House Price by Neighborhood

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import ptitprince as pt

np.random.seed(208)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'
COLORS = ['#6CF527', '#F5B027', '#F5276C', '#4927F5']

hoods = ['Downtown', 'Suburbs', 'Waterfront', 'Historic']
data = pd.DataFrame({
    'Price': np.concatenate([
        np.random.lognormal(13.2, 0.4, 70),
        np.random.lognormal(12.8, 0.35, 100),
        np.random.lognormal(13.5, 0.5, 50),
        np.random.lognormal(13.0, 0.45, 60)
    ]),
    'Area': ['Downtown']*70 + ['Suburbs']*100 + ['Waterfront']*50 + ['Historic']*60
})
data['Price'] = data['Price'] / 1000  # Convert to thousands

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

pt.RainCloud(x='Area', y='Price', data=data, palette=COLORS,
             bw=.2, width_viol=.6, ax=ax, orient='h', alpha=.65,
             dodge=True, pointplot=False, move=.2)

ax.set_xlabel('Price ($K)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Neighborhood', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('House Prices by Neighborhood', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#374151', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#e5e7eb')

plt.tight_layout()
plt.show()