CPU GPU Utilization

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(444)
cpu = np.random.beta(2, 5, 6000) * 100
gpu = cpu * 0.6 + np.random.beta(2, 3, 6000) * 40

fig, ax = plt.subplots(figsize=(10, 8), facecolor='#0c0c0c')
ax.set_facecolor('#0c0c0c')

colors = ['#0c0c0c', '#1a1a2e', '#16213e', '#1a4a6e', '#1e7a9e', '#22aace', '#44ccff', '#88ddff']
cmap = LinearSegmentedColormap.from_list('cyan', colors, N=256)

hb = ax.hexbin(cpu, gpu, gridsize=30, cmap=cmap, mincnt=1, edgecolors='none')

cbar = plt.colorbar(hb, ax=ax, pad=0.02, shrink=0.8)
cbar.ax.set_facecolor('#0c0c0c')
cbar.outline.set_edgecolor('#1a4a6e')
cbar.ax.tick_params(colors='#44ccff', labelsize=9)
cbar.set_label('Samples', color='#44ccff', fontsize=10)

ax.set_xlabel('CPU Usage (%)', color='#44ccff', fontsize=11)
ax.set_ylabel('GPU Usage (%)', color='#44ccff', fontsize=11)
ax.tick_params(colors='#44ccff', labelsize=10)
ax.set_xlim(0, 100)
ax.set_ylim(0, 100)
for spine in ax.spines.values():
    spine.set_visible(False)

plt.tight_layout()