Startup Investment Evaluation

import matplotlib.pyplot as plt
import numpy as np

# Startup evaluation criteria
categories = ['Market Size', 'Team Quality', 'Traction', 'Technology Moat',
              'Unit Economics', 'Competitive Position', 'Scalability', 'Exit Potential']
              
fintech_a = [92, 88, 75, 85, 70, 78, 90, 88]
saas_b = [75, 92, 88, 90, 85, 82, 95, 80]
biotech_c = [85, 95, 55, 98, 45, 90, 70, 95]
ecom_d = [88, 78, 92, 65, 80, 60, 88, 75]

N = len(categories)
angles = np.linspace(0, 2 * np.pi, N, endpoint=False).tolist()
angles += angles[:1]

fintech_a += fintech_a[:1]
saas_b += saas_b[:1]
biotech_c += biotech_c[:1]
ecom_d += ecom_d[:1]

fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(polar=True), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

ax.plot(angles, fintech_a, 'o-', linewidth=2.5, color='#27D3F5', label='FinTech Startup', markersize=7)
ax.fill(angles, fintech_a, alpha=0.15, color='#27D3F5')

ax.plot(angles, saas_b, 's-', linewidth=2.5, color='#F5276C', label='SaaS Platform', markersize=7)
ax.fill(angles, saas_b, alpha=0.15, color='#F5276C')

ax.plot(angles, biotech_c, '^-', linewidth=2.5, color='#6CF527', label='BioTech Company', markersize=7)
ax.fill(angles, biotech_c, alpha=0.15, color='#6CF527')

ax.plot(angles, ecom_d, 'D-', linewidth=2.5, color='#F5B027', label='E-Commerce', markersize=7)
ax.fill(angles, ecom_d, alpha=0.15, color='#F5B027')

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('Startup Investment Analysis', 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()