Radar Chart
Cryptocurrency Investment Profile
Dark-themed radar chart comparing cryptocurrencies across market cap, volatility, adoption, technology, and regulatory compliance.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
# Crypto metrics
categories = ['Market Cap', 'Liquidity', 'Technology', 'Adoption',
'Regulatory Status', 'Volatility Risk', 'Staking Yield', 'DeFi Integration']
bitcoin = [98, 95, 70, 95, 85, 75, 35, 65]
ethereum = [90, 92, 95, 90, 80, 80, 75, 98]
solana = [70, 75, 88, 70, 65, 90, 80, 85]
cardano = [65, 65, 85, 60, 75, 70, 85, 70]
N = len(categories)
angles = np.linspace(0, 2 * np.pi, N, endpoint=False).tolist()
angles += angles[:1]
bitcoin += bitcoin[:1]
ethereum += ethereum[:1]
solana += solana[:1]
cardano += cardano[:1]
fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(polar=True), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')
ax.plot(angles, bitcoin, 'o-', linewidth=2.5, color='#F5B027', label='Bitcoin', markersize=7)
ax.fill(angles, bitcoin, alpha=0.2, color='#F5B027')
ax.plot(angles, ethereum, 's-', linewidth=2.5, color='#5314E6', label='Ethereum', markersize=7)
ax.fill(angles, ethereum, alpha=0.2, color='#5314E6')
ax.plot(angles, solana, '^-', linewidth=2.5, color='#27F5B0', label='Solana', markersize=7)
ax.fill(angles, solana, alpha=0.2, color='#27F5B0')
ax.plot(angles, cardano, 'D-', linewidth=2.5, color='#276CF5', label='Cardano', markersize=7)
ax.fill(angles, cardano, alpha=0.2, color='#276CF5')
ax.set_xticks(angles[:-1])
ax.set_xticklabels(categories, fontsize=10, color='#e2e8f0', fontweight='500')
ax.set_ylim(0, 100)
ax.yaxis.grid(True, color='#1e293b', linestyle='-', linewidth=0.8)
ax.xaxis.grid(True, color='#334155', linestyle='-', linewidth=0.5)
ax.spines['polar'].set_color('#334155')
ax.tick_params(axis='y', colors='#94a3b8')
ax.set_title('Cryptocurrency Investment Profiles', fontsize=16, color='#f8fafc',
fontweight='bold', pad=25)
ax.legend(loc='upper right', bbox_to_anchor=(1.2, 1.1), fontsize=10,
frameon=True, facecolor='#1e293b', edgecolor='#334155', labelcolor='#e2e8f0')
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
Polar Charts
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