Daily Commute Time Distribution

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

np.random.seed(57)

# Commute times with different modes
walking = np.random.normal(15, 5, 200)
transit = np.random.normal(45, 15, 400)
driving = np.random.normal(35, 12, 300)
remote = np.zeros(100)  # Work from home
commute = np.concatenate([walking, transit, driving, remote])
commute = commute[commute >= 0]

kde = stats.gaussian_kde(commute[commute > 0])
x = np.linspace(0, 90, 500)
y = kde(x)

fig, ax = plt.subplots(figsize=(12, 6), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Purple gradient
ax.fill_between(x, y, alpha=0.4, color='#4927F5')
ax.plot(x, y, color='#4927F5', linewidth=3)
ax.plot(x, y, color='#4927F5', linewidth=10, alpha=0.15)

# Time zones
ax.axvspan(0, 20, alpha=0.15, color='#6CF527', label='Short (<20min)')
ax.axvspan(20, 45, alpha=0.1, color='#F5B027', label='Average (20-45min)')
ax.axvspan(45, 90, alpha=0.1, color='#F5276C', label='Long (>45min)')

mean_commute = np.mean(commute[commute > 0])
ax.axvline(mean_commute, color='#27D3F5', linestyle='--', linewidth=2, label=f'Mean: {mean_commute:.0f}min')

ax.set_xlabel('Commute Time (minutes)', fontsize=12, color='white', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='white', fontweight='500')
ax.set_title('Daily Commute Time Distribution', fontsize=16, color='white', fontweight='bold', pad=15)

ax.tick_params(colors='white', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#334155')
ax.legend(loc='upper right', facecolor='#1e293b', edgecolor='#334155', labelcolor='white')
ax.grid(True, alpha=0.1, color='white')
ax.set_xlim(0, 90)

plt.tight_layout()
plt.show()