Fintech Transaction Volume

import matplotlib.pyplot as plt
import squarify
import numpy as np

# Transaction volume (in millions)
labels = ['Card Payments', 'Bank Transfers', 'Digital Wallets', 'P2P',
          'International', 'Recurring', 'POS', 'eCommerce', 'Bill Pay']
sizes = [450, 320, 285, 165, 195, 145, 120, 380, 95]
total = sum(sizes)

# CLAUDE.md colors
colors = ['#276CF5', '#6CF527', '#5314E6', '#F5276C', '#27D3F5',
          '#F5B027', '#F54927', '#27F5B0', '#C82909']

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

pct = [s/total*100 for s in sizes]
squarify.plot(sizes=sizes, 
              label=[f'{l}\n${s}M ({p:.1f}%)' for l, s, p in zip(labels, sizes, pct)],
              color=colors, alpha=0.9, ax=ax,
              text_kwargs={'fontsize': 9, 'color': 'white', 'fontweight': 'bold'})

ax.axis('off')
ax.set_title(f'Monthly Transaction Volume - ${total/1000:.2f}B', 
             fontsize=18, color='#1f2937', fontweight='bold', pad=20)

plt.tight_layout()
plt.show()