Altair – A declarative statistical visualization library for Python

Post by fock » Thu, Jun 04, 2020, 5:38 PM UTC

kpgiskpg wrote: post #40

grenoire wrote: post #34

Earlier quoted context omitted.

While writing my thesis I found matplotlib to be quite beautiful with adjustments only on the text (use LaTeX rendering to fit in with the thesis doc itself) and colour schemes; that is literally three lines of code at most. It's not ugly by default either, it produces very crisp graphics easily.

Beauty is in the eye of the beholder, I guess. I wouldn't put matplotlib graphs in a paper without tweaking the style, and it gets frustrating when you have to do this for every single plotting script you write. And the defaults certainly aren't colourblind-friendly.

Post by dragonsh » Fri, Jun 05, 2020, 6:19 AM UTC

Sherl wrote: post #42

dragonsh wrote: post #18

We used altair to develop an analytics dashboard as part of our single page application (SPA). We developed a web component encapsulating vega-lite JS library and used that component to assemble the dashboard which is part of the application. Altair based backend can use custom renderer to generate target response for analytics API requests. [1] Most of the commercial and open source solutions including Tableau, Apac…

Would you recommend this to integrate with FastAPI or dash/plotly for similar application?

Post by nl » Sat, Jun 06, 2020, 5:57 AM UTC

dlkf wrote: post #29

kpgiskpg wrote: post #23

I've always hated matplotlib, even though it gets the job done. The graphs are ugly by default, and the API would be unusable if it weren't for StackOverflow. Maybe I just need to sit down and learn it really well. Anyway, this seems cool.

> even though it gets the job done How is this an addendum, rather than the main point? I will always take a flexible library that allows me to "get the job done" over a declarative framework that will do something similar to—but not exactly—what I need.