Mean target encoding

def test_mean_target_encoding(train, test, target, categorical, alpha=5):
    # Calculate global mean on the train data
    global_mean = train[target].mean()
    
    # Group by the categorical feature and calculate its properties
    train_groups = train.groupby(categorical)
    category_sum = train_groups[target].sum()
    category_size = train_groups.size()
    
    # Calculate smoothed mean target statistics
    train_statistics = (category_sum + global_mean * alpha) / (category_size + ____)
    
    # Apply statistics to the test data and fill new categories
    test_feature = test[categorical].map(train_statistics).fillna(____)
    return test_feature.values