vega-lite VS graphic-walker

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/

[2] https://github.com/Kanaries/graphic-walker/issues/330

GWalkR is an open-source R library that allows you to turn your data frame into a tableau style user interface for data exploration and visualization. It also allows you to analysis your data with natural language questions.

GWalkR is the R binding of graphic-walker: https://github.com/Kanaries/graphic-walker

Big fan of D3.js and now there is Observable Plot! I am building several data visualization software for exploratory data analysis:

RATH, auto exploratory data analysis: https://github.com/Kanaries/Rath

GraphicWalker, embeddable data exploration component: https://github.com/Kanaries/graphic-walker

They are using vega-lite for now. But there is a limit of building more fancy and customized visualizations. It seems Plot has a more flexible layer based visualization system that can support larger design space.

Is Plot stable enough now to migrate from vega-lite based system to Plot based? Are there any large milestone or roadmap of Plot in future?

+ Graphic Walker (https://github.com/Kanaries/graphic-walker): A lite embeddable component for visual analysis.

+ PyGWalker (https://github.com/Kanaries/pygwalker): turning your pandas dataframe into a Tableau-style User Interface for visual exploration.

RATH is a collection of interesting ideas that we think the next generation of data analysis software should be, so there might be many features that not well organized to be a united app. Tell me which feature you prefer and which is not. Looking forward for your ideas and advice.

I know you said you *dont* want a tableau like interface, but in case you do this might be a cool open source project to check out: https://github.com/Kanaries/graphic-walker

> it seems like the heavy lifting is done by the web app here: https://github.com/Kanaries/graphic-walker

FWIW, both are made by the same entity, Kanaries.

You may try to use and modify based on the OpenSource Graphic Walker: https://github.com/Kanaries/graphic-walker

Graphic Walker is designed to be easy to embed in other applications as a React component. Check out the code here: https://github.com/Kanaries/graphic-walker