Real Estate Price Distribution

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

# Real estate data
np.random.seed(42)
n_properties = 10000

# Square footage and price
sqft = np.random.lognormal(7, 0.4, n_properties)
sqft = np.clip(sqft, 500, 5000)

price_per_sqft = np.random.normal(350, 80, n_properties)
price = sqft * price_per_sqft / 1000  # in thousands
price = np.clip(price, 100, 2000)

# Modern light theme with warm tones
fig, ax = plt.subplots(figsize=(10, 8), facecolor='#ffffff')
ax.set_facecolor('#fffbf7')

# Warm coral colormap
colors = ['#fffbf7', '#fff0e6', '#ffe0cc', '#ffc9a8', '#ffb085', 
          '#ff9666', '#f47c4a', '#e05a30', '#c43d1a', '#9a2508']
cmap = LinearSegmentedColormap.from_list('warm_coral', colors, N=256)

# Hexbin plot
hb = ax.hexbin(sqft, price, gridsize=40, cmap=cmap, mincnt=1,
               edgecolors='white', linewidths=0.4)

# Trend line
z = np.polyfit(sqft, price, 1)
p = np.poly1d(z)
x_line = np.linspace(500, 5000, 100)
ax.plot(x_line, p(x_line), '-', color='#c43d1a', linewidth=2.5, alpha=0.8, label='Market Trend')

# Styled colorbar
cbar = plt.colorbar(hb, ax=ax, pad=0.02, shrink=0.85)
cbar.set_label('Property Count', fontsize=11, color='#44403c', labelpad=10)
cbar.ax.yaxis.set_tick_params(color='#78716c')
cbar.outline.set_edgecolor('#e7e5e4')
plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='#78716c', fontsize=9)

# Labels
ax.set_xlabel('Square Footage', fontsize=12, color='#44403c', fontweight='600', labelpad=12)
ax.set_ylabel('Price ($K)', fontsize=12, color='#44403c', fontweight='600', labelpad=12)
ax.set_title('Real Estate Price Distribution', fontsize=16, color='#1c1917', 
             fontweight='700', pad=20)

# Clean axes
ax.tick_params(colors='#78716c', labelsize=10, length=0)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color('#e7e5e4')
ax.spines['bottom'].set_color('#e7e5e4')

ax.legend(loc='upper left', fontsize=10, frameon=True, facecolor='white', 
          edgecolor='#e7e5e4', labelcolor='#44403c')
ax.grid(True, alpha=0.3, color='#e7e5e4', linestyle='-', linewidth=0.5)
ax.set_axisbelow(True)

plt.tight_layout()
plt.show()