Research Impact Bubble Chart

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')

institutions = ['MIT', 'Stanford', 'Harvard', 'Cambridge', 'Caltech', 'Oxford', 'ETH Zurich', 'Berkeley']
publications = np.array([45, 42, 55, 38, 18, 40, 25, 38])
h_index = np.array([420, 410, 450, 380, 350, 390, 320, 360])
funding = np.array([4.2, 3.8, 5.5, 2.8, 2.2, 3.2, 1.8, 2.9])

colors = ['#F54927', '#6CF527', '#C82909', '#27D3F5', '#F5B027', '#276CF5', '#F5276C', '#27F5B0']
sizes = funding * 250

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(publications, h_index, s=sizes*glow_mult, c=colors, alpha=glow_alpha, edgecolors='none')

ax.scatter(publications, h_index, s=sizes, c=colors, alpha=0.9, edgecolors='none')
ax.scatter(publications, h_index, s=sizes*0.4, c=colors, alpha=0.4, edgecolors='none')
ax.scatter(publications - np.sqrt(sizes)*0.08, h_index + np.sqrt(sizes)*0.3, s=sizes*0.15, c='white', alpha=0.5, edgecolors='none')

for i, inst in enumerate(institutions):
    offset_y = np.sqrt(sizes[i])/2 + 10
    ax.annotate(inst, (publications[i], h_index[i]), fontsize=11, color='white',
                ha='center', va='bottom', xytext=(0, offset_y), textcoords='offset points', fontweight='bold')

ax.text(0.0, 1.08, 'Research Impact Analysis', transform=ax.transAxes, fontsize=24, color='white', fontweight='bold')
ax.text(0.0, 1.02, 'Publications vs H-Index · Bubble size = Funding', transform=ax.transAxes, fontsize=11, color='#555555')

ax.set_xlabel('Annual Publications (K)', fontsize=14, color='#888888', fontweight='500', labelpad=15)
ax.set_ylabel('Institution H-Index', fontsize=14, color='#888888', fontweight='500', labelpad=15)
ax.tick_params(colors='#555555', labelsize=11, length=0)

for y in [300, 350, 400, 450]:
    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()