Customer Age by Product Category

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

np.random.seed(42)
products = ['Electronics', 'Fashion', 'Home & Garden', 'Sports', 'Books', 'Toys']
age_means = [32, 28, 42, 35, 38, 35]
age_stds = [10, 8, 12, 11, 14, 8]

fig, ax = plt.subplots(figsize=(12, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

colors = ['#4927F5', '#276CF5', '#27D3F5', '#6CF527', '#F5B027', '#F5276C']

x = np.linspace(15, 70, 200)
overlap = 2.2

for i, (product, mean, std, color) in enumerate(zip(products, age_means, age_stds, colors)):
    data = np.random.normal(mean, std, 1000)
    data = np.clip(data, 18, None)
    kde = stats.gaussian_kde(data)
    y = kde(x) * 8
    y_offset = i * overlap
    
    ax.fill_between(x, y_offset, y + y_offset, alpha=0.85, color=color, edgecolor='#374151', linewidth=0.8)
    ax.text(12, y_offset + 0.3, product, fontsize=10, color='#1f2937', va='center', ha='right', fontweight='500')

ax.set_xlim(-5, 70)
ax.set_ylim(-0.5, len(products) * overlap + 2)
ax.set_xlabel('Customer Age', color='#1f2937', fontsize=11, fontweight='500')
ax.set_title('Customer Age Distribution by Product Category', color='#1f2937', fontsize=14, fontweight='bold', pad=20)
ax.tick_params(colors='#374151', labelsize=9)
ax.set_yticks([])
for spine in ax.spines.values():
    spine.set_visible(False)
ax.spines['bottom'].set_visible(True)
ax.spines['bottom'].set_color('#e5e7eb')

plt.tight_layout()
plt.show()