decomp = PCA(n_components=2)

white_wines_scaled = decomp.fit_transform(X_w_test)

_, axs = plt.subplots(ncols=2, figsize=(20, 10))
first_ax, second_ax = axs

first_ax.scatter(white_wines_scaled[:, 0], white_wines_scaled[:, 1], c=y_w_test, cmap='twilight_shifted')
first_ax.grid(True)
first_ax.set_title("Исходные значения качества для белых вин")

second_ax.scatter(white_wines_scaled[:, 0], white_wines_scaled[:, 1], c=y_w_prediction_test, cmap='twilight_shifted')
second_ax.grid(True)
second_ax.set_title("Предсказнные значения качества для белых вин")