Scatter Plot

Glow Bubble Scatter

Multi-category scatter with glowing halo effect and modern color palette.

Output
Glow Bubble Scatter
Python
import matplotlib.pyplot as plt
import numpy as np

# === STYLE CONFIG ===
COLORS = {
    'primary': '#6366F1',     # Indigo
    'secondary': '#EC4899',   # Pink
    'accent': '#10B981',      # Emerald
    'background': '#FFFFFF',
    'text': '#1E293B',
    'text_muted': '#64748B',
    'grid': '#F1F5F9',
}

# === DATA ===
np.random.seed(42)
n = 30
x = np.random.uniform(1, 9, n)
y = np.random.uniform(1, 9, n)
sizes = np.random.uniform(150, 600, n)
categories = np.random.choice([0, 1, 2], n)
palette = [COLORS['primary'], COLORS['secondary'], COLORS['accent']]

# === FIGURE ===
fig, ax = plt.subplots(figsize=(10, 6), dpi=100)
ax.set_facecolor(COLORS['background'])
fig.patch.set_facecolor(COLORS['background'])

# === PLOT ===
# Glow layers (halo effect)
for alpha, scale in [(0.03, 2.5), (0.05, 2.0), (0.08, 1.5)]:
    for cat in [0, 1, 2]:
        mask = categories == cat
        ax.scatter(x[mask], y[mask], s=sizes[mask] * scale, 
                   c=palette[cat], alpha=alpha, zorder=1)

# Main points
for cat, label in zip([0, 1, 2], ['Alpha', 'Beta', 'Gamma']):
    mask = categories == cat
    ax.scatter(x[mask], y[mask], s=sizes[mask], c=palette[cat],
               alpha=0.8, edgecolors='white', linewidths=2,
               label=label, zorder=3)

# === AXES ===
ax.set_xlim(0, 10)
ax.set_ylim(0, 10)
ax.set_xlabel('Dimension X', fontsize=10, color=COLORS['text'], labelpad=10)
ax.set_ylabel('Dimension Y', fontsize=10, color=COLORS['text'], labelpad=10)

# === STYLING ===
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.yaxis.grid(True, color=COLORS['grid'], linewidth=1)
ax.set_axisbelow(True)
ax.tick_params(axis='both', colors=COLORS['text_muted'], labelsize=9, length=0, pad=8)

ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12),
          ncol=3, frameon=False, fontsize=9, labelcolor=COLORS['text_muted'])

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Pairwise Data

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