Chord diagram · The Data Visualization Deck

What Wikipedia says

A chord diagram is a graphical method of displaying the inter-relationships between data in a matrix. The data are arranged radially around a circle with the relationships between the data points typically drawn as arcs connecting the data.

The format can be aesthetically pleasing, making it a popular choice in the world of data visualization.

The primary use of chord diagrams is to show the flows or connections between several entities (called nodes). Each entity is represented by a fragment (often colored or pattered) along the circumference of the circle.

Arcs are drawn between entities to show flows (and exchanges in economics). The thickness of the arc is proportional to the significance of the flow.

Chord diagram (information visualization)

Chord diagrams can show pretty complex data.

Cumulative electricity trade (2015–2065) among African countries (TWh)

Chord diagrams can sometimes be unreadable.

A Thousand Fibers Connect Us — Wikipedia's Global Reach

The data

To create a chord diagram, you need data. In his Medium article LA Lakers Statistics Visualized Using Python Chord Diagrams, Saul Dobilas describes ways to create chord diagrams using Python and shows how this data can be prepared.

Passes made between LA Lakers team players. NBA Regular Season 2019–20. Picture by Saul Dobilas. Data from NBA Stats

And this is what his resulting chord diagram looks like.

LA Lakers Statistics Visualized Using Python Chord Diagrams

Using a chord diagram

Use chord diagrams

For showing relationships between entities and their relative magnitudes in comparison to alternative arcs.

As a result, chord diagrams are popular in migration studies, economic flows, and genome studies.

They have also been used to highlight unexplored relationships to help address the problem of filter bubbles.

Warning!

Chord diagrams can be difficult to read or interpret when there are many groups or categories involved, as the lines or arcs may overlap and become cluttered.

It can be difficult to accurately compare the size or magnitude of the relationships or connections between groups using a chord diagram, as the lines or arcs are not necessarily proportional to one another.

Don't use chord diagrams

For displaying data with a large range of values or a wide variability, as the lines or arcs may not be able to accurately represent the differences in the data.

For displaying data that is categorical rather than numerical.

For displaying data that cannot be clearly divided into distinct groups or categories.

For displaying data that requires more precise or detailed analysis or comparison than they can provide.

Chord diagram variants you can find online

Co-occurrence of the predicted labels

Revisited the last #Eurovision contest for this one. #Netherlands was the winner

Circos — an information aesthetic for comparative genomics

Chapter 15. Advanced usage of chordDiagram(). Fig 15.7

Chapter 16 A complex example of Chord diagram

Close-Ups of a Genome, Species by Species by Species

Figure 4. Pleiotropy plot of rs1688030, an intronic variant of the HPN gene

Figure 3. The summary of the real data-analysis

Area, counties and different taxa in China (China arc), and different taxa in Hotspots and NRs (Out arcs)

Fig. 1: Chromosomal synteny between Haemonchus contortus and Caenorhabditis elegans

Adapting language models to track virus variants

Fig. 2. Genome-wide association results with WMH burden and genetic overlap of WMH risk loci

Non-ribbon Chord Diagram

Hacking a chord diagram to visualize a flow

LA Lakers Statistics Visualized Using Python Chord Diagrams

The core genes of significant pathways in FDMR 0 h versus control, FDMR 6 h versus 0 h and FDMR 24 h versus 6 h as different annuli of genes

Global migrant populations visualized using animated chord diagrams

The number of people migrating from one country to another

Seeing complexity. Hierarchical edge bundles

Editor’s notes

The chord diagram was the first card I designed for The Data Visualization Deck. Instead of coding the diagram with Python or another tool, I used Figma, so it must be treated as an illustration.

Chords in Figma are made simply by adding corner radii to shapes

But in real life, chord diagrams may become cluttered. One way to make them more readable is using something called “Hierarchical edge bundling,” proposed by Danny Holten. More about this — in the article on Seeing Complexity.