import pandas as pd
from sklearn.datasets import load_wine

data = load_wine()
wine = pd.DataFrame(data.data, columns=data.feature_names)

X = wine[['alcohol', 'total_phenols']]

from sklearn.preprocessing import StandardScaler
scale = StandardScaler()
scale.fit(X)

print(scale.mean_)
print(scale.scale_)

X_scaled = scale.transform(X)
print(X_scaled.mean(axis=0))
print(X_scaled.std(axis=0))
