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yuankunzhang / charming

A visualization library for Rust
Apache License 2.0
1.66k stars 61 forks source link

roadmap #32

Open wangjiawen2013 opened 8 months ago

wangjiawen2013 commented 8 months ago

Hi,

Thanks for your great work! I am looking for rust visualization library for a long time. I have tried plotters (https://github.com/plotters-rs/plotters) and plotly (https://github.com/igiagkiozis/plotly), both of them are disappointing cannot meet my demand. Charming is the best one of all the rust visualization library I have ever seen and worth trying!

Do you have a roadmap of charming and will you maintain this project ? Though I am not a developer, I can test charming for you. And can I convert charming chart to json now using something like Chart.to_json() ? if so, I can send the json to web front end and render it. Besides, can I use charming in vscode jupyter and render them ?

yuankunzhang commented 8 months ago

Hi @wangjiawen2013 , thanks for the feedback!

At the moment I don't have a concrete roadmap, but I do have something in my mind: adding more documentations being the most important one and adding support for 3D charts being another. Making it accessible in Jupyter is an interesting (and a very useful) idea, I'll find some time to look into it.

Btw you can use the Chart.to_string() method to dump a chart definition into a JSON string. And any form of contributions is welcome!

locke4 commented 7 months ago

This is a fantastic library by the way, I too found plotters and plotly weren't as useful as this library. I'm testing it out with WASM and Yew. One suggestion for the roadmap, I'd be really keen to either see a histogram series type or an option with bar charts to set the width in relative interval % rather than absolute screen pixels. I'm currently calculating the pixels based on the chart width.

image

wangjiawen2013 commented 7 months ago

It's also helpful to add some examples on how to work with external dataset, such as excel, csv, polars dataframe , because some user's data are stored in excel and csv. Vega-lite altair supports pandas dataframe and is more friendly to users.

humphreylee commented 3 weeks ago

Is the project still alive?

wangjiawen2013 commented 3 weeks ago

I'm afraid not. There is a very lack of tutorials and practical chart types. But there is a good news, the rust plotly project is re-vived.

humphreylee commented 3 weeks ago

Thanks. Will check it out.