from sklearn.compose import ColumnTransformer
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import load_iris

# Load data
iris = load_iris()
X, y = iris.data, iris.target

# Load data and split into train and test sets
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42)

# Define transformers for preprocessing
preprocessor = ColumnTransformer(
    transformers=[
        ('num', StandardScaler(), [0, 1, 2, 3])
    ])

# Define classifier
clf = Pipeline(steps=[('preprocessor', preprocessor),
                        ('classifier', LogisticRegression())])

# Fit model
clf.fit(X_train, y_train)