this post was submitted on 12 Nov 2024
338 points (98.0% liked)

Science Memes

11148 readers
2117 users here now

Welcome to c/science_memes @ Mander.xyz!

A place for majestic STEMLORD peacocking, as well as memes about the realities of working in a lab.



Rules

  1. Don't throw mud. Behave like an intellectual and remember the human.
  2. Keep it rooted (on topic).
  3. No spam.
  4. Infographics welcome, get schooled.

This is a science community. We use the Dawkins definition of meme.



Research Committee

Other Mander Communities

Science and Research

Biology and Life Sciences

Physical Sciences

Humanities and Social Sciences

Practical and Applied Sciences

Memes

Miscellaneous

founded 2 years ago
MODERATORS
 
you are viewing a single comment's thread
view the rest of the comments
[–] Eheran 6 points 1 week ago (2 children)

How does it compare to matplotlib?

[–] scrion 7 points 1 week ago (1 children)

Plots are typical composed, and when writing a paper (I insert them mostly into TeX publications) I do find the quality of the resulting plot is just so much more refined.

Seaborn is indeed closer and was definitely inspired by ggplot2 in some areas, but IMHO, it's still not 100% there visually. I'm very much a Python user and would love it to be, but when I'm, let's say, publishing a book, I'd always go back to ggplot2 - when preparing a paper for a lab class, seaborn is probably fine.

[–] [email protected] 2 points 1 week ago

Same here. I mostly work with Python but the graphs? They are ggplot2.

Plotnine is getting there

[–] [email protected] 2 points 1 week ago* (last edited 1 week ago)

It's a lot more like Seaborn. It produces gorgeous plots with a lovely syntax that is quick and easy to use, but it's not a full drawing toolkit like matplotlib.

If I need the plot to have a very precise aesthetic, mpl is great. But if I want a high quality statistical plot that looks great. ggplot2 will do it in about 2 seconds. See also plotnine.

I have no idea how op thinks they could make a decent histogram any quicker than ggplot(data) + geom_histogram(x= x). I mean you don't even have to leave your shell/editor or extract the SQL into CSV.