Polar Chart

Processor Core Load Monitor

Multi-core CPU utilization with tech aesthetic

Output
Processor Core Load Monitor
Python
import matplotlib.pyplot as plt
import numpy as np

cores = [f'Core {i}' for i in range(8)]
utilization = [85, 72, 90, 45, 88, 65, 78, 55]

angles = np.linspace(0, 2 * np.pi, len(cores), endpoint=False)
width = 2 * np.pi / len(cores) * 0.8

fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(polar=True), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#6CF527' if u < 60 else '#F5B027' if u < 80 else '#F5276C' for u in utilization]
bars = ax.bar(angles, utilization, width=width, bottom=5, alpha=0.8)
for bar, color in zip(bars, colors):
    bar.set_facecolor(color)
    bar.set_edgecolor('#0a0a0f')
    bar.set_linewidth(2)

ax.set_xticks(angles)
ax.set_xticklabels(cores, fontsize=10, color='white', fontweight='500')
ax.set_ylim(0, 100)
ax.set_yticks([25, 50, 75, 100])
ax.set_yticklabels(['', '', '', ''], fontsize=9)
ax.spines['polar'].set_color('#555555')
ax.grid(color='#555555', linewidth=0.8, alpha=0.7)
ax.set_title('Processor Core Load Monitor', fontsize=16, color='white', fontweight='bold', pad=20, y=1.08)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Part-to-Whole

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