plotnine

Seems like plotnine renders plots using matplotlib and has matplotlib as a dependency: https://github.com/has2k1/plotnine/blob/f6f5cb424f38329c5267...

If you already use plotnine, or if this has piqued your interest, the next release (v0.16.0) will bring nice capabilities. You can get a sneak peek by installing the pre-release: pip install --pre plotnine Details here: https://github.com/has2k1/plotnine/issues/1031 Disclaimer: I'm the author.

To your last point, have you tried plotnine? It's meant to be ggplot2 for python. https://github.com/has2k1/plotnine

I see the potential long term but that api is unintuitive at best. It almost seems obstructively terse. (ggplot(mtcars, aes("wt", "mpg", color="factor(gear)")) + geom_point() + stat_smooth(method="lm") + facet_wrap("~gear")) From https://github.com/has2k1/plotnine, their front page examples. I get that it's ripping off the ggplot api, but why would they not alias "aes" to something more meaningful? It stands for "aesthetic mapping". My problem with all the popular plotting libraries in python is they seem designed for researchers slapping together a paper and produce code that's awful to maintain.

There are Python ports of ggplot (e.g. plotnine (https://github.com/has2k1/plotnine)), but agreed, Python is behind here. I'm not the best at data viz, but I can usually piece together a way to make ggplot do what I want it to do without that much trouble or looking at documentation. Matplotlib, though ... that's a harder beast to internalize. I know it's possible to make high-quality matplotlib plots, but it's much harder for me. Like pandas, it's a library that I don't want to denigrate because I know people put lots of effort into it, but I can't lie -- I'm not a fan.

Data scientists at my previous company switched to https://github.com/has2k1/plotnine when we made a big push to python. Bit closer api to ggplot than Altair.

Another option is to use plotnine, which is intended to be a ggplot2 clone. It uses matplotlib under the hood, so if something isn't right you can tweak it. That was the main drawback I found with Altair: your declarative code is almost literally dumped to a json file and then rendered by a process external to Python, so good luck tweaking your plot. https://github.com/has2k1/plotnine

I'm partial to plotnine (https://github.com/has2k1/plotnine). It is an implementation of grammar of graphics in python (like ggplot2). It provides a stateless layer like interface which feels intuitive, and avoids bugs due to global state. But, it is built on top of matplotlib. So, if plotnine cannot do something, you can go back to the matplotlib way of doing things and take advantage of the large number of blogs, example, tutorials, and stackoverflow answers. Performance wise, it can handle more data than altair. But less than matplotlib, if you use the built in data manipulation features.

I would say hands down, plotnine. It... * is a port of ggplot2 to python * has a very active maintainer I've been testing out porting a bunch of analyses from R to python, and it has been very easy to swap in for ggplot2. The biggest downside I can see is that with ggplot2 it's easy to convert to interactive using plotly (but there isn't that kind of support for plotnine yet). https://github.com/has2k1/plotnine

The good python port is https://github.com/has2k1/plotnine/

Huh, when I was looking into Python options I had thought plotnine was dead, but looking at the GitHub that's not the case: https://github.com/has2k1/plotnine I'll give it a shot! :)

Repo https://github.com/has2k1/plotnine Docs https://plotnine.readthedocs.io/en/latest/