Scatter Plot

Bubble Correlation Matrix

Matrix showing correlation strength with bubble size.

Output
Bubble Correlation Matrix
Python
import matplotlib.pyplot as plt
import numpy as np

# === STYLE CONFIG ===
COLORS = {
    'positive': '#10B981',
    'negative': '#EF4444',
    'background': '#FFFFFF',
    'text': '#1E293B',
    'text_muted': '#64748B',
    'grid': '#F1F5F9',
}

# === DATA ===
np.random.seed(42)
labels = ['A', 'B', 'C', 'D', 'E']
n = len(labels)
values = np.random.uniform(-1, 1, (n, n))
sizes = np.abs(values) * 800

# === FIGURE ===
fig, ax = plt.subplots(figsize=(8, 8), dpi=100)
ax.set_facecolor(COLORS['background'])
fig.patch.set_facecolor(COLORS['background'])

# === PLOT ===
for i in range(n):
    for j in range(n):
        color = COLORS['positive'] if values[i,j] > 0 else COLORS['negative']
        # Glow
        ax.scatter(j, i, s=sizes[i,j]*1.5, c=color, alpha=0.15, zorder=1)
        # Point
        ax.scatter(j, i, s=sizes[i,j], c=color, alpha=0.8,
                   edgecolors='white', linewidths=2, zorder=2)

# === STYLING ===
ax.set_xticks(range(n))
ax.set_yticks(range(n))
ax.set_xticklabels(labels)
ax.set_yticklabels(labels)

ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color(COLORS['grid'])
ax.spines['bottom'].set_color(COLORS['grid'])

ax.tick_params(axis='both', colors=COLORS['text_muted'], labelsize=10, length=0, pad=8)
ax.set_xlim(-0.5, n-0.5)
ax.set_ylim(-0.5, n-0.5)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Pairwise Data

Did this help you?

Support PyLucid to keep it free & growing

Support