Mirror Chart

Desktop vs Mobile Performance

Mirror density comparing response times with SLA threshold and percentile annotations

Output
Desktop vs Mobile Performance
Python
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde

np.random.seed(1968)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'

desktop = np.random.lognormal(2.0, 0.5, 1000)
mobile = np.random.lognormal(2.5, 0.6, 1200)
desktop = desktop[desktop < 50]
mobile = mobile[mobile < 80]

fig, ax = plt.subplots(figsize=(12, 7), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

x = np.linspace(0, 80, 400)

kde_d = gaussian_kde(desktop)
y_d = kde_d(x)
ax.fill_between(x, y_d, alpha=0.3, color='#4927F5')
ax.plot(x, y_d, color='#4927F5', linewidth=2, label='Desktop')

kde_m = gaussian_kde(mobile)
y_m = kde_m(x) * -1
ax.fill_between(x, y_m, alpha=0.3, color='#F5276C')
ax.plot(x, y_m, color='#F5276C', linewidth=2, label='Mobile')

ax.axhline(0, color=TEXT_COLOR, linewidth=1.5)

p50_d = np.percentile(desktop, 50)
p50_m = np.percentile(mobile, 50)
p90_d = np.percentile(desktop, 90)
p90_m = np.percentile(mobile, 90)

ax.axvline(p50_d, color='#4927F5', linestyle='--', linewidth=1.5, alpha=0.7)
ax.axvline(p50_m, color='#F5276C', linestyle='--', linewidth=1.5, alpha=0.7)

core_web_vital = 2.5
ax.axvline(core_web_vital, color='#22c55e', linestyle=':', linewidth=2)
ax.text(core_web_vital + 0.5, 0.08, 'Good (2.5s)', color='#22c55e', fontsize=9, rotation=90)

stats_text = 'Performance (P50/P90):\nDesktop: %.1fs / %.1fs\nMobile: %.1fs / %.1fs' % (p50_d, p90_d, p50_m, p90_m)
ax.text(0.02, 0.98, stats_text.replace('\n', chr(10)), transform=ax.transAxes, fontsize=10,
        color=TEXT_COLOR, verticalalignment='top', fontfamily='monospace',
        bbox=dict(boxstyle='round,pad=0.5', facecolor='#f8fafc', edgecolor='#e5e7eb', alpha=0.9))

pct_good_d = (desktop < core_web_vital).sum() / len(desktop) * 100
pct_good_m = (mobile < core_web_vital).sum() / len(mobile) * 100
ax.text(0.98, 0.98, 'Good CWV: Desktop %.0f%% | Mobile %.0f%%' % (pct_good_d, pct_good_m), 
        transform=ax.transAxes, fontsize=10, color='#6b7280', ha='right', va='top')

ax.set_xlabel('Page Load Time (seconds)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Density', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Web Performance: Desktop vs Mobile', fontsize=14, 
             color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#374151', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#e5e7eb')

ax.legend(loc='upper right', facecolor=BG_COLOR, edgecolor='#e5e7eb', 
          labelcolor=TEXT_COLOR, fontsize=10)
ax.set_xlim(0, 50)
plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Statistical

Did this help you?

Support PyLucid to keep it free & growing

Support