Chip Fabrication Correlogram

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

np.random.seed(333)

n = 160
node = np.random.choice(['7nm', '14nm', '28nm'], n)
data = {
    'Yield (%)': np.where(node == '28nm', np.random.normal(92, 3, n),
                         np.where(node == '14nm', np.random.normal(85, 5, n), np.random.normal(75, 8, n))),
    'Defects/cm2': np.where(node == '7nm', np.random.normal(0.15, 0.05, n),
                           np.where(node == '14nm', np.random.normal(0.08, 0.03, n), np.random.normal(0.04, 0.02, n))),
    'Power (W)': np.where(node == '7nm', np.random.normal(5, 1.5, n),
                         np.where(node == '14nm', np.random.normal(12, 3, n), np.random.normal(25, 5, n))),
    'Clock (GHz)': np.where(node == '7nm', np.random.normal(4, 0.5, n),
                           np.where(node == '14nm', np.random.normal(3.5, 0.4, n), np.random.normal(3, 0.3, n))),
    'Node': node
}
df = pd.DataFrame(data)

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

palette = {'7nm': '#5314E6', '14nm': '#27D3F5', '28nm': '#6CF527'}

g = sns.pairplot(
    df,
    hue='Node',
    palette=palette,
    height=2,
    kind='scatter',
    diag_kind='hist',
    markers=['D', 'o', 's'],
    plot_kws={'alpha': 0.75, 's': 55, 'edgecolor': 'white', 'linewidths': 0.6},
    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('Fab Process Comparison', fontsize=14, fontweight='bold', color='#1a1a1a', y=1.02)

plt.tight_layout()
plt.show()