vega-lite VS plotly.js

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/

The underlying data is from an online betting site. Data analysis was done in Python and I used Vega/Altair for the visualisation.

Plotly is based on D3. Has both open-source version and paid option.

https://plotly.com/javascript/

Plotly as our chart renderer

In this lesson, we will go through the steps of using Plotly.js in React. Plotly.js is an Open Source Graphing Library. At the end of this lesson, you should be able to do a simple plot with Plotly.js.

Well, MathML[1] support is (nearly) everywhere now, and as the docs say:

MathML Core is a subset with increased implementation details based on rules from LaTeX and the Open Font Format. It is tailored for browsers and designed specifically to work well with other web standards including HTML, CSS, DOM, JavaScript.

I don't have a lot of experience working with this stuff (yet) but if you can script your MathML objects with Javascript, you should be able to make whatever interactive "stuff" you want in terms of math notation. Now drawing objects and plots and stuff is a different question.

There's stuff like Plotly[2], D3[3], Sigma[4], etc. that might be useful depending on exactly what effects you're going for.

[1]: https://developer.mozilla.org/en-US/docs/Web/MathML

[2]: https://github.com/plotly/plotly.js

[3]: https://d3js.org/

[4]: https://www.sigmajs.org/

This is the end of the lesson. For more information on Plotly.js, check the documentation Plotly.