Thanks! Glad to know it can be helpful!

That's the thing with wrapper libraries: amazing at the beginning, but quickly becoming frustrating.

There aren't so many polished matplotlib charts out there. So I'm not even sure if chatGPT would be good at it.

There are countless stunning charts available on the web, many of which are crafted using programming languages like R.

Tired of hearing doubts about matplotlib's capabilities, I've curated and translated a collection of impressive charts using Python and matplotlib.

Explore them all with detailed tutorials and reproducible code at:

https://python-graph-gallery.com/best-python-chart-examples/

What's weird is that I don't think I've ever heard any serious practitioner doubt its capabilities. The main complaints I hear are just annoyance with pyplot.

This is a very good question as performance is a key struggle in Data Visualization. Swizec answer below is great.

I will write more about performance soon. But using several layers of canvas is definitely the way to go in most situation to put it in a nutshell

All the map sections are not ready yet. But they will be soon!

Nice thanks!

Animation is the trickiest part of dataviz on the web IMO.

I like react-spring but there are sooo many approached. All with pros and cons.

I'll write more about it soon!

Do you have a Substack? I remember your name from the data-to-viz. I’m interested in reading more about your experiences and thoughts on the space

If 1 day you need to compute the position of all the rectangles in a treemap, you will understand how handy d3.js is.

D3.js is split in 2 types of functions:

- "math" - rendering

Math functions cannot be avoided for sure

I also have the d3 graph gallery. It shows only simple charts which ease the learning curve

d3-graph-gallery.com

Thank you.

Really nice gallery. I think this will serve as a great reference material for me when learning.