from sklearn.datasets import load_iris
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import FunctionTransformer
iris = load_iris()
def standardize(X):
    return StandardScaler().fit_transform(X)
pipeline = Pipeline([('standardize', FunctionTransformer(standardize))])
iris_standardized = pipeline.transform(iris.data)
# printing only first 5 rows
for i in range(5):
    print(iris_standardized[i])