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dgfltoday at 8:12 AM3 repliesview on HN

Disagree on the last statement. Makie is tremendously superior to matplotlib. I love ggplot but it is slow, as all of R is. And my work isn’t so heavy on statistics anyway.

Makie has the best API I’ve seen (mostly matlab / matplotlib inspired), the easiest layout engine, the best system for live interactive plots (Observables are amazing), and the best performance for large data and exploration. It’s just a phenomenal visualization library for anything I do. I suggest everyone to give it a try.

Matlab is the only one that comes close, but it has its own pros and cons. I could write about the topic in detail, as I’ve spent a lot of time trying almost everything that exists across the major languages.


Replies

versteegentoday at 11:38 AM

I recently used Makie to create an interactive tool for inspecting nodes of a search graph (dragging, hiding, expanding edges, custom graph layout), with floating windows of data and buttons. Yes, it's great for interactive plots (you can keep using the REPL to manipulate the plot, no freezing), yes Observables and GridLayout are great, and I was very impressed with Makie's plotting abilities from making the basics easy to the extremely advanced, but no, it was the wrong tool. Makie doesn't really do floating windows (subplots), and I had to jump through hoops to create my own float system which uses GridLayout for the GUI widgets inside them. I did get it to all work nearly flawlessly in the end, but I should probably have used a Julia imGUI wrapper instead: near instant start time!

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Certhastoday at 8:40 AM

I love Makie but for investigating our datasets Python is overall superior (I am not familiar enough with R), despite Julia having the superior Array Syntax and Makie having the better API. This is simply because of the brilliant library support available in scikit learn and the whole compilation overhead/TTFX issue. For these workflows it's a huge issue that restarting your interactive session takes minutes instead of seconds.

dan-robertsontoday at 8:21 AM

I tried some Julia plotting libraries a few years ago and they had apis that were bad for interactively creating plots as well as often being buggy. I don’t have performance problems with ggplot so that’s what I tend to lean to. Matplotlib being bad isn’t much of a problem anymore as LLMs can translate from ggplot to matplotlib for you.