Smartwatch Feature Comparison

import matplotlib.pyplot as plt
import numpy as np

# Smartwatch features
categories = ['Fitness Tracking', 'Battery Life', 'Health Sensors', 'Display',
              'App Ecosystem', 'Build Quality', 'Value', 'Notifications']
              
apple_watch = [92, 65, 95, 95, 98, 95, 70, 98]
galaxy_watch = [90, 85, 90, 92, 85, 90, 85, 92]
garmin = [98, 98, 88, 75, 70, 92, 80, 75]
fitbit = [95, 90, 85, 80, 75, 78, 90, 85]

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

apple_watch += apple_watch[:1]
galaxy_watch += galaxy_watch[:1]
garmin += garmin[:1]
fitbit += fitbit[:1]

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

ax.plot(angles, apple_watch, 'o-', linewidth=2.5, color='#F5276C', label='Apple Watch', markersize=7)
ax.fill(angles, apple_watch, alpha=0.15, color='#F5276C')

ax.plot(angles, galaxy_watch, 's-', linewidth=2.5, color='#5314E6', label='Galaxy Watch', markersize=7)
ax.fill(angles, galaxy_watch, alpha=0.15, color='#5314E6')

ax.plot(angles, garmin, '^-', linewidth=2.5, color='#F5B027', label='Garmin', markersize=7)
ax.fill(angles, garmin, alpha=0.15, color='#F5B027')

ax.plot(angles, fitbit, 'D-', linewidth=2.5, color='#27D3F5', label='Fitbit', markersize=7)
ax.fill(angles, fitbit, alpha=0.15, color='#27D3F5')

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('Smartwatch Feature Comparison', 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()