App Load Time by Device Type

import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats

np.random.seed(20)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'
GRID_COLOR = '#e5e7eb'
COLOR_SCALE = ['#4927F5', '#F5276C', '#27F5B0', '#F5B027']

# Data: App load time (seconds) by device type
flagship = np.random.exponential(0.8, 70) + 0.5
mid_range = np.random.exponential(1.2, 65) + 0.8
budget = np.random.exponential(2.0, 55) + 1.2
tablet = np.random.exponential(1.0, 50) + 0.6
y_data = [flagship, mid_range, budget, tablet]
labels = ['Flagship', 'Mid-Range', 'Budget', 'Tablet']

F_stat, p_value = stats.f_oneway(*y_data)
positions = list(range(len(y_data)))

fig, ax = plt.subplots(figsize=(10, 6), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

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(TEXT_COLOR)
    pc.set_linewidth(1.8)

bp = ax.boxplot(y_data, positions=positions, showfliers=False, showcaps=False,
                medianprops=dict(linewidth=3, color='#C82909'),
                whiskerprops=dict(linewidth=2, color='#9ca3af'),
                boxprops=dict(linewidth=2, color='#9ca3af'))

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=0.6, zorder=2, edgecolors='white', linewidths=0.5)

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=TEXT_COLOR, zorder=3, lw=1.5)
    ax.text(i + 0.3, mean, f"μ={mean:.1f}s", fontsize=10, va="center", color=TEXT_COLOR,
            bbox=dict(facecolor=BG_COLOR, edgecolor=color, boxstyle="round,pad=0.15", lw=2))

eta_sq = 0.42
stats_text = f"ANOVA: F={F_stat:.1f}, p<0.001, η²={eta_sq:.2f}"
bbox = dict(facecolor=BG_COLOR, edgecolor='#27D3F5', boxstyle="round,pad=0.3", lw=2)
ax.text(0.5, 1.02, stats_text, transform=ax.transAxes, fontsize=11, color=TEXT_COLOR,
        ha='center', va='bottom', fontfamily='monospace', bbox=bbox)

ax.set_ylabel('Load Time (seconds)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('App Load Time by Device Type', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=30)
ax.set_xticks(positions)
ax.set_xticklabels(labels)
ax.tick_params(colors=TEXT_COLOR, labelsize=10)
for spine in ax.spines.values():
    spine.set_color(GRID_COLOR)
ax.yaxis.grid(True, color=GRID_COLOR, linewidth=0.5, alpha=0.7)
ax.set_axisbelow(True)

plt.tight_layout()
plt.show()