Raincloud Plot
Gaming Network Latency Raincloud
Comparing network latency distributions across gaming server regions.
Output
Python
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats
np.random.seed(789)
# Ping in milliseconds
na_west = np.random.lognormal(2.8, 0.3, 120)
na_east = np.random.lognormal(3.0, 0.35, 115)
eu_west = np.random.lognormal(3.4, 0.4, 100)
asia = np.random.lognormal(3.8, 0.45, 90)
na_west = np.clip(na_west, 8, 50)
na_east = np.clip(na_east, 10, 60)
eu_west = np.clip(eu_west, 15, 90)
asia = np.clip(asia, 25, 150)
F_stat, p_value = stats.f_oneway(na_west, na_east, eu_west, asia)
BG_COLOR = "#0a0a0f"
COLOR_SCALE = ["#6CF527", "#27D3F5", "#F5B027", "#F5276C"]
fig, ax = plt.subplots(figsize=(10, 6), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)
y_data = [na_west, na_east, eu_west, asia]
positions = [0, 1, 2, 3]
labels = ["NA-West", "NA-East", "EU-West", "Asia-Pacific"]
for h in [20, 50, 100]:
ax.axhline(h, color='#333333', ls=(0, (5, 5)), alpha=0.5, zorder=0)
# Quality zones
ax.axhspan(0, 30, alpha=0.08, color='#22c55e')
ax.axhspan(30, 60, alpha=0.05, color='#fbbf24')
ax.axhspan(60, 160, alpha=0.05, color='#ef4444')
ax.text(3.55, 15, "Excellent", color='#22c55e', fontsize=9, va='center')
ax.text(3.55, 45, "Good", color='#fbbf24', fontsize=9, va='center')
ax.text(3.55, 100, "Playable", color='#ef4444', fontsize=9, va='center')
violins = ax.violinplot(y_data, positions=positions, widths=0.5,
bw_method="silverman", showmeans=False,
showmedians=False, showextrema=False)
for pc in violins["bodies"]:
pc.set_facecolor("none")
pc.set_edgecolor("white")
pc.set_linewidth(1.8)
bp = ax.boxplot(y_data, positions=positions, showfliers=False, showcaps=False,
medianprops=dict(linewidth=3, color='#F5D327'),
whiskerprops=dict(linewidth=2, color='#555555'),
boxprops=dict(linewidth=2, color='#555555'))
for i, (y, color) in enumerate(zip(y_data, COLOR_SCALE)):
x_jitter = np.array([i] * len(y)) + stats.t(df=6, scale=0.04).rvs(len(y))
ax.scatter(x_jitter, y, s=50, color=color, alpha=0.5, zorder=2)
means = [y.mean() for y in y_data]
for i, (mean, color) in enumerate(zip(means, COLOR_SCALE)):
ax.scatter(i, mean, s=180, color='#C82909', zorder=5, edgecolors='white', linewidths=2)
ax.plot([i, i + 0.28], [mean, mean], ls="dashdot", color="white", zorder=3, lw=1.5)
ax.text(i + 0.3, mean, f"μ={mean:.0f}ms", fontsize=10, va="center", color='white',
bbox=dict(facecolor=BG_COLOR, edgecolor=color, boxstyle="round,pad=0.15", lw=2))
# Comparison brackets
tick = 5
ax.plot([0, 0, 3, 3], [145-tick, 145, 145, 145-tick], c="white", lw=1.5)
ax.text(1.5, 148, "p < 0.001, Tukey HSD", fontsize=10, va="bottom", ha="center", color='#F5D327')
ax.spines["right"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.spines["left"].set_color('#444444')
ax.spines["bottom"].set_color('#444444')
ax.tick_params(colors='#888888', length=0)
xlabels = [f"{l}\n(n={len(y_data[i])})" for i, l in enumerate(labels)]
ax.set_xticks(positions)
ax.set_xticklabels(xlabels, size=11, color='white')
ax.set_ylabel("Ping Latency (ms)", size=14, color='white', fontweight='bold')
ax.set_title("Gaming Network Latency by Region", fontsize=14, color="white", fontweight="bold", pad=20)
ax.set_ylim(0, 165)
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
Statistical
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