Real Estate Market Analysis

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(963)

# Real estate listings
n_properties = 150

sqft = np.random.uniform(800, 4000, n_properties)
bedrooms = np.random.choice([1, 2, 3, 4, 5], n_properties, p=[0.1, 0.25, 0.35, 0.2, 0.1])
price = sqft * 200 + bedrooms * 50000 + np.random.normal(0, 50000, n_properties)
price = np.clip(price, 100000, 1500000)

# Property type
prop_type = np.random.choice(['Condo', 'House', 'Townhouse'], n_properties, p=[0.3, 0.5, 0.2])
type_colors = {'Condo': '#27D3F5', 'House': '#6CF527', 'Townhouse': '#F5B027'}
colors = [type_colors[t] for t in prop_type]

fig = plt.figure(figsize=(10, 8), facecolor='#ffffff')
ax = fig.add_subplot(111, projection='3d', facecolor='#ffffff')

ax.scatter(sqft, bedrooms, price/1000, c=colors, s=60, 
           alpha=0.7, edgecolors='#374151', linewidths=0.3)

ax.set_xlabel('Square Feet', color='#1f2937', fontsize=10)
ax.set_ylabel('Bedrooms', color='#1f2937', fontsize=10)
ax.set_zlabel('Price ($K)', color='#1f2937', fontsize=10)
ax.set_title('Real Estate Market Analysis', color='#1f2937', fontsize=14, fontweight='bold', pad=20)

ax.tick_params(colors='#6b7280', labelsize=8)
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor('#e5e7eb')
ax.yaxis.pane.set_edgecolor('#e5e7eb')
ax.zaxis.pane.set_edgecolor('#e5e7eb')

ax.view_init(elev=20, azim=45)
plt.tight_layout()
plt.show()