Circle Packing

Circle packing is a hierarchical visualization where data is represented as circles containing other circles. The area of each circle is proportional to the value it represents, making it effective for showing part-to-whole relationships in nested data. Unlike treemaps which use rectangles, circle packing can sometimes waste space but creates a more organic, visually appealing representation. It's particularly effective for organizational charts, file systems, and budget allocations.

Example Visualization

Circle packing diagram showing budget allocation by department and subcategory

Try this prompt

"Use circlify with matplotlib to create a circle packing diagram visualizing the 'Budget Allocation' by 'Department' and 'Sub-category'. Generate a proper example dataset to demonstrate this visualization."

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Python Code Example

example.py

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import circlify

# Example hierarchical data
df = pd.DataFrame({
    'Department': ['Marketing', 'Marketing', 'Engineering', 'Engineering', 
                   'Sales', 'Sales', 'HR', 'HR'],
    'Subcategory': ['Advertising', 'Social Media', 'Development', 'Testing', 
                    'Direct Sales', 'Online Sales', 'Recruitment', 'Training'],
    'Budget': [30000000, 20000000, 50000000, 15000000, 
               25000000, 18000000, 12000000, 8000000]
})

# Build hierarchy for circlify
data = []
for dept, group in df.groupby('Department'):
    children = [{'id': row['Subcategory'], 'datum': row['Budget']} 
                for _, row in group.iterrows()]
    data.append({'id': dept, 'datum': group['Budget'].sum(), 'children': children})

# Compute circle positions
circles = circlify.circlify(data, show_enclosure=False)

# Plot
fig, ax = plt.subplots(figsize=(14, 14))
ax.set_xlim(-1.2, 1.2)
ax.set_ylim(-1.2, 1.2)
ax.set_aspect('equal')
ax.axis('off')

for circle in circles:
    x, y, r = circle.x, circle.y, circle.r
    if circle.level == 1:  # Department
        ax.add_patch(patches.Circle((x, y), r, facecolor='#f0f0f0', 
                                     edgecolor='#999', linewidth=2))
        ax.text(x, y + r, circle.ex['id'].upper(), ha='center', 
                fontsize=14, fontweight='bold')
    elif circle.level == 2:  # Subcategory
        ax.add_patch(patches.Circle((x, y), r * 0.95, facecolor='steelblue', 
                                     edgecolor='white'))

plt.title('Budget Allocation by Department', fontsize=16)
plt.show()

Common Use Cases

1Corporate budget allocation visualization
2File system size analysis
3Organizational structure display
4Market segmentation by size

Pro Tips

Use contrasting colors for different hierarchy levels

Add labels only for circles large enough to display them

Consider treemaps for more space-efficient layouts