Arc Diagram
Chart overview
Arc diagrams display network relationships by placing nodes along a horizontal line and drawing arcs between connected nodes.
Key points
- The height of each arc typically represents the distance between nodes or the strength of the connection.
- This layout is particularly useful for showing patterns in ordered data, such as character interactions in a story or sequential dependencies in a process.
Python Tutorial
How to create a arc diagram in Python
Use the full tutorial for implementation details, troubleshooting, and chart variations in matplotlib, seaborn, and plotly.
Complete Guide to Scientific Data VisualizationExample Visualization
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Generate publication-ready arc diagrams with AI in seconds. No coding required – just describe your data and let AI do the work.
View example prompt
"Create an arc diagram showing character interactions from 'The Great Gatsby'. Include 8 main characters: Nick, Gatsby, Daisy, Tom, Jordan, Myrtle, Wilson, Meyer. Generate interaction counts based on the novel (Gatsby-Daisy: 25, Nick-Gatsby: 35, Nick-Jordan: 20, Tom-Myrtle: 15, Tom-Daisy: 30, etc.). Order characters chronologically by first appearance. Set arc height proportional to interaction strength. Color arcs by type: romantic (red), friendly (blue), antagonistic (gray). Width of arcs proportional to interaction count. Add character labels below nodes. Include a legend for arc types and a title with total interactions."
How to create this chart in 30 seconds
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AI Generation
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Customize & Export
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Python Code Example
Console Output
Total Interactions: 173
Characters: 8
Most Interactions: ('Nick', 4)Common Use Cases
- 1Character interactions in literature
- 2Sequential process dependencies
- 3Genomic connections and relationships
- 4Social network visualization
Pro Tips
Order nodes to minimize arc crossings
Use arc thickness for connection strength
Color-code arcs by category or direction
Long-tail keyword opportunities
High-intent chart variations
Library comparison for this chart
nxviz
Useful in specialized workflows that complement core Python plotting libraries for arc-diagram analysis tasks.
matplotlib
Best when you need full control over axis formatting, annotation placement, and journal-specific styling for arc-diagram.
networkx
Useful in specialized workflows that complement core Python plotting libraries for arc-diagram analysis tasks.
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.