House Price Distribution

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

np.random.seed(106)

downtown = np.random.lognormal(13.2, 0.4, 300)
suburban = np.random.lognormal(12.8, 0.3, 500)
rural = np.random.lognormal(12.2, 0.35, 200)

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

x = np.linspace(100000, 1500000, 500)

areas = [
    (downtown, 'Downtown', '#4927F5'),
    (suburban, 'Suburban', '#27D3F5'),
    (rural, 'Rural', '#6CF527'),
]

for data, label, color in areas:
    kde = stats.gaussian_kde(data)
    y = kde(x)
    median = np.median(data)
    ax.fill_between(x, y, alpha=0.3, color=color)
    ax.plot(x, y, color=color, linewidth=2.5, label=label + ' ($' + str(int(median/1000)) + 'K)')

ax.set_xlabel('Price ($)', fontsize=12, color='#1f2937', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='#1f2937', fontweight='500')
ax.set_title('House Price Distribution by Area', fontsize=16, color='#1f2937', fontweight='bold', pad=15)

ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: '$' + str(int(x/1000)) + 'K'))
ax.tick_params(colors='#374151', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#d1d5db')
ax.legend(loc='upper right', facecolor='#f9fafb', edgecolor='#d1d5db', labelcolor='#374151')
ax.grid(True, alpha=0.3, color='#e5e7eb')
ax.set_xlim(100000, 1500000)

plt.tight_layout()
plt.show()