Stock Return Distribution KDE

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

np.random.seed(123)
BG_COLOR = '#0d1117'
TEXT_COLOR = 'white'

# Daily returns (%)
tech = np.random.normal(0.08, 1.8, 500)
finance = np.random.normal(0.05, 1.2, 500)
healthcare = np.random.normal(0.06, 0.9, 500)

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

x_range = np.linspace(-6, 6, 500)

for data, color, label in [(tech, '#4927F5', 'Technology'), 
                            (finance, '#F5B027', 'Finance'),
                            (healthcare, '#27F5B0', 'Healthcare')]:
    kde = gaussian_kde(data)
    density = kde(x_range)
    ax.plot(x_range, density, color=color, linewidth=2.5, label=label)
    ax.fill_between(x_range, density, alpha=0.25, color=color)

ax.axvline(0, color='#ef4444', linestyle='--', alpha=0.7, label='Zero Return')

ax.set_xlabel('Daily Return (%)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Density', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Stock Return Distribution by Sector', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#888888', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#333333')
ax.legend(facecolor=BG_COLOR, edgecolor='#333333', labelcolor=TEXT_COLOR, fontsize=10)

plt.tight_layout()
plt.show()