Wine Quality Features

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(123)

n = 160
wine_type = np.random.choice(['Red', 'White', 'Rosé'], n)
data = {
    'Alcohol (%)': np.where(wine_type == 'Red', np.random.normal(13, 0.8, n),
                           np.where(wine_type == 'White', np.random.normal(11, 0.7, n), np.random.normal(12, 0.6, n))),
    'Acidity': np.where(wine_type == 'White', np.random.normal(6.5, 0.8, n),
                       np.where(wine_type == 'Red', np.random.normal(5.5, 0.6, n), np.random.normal(6, 0.5, n))),
    'Residual Sugar': np.where(wine_type == 'White', np.random.normal(6, 3, n),
                              np.where(wine_type == 'Rosé', np.random.normal(8, 4, n), np.random.normal(2.5, 1, n))),
    'pH': np.random.normal(3.3, 0.15, n),
    'Type': wine_type
}
df = pd.DataFrame(data)

sns.set_style("whitegrid", {'axes.facecolor': '#ffffff', 'figure.facecolor': '#ffffff', 'grid.color': '#eeeeee'})

palette = {'Red': '#9C2007', 'White': '#F5D327', 'Rosé': '#F527B0'}

g = sns.pairplot(
    df,
    hue='Type',
    palette=palette,
    height=2,
    kind='reg',
    diag_kind='hist',
    markers=['o', '^', 's'],
    plot_kws={'scatter_kws': {'alpha': 0.65, 's': 50, 'edgecolor': 'white', 'linewidths': 0.6}, 'line_kws': {'linewidth': 2}},
    diag_kws={'alpha': 0.6, 'edgecolor': 'white', 'linewidth': 0.5}
)

g.fig.set_facecolor('#ffffff')
for ax in g.axes.flat:
    if ax:
        ax.set_facecolor('#ffffff')
        for spine in ax.spines.values():
            spine.set_color('#dddddd')
        ax.tick_params(colors='#666666')
        ax.xaxis.label.set_color('#333333')
        ax.yaxis.label.set_color('#333333')

g.fig.suptitle('Wine Chemical Composition', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)

plt.tight_layout()
plt.show()