Metabolic Health Correlogram

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

np.random.seed(321)

n = 170
status = np.random.choice(['Normal', 'Prediabetic', 'Diabetic'], n)
data = {
    'Glucose': np.where(status == 'Normal', np.random.normal(90, 10, n),
                       np.where(status == 'Prediabetic', np.random.normal(115, 12, n), np.random.normal(150, 25, n))),
    'BMI': np.where(status == 'Normal', np.random.normal(23, 3, n),
                   np.where(status == 'Prediabetic', np.random.normal(28, 4, n), np.random.normal(32, 5, n))),
    'HbA1c (%)': np.where(status == 'Normal', np.random.normal(5.2, 0.3, n),
                         np.where(status == 'Prediabetic', np.random.normal(6, 0.3, n), np.random.normal(7.5, 1, n))),
    'Insulin': np.where(status == 'Normal', np.random.normal(8, 3, n),
                       np.where(status == 'Prediabetic', np.random.normal(15, 5, n), np.random.normal(25, 10, n))),
    'Status': status
}
df = pd.DataFrame(data)

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

palette = {'Normal': '#6CF527', 'Prediabetic': '#F5B027', 'Diabetic': '#F5276C'}

g = sns.pairplot(
    df,
    hue='Status',
    palette=palette,
    height=2,
    kind='reg',
    diag_kind='kde',
    markers=['o', 's', 'D'],
    plot_kws={'scatter_kws': {'alpha': 0.65, 's': 50, 'edgecolor': 'white', 'linewidths': 0.6}, 'line_kws': {'linewidth': 2}},
    diag_kws={'alpha': 0.5, 'linewidth': 2.5, 'fill': True}
)

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('Metabolic Health Indicators', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)

plt.tight_layout()
plt.show()