Tech Giants Market Analysis

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')

companies = ['Apple', 'Microsoft', 'Google', 'Amazon', 'Meta', 'Tesla', 'Netflix', 'Adobe']
revenue = np.array([394, 211, 307, 574, 134, 96, 33, 19])
profit_margin = np.array([25, 36, 26, 4, 20, 15, 18, 35])
employees = np.array([164, 221, 190, 1540, 86, 128, 13, 29])

colors = ['#F5276C', '#27D3F5', '#6CF527', '#F5B027', '#4927F5', '#F54927', '#27F5B0', '#F527B0']
sizes = employees * 3

# Glow layers
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(revenue, profit_margin, s=sizes*glow_mult, c=colors, alpha=glow_alpha, edgecolors='none')

ax.scatter(revenue, profit_margin, s=sizes, c=colors, alpha=0.9, edgecolors='none')
ax.scatter(revenue, profit_margin, s=sizes*0.4, c=colors, alpha=0.4, edgecolors='none')

# Specular highlight
ax.scatter(revenue - np.sqrt(sizes)*0.5, profit_margin + np.sqrt(sizes)*0.08, 
           s=sizes*0.15, c='white', alpha=0.5, edgecolors='none')

for i, company in enumerate(companies):
    offset_y = np.sqrt(sizes[i])/2 + 15
    ax.annotate(company, (revenue[i], profit_margin[i]), fontsize=12, color='white',
                ha='center', va='bottom', xytext=(0, offset_y), textcoords='offset points', fontweight='bold')

ax.text(0.0, 1.08, 'Tech Giants Analysis', transform=ax.transAxes, fontsize=24, color='white', fontweight='bold')
ax.text(0.0, 1.02, 'Revenue vs Profit Margin · Bubble size = Employees', transform=ax.transAxes, fontsize=11, color='#555555')

ax.set_xlabel('Revenue (Billion $)', fontsize=14, color='#888888', fontweight='500', labelpad=15)
ax.set_ylabel('Profit Margin (%)', fontsize=14, color='#888888', fontweight='500', labelpad=15)
ax.tick_params(colors='#555555', labelsize=11, length=0)
ax.set_xlim(-40, 680)
ax.set_ylim(-5, 45)

for y in [0, 10, 20, 30, 40]:
    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()