vega-lite VS plot

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.

I have a bunch of data that I want to plot. I'm using lisp-stat, which is pretty good, for data frames and analysis. However, lisp-stat uses vega-lite for plotting and to put it mildly, vega-lite is fucking awful.

I wish the author all the best in developing his library; at the moment it seems quite incomplete, so if you want SVG charts today, I recommend Observable Plot[1] or Vega-Lite[2]

[1]: https://github.com/observablehq/plot

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

The examples from the first chapter of the Introduction to the Practice of Statistics, In Lisp-Stat, are complete and on github. This chapter is mostly about data visualisation, and anyone who uses PLOT might find the additional examples useful.

But, that's part of the reason for PLOT -- to hide that ugliness and make it easier to work with from Common Lisp. Have you found something specific that PLOT won't let you do? If so, open an issue and I'll take a look.

If you want to learn Lisp using a real-world problem, consider enhancing the stem-and-leaf plots. This is a good way to learn Common Lisp basics. It uses looping, printing and other basic programming constructs with text output. Specifically we need split stems and back-to-back stem plots.