Cytoscape.js VS vega-lite

Interactive User Interface: Developing an interactive UI for visualizing the graph and its communities could make the summarization process more intuitive. Tools like D3.js or Cytoscape.js can be used to create dynamic visualizations.

This could be probably done with https://js.cytoscape.org/ as well, so maybe look into that.

Maybe look into Cytoscape.js... There's a react wrapper component: https://github.com/plotly/react-cytoscapejs

The UI is almost entirely based on Cytoscape JS, which is one of the most use graph libraries out there (and for good reason, I've found it very good). The UI is similar to some other JavaScript libraries that deal with visualisation of network models, so it ends up being similar to most examples of Neo4j dashboards, D3, etc.

Relationship graphs are created using Cytoscape.js

I am playing with an app built around cytoscape.js for visualizing graphs. That means adding/removing nodes, responding to node events and so on.

Data source: DB of tutorials and tags. I created the skills map of collective knowledge shows a number of tutorials uploaded by users. It is illustrated the topics of user-generated content. Size of stars is a number of tutorials on the topic. The bigger the star — the more popular skill. The more connection a skill has — the more essential and versatile it is. After the login, this map becomes personalized for every user in accordance with the uploaded tutorials. All skills are combined into 6 specializations (science, sign, people, tech, art, business). Some topics are repeated in several specializations, for instance, "soft skills." Tool: Cytograph.js Layout: Cise layout Interactive version is here https://unschooler.me/skills

We use the slightly simpler vega-lite from the same group. It typically gets us 98% of the way there quite quickly.

Its from the same team, just a more simple wrapper around D3.

https://vega.github.io/vega-lite/

I like Vega-Lite: https://vega.github.io/vega-lite/

It’s built by folks from the same lab as D3, but designed as “a higher-level visual specification language on top of D3” [https://vega.github.io/vega/about/vega-and-d3/]

My favorite way to prototype a dashboard is to use Streamlit to lay things out and serve it and then use Altair [https://altair-viz.github.io/] to generate the Vega-Lite plots in Python. Then if you need to move to something besides Python to productionize, you can produce the same Vega-Lite definitions using the framework of your choice.

Box zoom would need to be added to Vega-Lite first, and there has been some discussion around it in https://github.com/vega/vega-lite/issues/4742. Bottom line is that there's nothing blocking its implementation, someone just needs to do the work in Vega-Lite. And once released in Vega-Lite, Altair would pick it up automatically with how we generate the Altair API from the Vega-Lite schema.

I also have difficulties with Gnuplot and Matplotlib. I like Vega that allows me to create visualisations in a declarative way. If I really need something special I go with d3.js, which had a really steep learning curve but with ChatGPT it should have become easier for beginners.

[1] https://vega.github.io/vega-lite/

To ensure you do not miss this: LiveBook comes with a Vega Lite integration (https://livebook.dev/integrations -> https://livebook.dev/integrations/vega-lite/), which means you get access to a lot of visualisations out of the box, should you need that (https://vega.github.io/vega-lite/).

In the same "standing on giant's shoulders" stance, you can use Explorer (see example LiveBook at https://github.com/elixir-explorer/explorer/blob/main/notebo...), which leverages Polars (https://www.pola.rs), a very fast DataFrame library and now a company (https://www.pola.rs/posts/company-announcement/) with 4M$ seed.

Nice, would be nice to have it integrated in GitHub markdown.

Looks similar to Vega or Vega-lite(https://vega.github.io/vega-lite/). Definitely as rich as D3.js but gets the job done for simple visualisations.

Vega-lite can do this https://vega.github.io/vega-lite/