Science Memes
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.

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Rules
- Don't throw mud. Behave like an intellectual and remember the human.
- Keep it rooted (on topic).
- No spam.
- Infographics welcome, get schooled.
If you are here asking: "Is this a science meme?"
Probably, yes. We use the Dawkins definition of meme: a replicating idea, not just an image macro with a fact on it. A good post here doesn't need to teach you something. It needs to make you ask something: who, what, where, when, and especially why or how.
Science isn't a filing cabinet of facts, it's a conversation. For example, a photo of an eel or other localized wildlife counts because most people never see one, and wonder is the first step of inquiry. A car meme counts if it makes you curious about what's under the bonnet. If you want to talk about something you noticed in the world, chances are someone else wants to talk about it too.
We moderate for vibe, not category. Pruning is light, especially where a post creates interesting discussion. Experimenting is encouraged.
See the pinned paper on Shitposting as Public Pedagogy if you want the academic case for why this works.
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Memes
Miscellaneous
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How does it compare to matplotlib?
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.
Same here. I mostly work with Python but the graphs? They are ggplot2.
Plotnine is getting there
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.