Rental Price Distribution KDE

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

np.random.seed(1010)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'
GRID_COLOR = '#e5e7eb'

# Monthly rent ($)
downtown = np.random.lognormal(7.8, 0.3, 400)
midtown = np.random.lognormal(7.5, 0.35, 400)
suburbs = np.random.lognormal(7.2, 0.4, 400)

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

x_range = np.linspace(1000, 5000, 500)

for data, color, label in [(downtown, '#C82909', 'Downtown'), 
                            (midtown, '#4927F5', 'Midtown'),
                            (suburbs, '#6CF527', 'Suburbs')]:
    data_clipped = data[(data > 1000) & (data < 5000)]
    kde = gaussian_kde(data_clipped)
    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.set_xlabel('Monthly Rent ($)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Density', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Rental Price Distribution by Zone', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)
ax.set_xlim(1000, 5000)

ax.tick_params(colors=TEXT_COLOR, labelsize=10)
for spine in ax.spines.values():
    spine.set_color(GRID_COLOR)
ax.yaxis.grid(True, color=GRID_COLOR, linewidth=0.5, alpha=0.7)
ax.legend(facecolor=BG_COLOR, edgecolor=GRID_COLOR, labelcolor=TEXT_COLOR, fontsize=10)

plt.tight_layout()
plt.show()