Electric Vehicle Adoption Stream

import matplotlib.pyplot as plt
import numpy as np

COLORS = {
    'layers': ['#E31937', '#0066B1', '#CC0000', '#000000', '#00A3E0'],
    'background': '#ffffff',
    'text': '#1f2937',
    'grid': '#e5e7eb',
}

np.random.seed(1111)
years = np.arange(2015, 2025)
n = len(years)

# EV manufacturers
tesla = 10 + 15 * (years - 2015) + np.random.normal(0, 3, n)
byd = 5 + 12 * (years - 2018) * (years >= 2018) + np.random.normal(0, 2, n)
vw = 2 + 8 * (years - 2020) * (years >= 2020) + np.random.normal(0, 1, n)
gm = 3 + 5 * (years - 2019) * (years >= 2019) + np.random.normal(0, 1, n)
hyundai = 2 + 6 * (years - 2019) * (years >= 2019) + np.random.normal(0, 1, n)

data = [np.clip(d, 0.5, None) for d in [tesla, byd, vw, gm, hyundai]]

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

ax.stackplot(years, *data, colors=COLORS['layers'], alpha=0.85, baseline='sym',
             labels=['Tesla', 'BYD', 'VW Group', 'GM', 'Hyundai/Kia'])

ax.axhline(0, color=COLORS['grid'], linewidth=0.5)
ax.set_xlim(2015, 2024)

ax.set_title('Electric Vehicle Sales by Manufacturer', color=COLORS['text'], fontsize=14, fontweight='bold', pad=15)
ax.set_xlabel('Year', color=COLORS['text'], fontsize=11)
ax.set_ylabel('Sales (Millions)', color=COLORS['text'], fontsize=11)

# Legend outside plot area
ax.legend(loc='upper left', bbox_to_anchor=(0, -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()