[raffael_de]

no plotting library available in python even comes close to ggplot2. just to give one major example. another would be the vast amount of statistics solutions. but ... python is good enough for everything and more - so, it doesn't really feel worth maintaining two separate code bases and R is lacking in too many areas for it to compete with python for most applications.

[TheSoftwareGuy]

Plotting is one task I find such huge benefits to AI coding assistants. I can ask "make a plot with such and such data, one line per <blank>" etc. Since its so east to validate the code (just run the program and look at the plots) iterations are super easy

[raffael_de]

That's probably 50% what I use Claude for. But always "use matplotlib's explicit / object-oriented interface and don't add comments".

[YeGoblynQueenne]

>> no plotting library available in python even comes close to ggplot2.

I so disagree. I've used R for plotting and a bit of data handling since 2014, I believe, to prove to a colleague I could do it (we were young). After all this time I still can't say I know how to do anything beyond plotting a simple function in R without looking up the syntax.

Last week I needed to create two figures, each with 16 subplots, and make sure all the subplot axis labels and titles are readable when the main text is readable (with the figure not more than half a page tall). On a whim I tried matplotlib, which I'd never tried before and... I got it to work.

I mean I had to make an effort and read the dox (OMG) and not just rummage around SO posts, but in like 60% of the time I could just use basic Python hacking skillz to intuit the right syntax. That is something that is completely impossible (for me anyway) to do in R, which just has no rhyme or reason, like someone came up with an ad-hoc new bit of syntax to do every different thing.

With Matplotlib I even managed to get a legend floating on the side of my plot. Each of my plots has lines connecting points in slightly different but overlapping scales (e.g. one plot has a scale 10, 20, 30,another 10, 20, 30, 40, 50) but they share some of the lines and markers automatically, so for the legend to make sense I had to create it manually. I also had to adjust some of the plot axis ticks manually.

No sweat. Not a problem! By that point I was getting the hang of it so it felt like a piece of cake.

And that's what kills me with R. No matter how long I use it, it never gets easier. Never.

I don't know what's wrong with that poor language and why it's such an arcane, indecipherable mess. But it's an arcane and indecipherable mess and I'm afraid to say I don't know if I'll ever go back to it again.

... gonna miss it a little though.

Edit: actually, I won't. Half of my repos are half R :|

[freehorse]

Until you need to plot anything more than a few hundred thousand data points, in which case ggplot is extremely slow, if it even manages.

[raffael_de]

I would argue that this is too much for any static plot. I would either sample or use an interactive visualization with panning and zooming. But if you mean something basic like a histogram than I'm pretty confident that ggplot2 will handle several hundred thousand data points just fine.

[freehorse]

Fair; so my arguments becomes "until you need anything barely interactive such as zooming in".

[DadBase]

We used to do our plots with PostScript and dental floss. ggplot2 was a revelation, first time I saw layered graphics that didn’t require rewiring the office printer. Still can’t run it on Thursdays though, not after the libcurl incident.