Stream Graph

Urban Transportation Mode Stream

Stream graph showing urban transportation mode preferences throughout the day.

Output
Urban Transportation Mode Stream
Python
import matplotlib.pyplot as plt
import numpy as np

COLORS = {
    'layers': ['#EF4444', '#3B82F6', '#10B981', '#F59E0B', '#8B5CF6'],
    'background': '#ffffff',
    'text': '#1f2937',
    'grid': '#e5e7eb',
}

np.random.seed(3838)
hours = np.arange(0, 24)

car = 30 + 20 * np.exp(-((hours - 8)**2) / 8) + 18 * np.exp(-((hours - 17)**2) / 8) + np.random.normal(0, 2, 24)
public_transit = 15 + 25 * np.exp(-((hours - 8)**2) / 6) + 22 * np.exp(-((hours - 18)**2) / 6) + np.random.normal(0, 2, 24)
bike = 8 + 12 * np.exp(-((hours - 8)**2) / 10) + 10 * np.exp(-((hours - 17)**2) / 10) + np.random.normal(0, 1, 24)
rideshare = 5 + 8 * np.exp(-((hours - 22)**2) / 15) + 5 * np.exp(-((hours - 8)**2) / 10) + np.random.normal(0, 1, 24)
walk = 10 + 8 * np.exp(-((hours - 12)**2) / 15) + np.random.normal(0, 1, 24)

data = [np.clip(d, 1, None) for d in [car, public_transit, bike, rideshare, walk]]

fig, ax = plt.subplots(figsize=(14, 6), facecolor=COLORS['background'])
ax.set_facecolor(COLORS['background'])

ax.stackplot(hours, *data, colors=COLORS['layers'], alpha=0.85, baseline='sym',
             labels=['Private Car', 'Public Transit', 'Bicycle', 'Rideshare', 'Walking'])

ax.axhline(0, color=COLORS['grid'], linewidth=0.5)
ax.set_xlim(0, 23)
ax.set_xticks([0, 6, 12, 18, 24])
ax.set_xticklabels(['12 AM', '6 AM', '12 PM', '6 PM', '12 AM'])

ax.set_title('Urban Transportation by Hour', color=COLORS['text'], fontsize=14, fontweight='bold', pad=15)
ax.set_xlabel('Hour', color=COLORS['text'], fontsize=11)
ax.set_ylabel('Trips (thousands)', color=COLORS['text'], fontsize=11)

ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12), frameon=False, fontsize=9, ncol=5)

for spine in ax.spines.values():
    spine.set_color(COLORS['grid'])
ax.tick_params(colors=COLORS['text'], labelsize=9)

plt.tight_layout()
plt.subplots_adjust(bottom=0.18)
plt.show()
Library

Matplotlib

Category

Time Series

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