from sklearn.datasets import load_iris
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler
import pandas as pd

# Load the Iris dataset
iris = load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)

# Define the transformer
ct = ColumnTransformer(
    transformers=[
        ('standard', StandardScaler(), ['petal length (cm)', 'petal width (cm)']),
        ('pass', 'passthrough', ['sepal length (cm)', 'sepal width (cm)'])
    ])

# Fit and transform the transformer on the dataset
transformed_data = ct.fit_transform(df)

# Display the transformed data
print(transformed_data)