aplzr · HackerTrans

hace 2 mesesdiscuss

Workplace safety rules for screen workers say that to avoid eye strain, windows should be to the side, not in the direction you're facing. On a bright day the light coming from the window can have an intensity multiple orders of magnitude higher than the screen. I find it very uncomfortable.

aplzr

hace 12 mesesdiscuss

I really like talking to Claude (free tier) instead of using a search engine when I'm stumbling upon a random topic that interests me. For example, this morning I had it explain the differences between pass by value, pass by reference, and pass by sharing, the last of which I wasn't aware of until then.

Is this kind of thing also possible with one of these self-hosted models in a comparable way, or are they mostly good for coding?

aplzr

el año pasadodiscuss

Alright, thanks. I don't particularly like notebook, but this might a reason to give it another go.

aplzr

el año pasadodiscuss

I'm in the same boat as the person you replied to, but have zero experience with remote plotting other that doing static plots in in a remote session in the interactive window provided by VS Code's python extension. Would this also work there, or would I have to start using jupyter notebooks?

aplzr

hace 2 añosdiscuss

The article lists a few things that you can do with R, but fails to make good on its headline promise: explaining why R is the best language for data journalism.

To me, and I think to many other people as well, the language most suited for anything data-related is Python, not R. I might be wrong, but If I am I won't know it after reading this article, because it doesn't compare R to other options on the table. R is only the best at something if it offers advantages over the other options, and to be honest I very much doubt that this is the case when comparing against Python.

Anecdotally, a number of years ago at university I took a class titled "Statistical programming with R" because I had heard good things about it and was looking forward to a chance to learn a new tool. Unfortunately I learned pretty quickly that I had to fight R every step of the way to get it to do what I wanted. Everything seemed arcane, convoluted, and complicated. Went back to Python and never looked back. I don't doubt that one can do great things with R, but the effort needed to get there simply doesn't seem worth it to me when Python seems so much more accessible.

Having said all that, I would be quite interested in a comparison of typical data science (or data journalism) tasks in both R and Python by someone who is good at both. After having read the article headline I had hoped it went into that direction. I was disappointed to see that it's essentially just a statement of opinion that isn't backed up in any meaningful way.

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