Commute Time by City

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

np.random.seed(42)
cities = ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Phoenix', 'Seattle']
commute_means = [42, 55, 35, 32, 28, 30]
commute_stds = [18, 22, 14, 12, 10, 12]

fig, ax = plt.subplots(figsize=(12, 8), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#F5276C', '#F54927', '#F5B027', '#6CF527', '#27D3F5', '#4927F5']

x = np.linspace(0, 120, 200)
overlap = 2.2

for i, (city, mean, std, color) in enumerate(zip(cities, commute_means, commute_stds, colors)):
    data = np.random.gamma(mean/5, 5, 1000)
    kde = stats.gaussian_kde(data)
    y = kde(x) * 10
    y_offset = i * overlap
    
    ax.fill_between(x, y_offset, y + y_offset, alpha=0.85, color=color, edgecolor='white', linewidth=0.8)
    ax.text(-5, y_offset + 0.3, city, fontsize=10, color='white', va='center', ha='right', fontweight='500')

ax.set_xlim(-30, 120)
ax.set_ylim(-0.5, len(cities) * overlap + 2)
ax.set_xlabel('Commute Time (minutes)', color='white', fontsize=11, fontweight='500')
ax.set_title('Commute Time Distribution by City', color='white', fontsize=14, fontweight='bold', pad=20)
ax.tick_params(colors='#888888', labelsize=9)
ax.set_yticks([])
for spine in ax.spines.values():
    spine.set_visible(False)
ax.spines['bottom'].set_visible(True)
ax.spines['bottom'].set_color('#333333')

plt.tight_layout()
plt.show()