input: Write a python function to preprocess data with StandardScaler and train a logistic regression model for multiclass classification using sklearn.
  assert preprocess_and_train_model(X, y).score(X_scaled, y) > 0.8
output: def preprocess_and_train_model(X, y):
      from sklearn.preprocessing import StandardScaler
      from sklearn.linear_model import LogisticRegression
      from sklearn.pipeline import make_pipeline
      
      scaler = StandardScaler()
      model = LogisticRegression(multi_class='ovr', max_iter=1000)
      pipeline = make_pipeline(scaler, model)
      
      pipeline.fit(X, y)
      return pipeline