Cryptocurrency Market Bubble

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(42)

fig, ax = plt.subplots(figsize=(14, 9), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

cryptos = ['BTC', 'ETH', 'BNB', 'SOL', 'XRP', 'ADA', 'DOGE', 'AVAX']
volatility = np.array([3.2, 4.5, 3.8, 6.2, 4.1, 5.5, 8.2, 5.8])
volume = np.array([28, 15, 2.5, 3.8, 2.2, 0.8, 1.5, 0.9])
market_cap = np.array([850, 380, 85, 60, 35, 18, 22, 14])

colors = ['#F5B027', '#6CF527', '#F5D327', '#27D3F5', '#276CF5', '#4927F5', '#F54927', '#F5276C']
sizes = market_cap * 3

for glow_mult, glow_alpha in [(3.5, 0.02), (2.8, 0.04), (2.2, 0.06), (1.7, 0.10), (1.3, 0.15)]:
    ax.scatter(volatility, volume, s=sizes*glow_mult, c=colors, alpha=glow_alpha, edgecolors='none')

ax.scatter(volatility, volume, s=sizes, c=colors, alpha=0.9, edgecolors='none')
ax.scatter(volatility, volume, s=sizes*0.4, c=colors, alpha=0.4, edgecolors='none')
ax.scatter(volatility - np.sqrt(sizes)*0.008, volume + np.sqrt(sizes)*0.015, s=sizes*0.15, c='white', alpha=0.5, edgecolors='none')

for i, crypto in enumerate(cryptos):
    offset_y = np.sqrt(sizes[i])/2 + 10
    ax.annotate(crypto, (volatility[i], volume[i]), fontsize=13, color='white',
                ha='center', va='bottom', xytext=(0, offset_y), textcoords='offset points', fontweight='bold')

ax.text(0.0, 1.08, 'Cryptocurrency Market', transform=ax.transAxes, fontsize=24, color='white', fontweight='bold')
ax.text(0.0, 1.02, 'Volatility vs Volume · Bubble size = Market Cap', transform=ax.transAxes, fontsize=11, color='#555555')

ax.set_xlabel('30-Day Volatility (%)', fontsize=14, color='#888888', fontweight='500', labelpad=15)
ax.set_ylabel('24h Volume (Billion $)', fontsize=14, color='#888888', fontweight='500', labelpad=15)
ax.tick_params(colors='#555555', labelsize=11, length=0)

for y in [0, 5, 10, 15, 20, 25, 30]:
    ax.axhline(y=y, color='#1a1a2e', linewidth=0.8, zorder=0)
for spine in ax.spines.values():
    spine.set_visible(False)

plt.tight_layout()
plt.show()