleImputer(strategy="median")), 
                 ('scaler', StandardScaler()), 
                 ('svc', SVC())])
pipe.fit(X_train, y_train)

# Evaluate the pipeline
>>> pipe.score(X_test, y_test)
0.88