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Too many R packages: CRAN is inundated with submissions

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Re: Too many R packages: CRAN is inundated with submissions

#71

Post by dash2 »

Mairoce wrote: post #70
levocardia wrote: post #68

Earlier quoted context omitted.

"The real problem with this package is that it makes things easy, instead of hard"

That’s a rather glib interpretation of what I said. I’m being rather charitable when I call the tidyverse “user-friendly”. That might be the goal of tidyverse devs, but it hasn’t been the reality since inception. The point is even if we assume it is or will eventually become user-friendly, are we willing to accept the trade-offs that come with that?

I think the users have clearly delivered the verdict that it is friendlier than base R. Admittedly a low bar. Non R users, which do you prefer:

    foo[foo$bar == “baz”,]

    foo |> filter(bar == “baz”)

?

Re: Too many R packages: CRAN is inundated with submissions

#72

Post by chocochunks »

donkeyboy wrote: post #64
pks016 wrote: post #55

Earlier quoted context omitted.

I would be in minority. But, I don't like tidyverse ecosystem. I prefer data.table for most of my uses.

Data.table is just so much faster, and the sql-like stntax is easier tonunderstand

I can never remember the data.table syntax, every time I use it I have to re-learn it. It doesn't feel very SQL to me either. There is an interface to use tidy syntax on data.tables and get's you 90% of the speed.

Re: Too many R packages: CRAN is inundated with submissions

#73

Post by Mairoce »

dash2 wrote: post #71
Mairoce wrote: post #70

Earlier quoted context omitted.

That’s a rather glib interpretation of what I said. I’m being rather charitable when I call the tidyverse “user-friendly”. That might be the goal of tidyverse devs, but it hasn’t been the reality since inception. The point is even if we assume it is or will eventually become user-friendly, are we willing to accept the trade-offs that come with that?

I think the users have clearly delivered the verdict that it is friendlier than base R. Admittedly a low bar. Non R users, which do you prefer: foo[foo$bar == “baz”,] foo |> filter(bar == “baz”) ?

The first one by a mile.

Is this a joke?

Re: Too many R packages: CRAN is inundated with submissions

#74

Post by rcbdev »

PaulHoule wrote: post #48
jdw64 wrote: post #31

Earlier quoted context omitted.

I also think Python is a bit better. (Though, unlike you, my programming skills are directly tied to my livelihood, so it benefits me if one language can cover as much ground as possible. Being locked into a specific domain just narrows the number of jobs I can take on.) You're not wrong, but it makes me pretty sad that all my homepage submissions are marked as 'showdead' and no one ever sees them. Maybe my submissio…

I've got a very Clark Kent kind of a job doing very ordinary work at a university unit which is authoritative in its domain and don't talk a lot about what I do there because the last thing I want to do is have people think my opinions have anything to do with my employer (and the second to last thing I want to do is post statements to that effect!) I code Java and Javascript by day and mostly Python for my side proj…

This reads like a Markov Chain's output.

Re: Too many R packages: CRAN is inundated with submissions

#75

Post by kgwgk »

dash2 wrote: post #71
Mairoce wrote: post #70

Earlier quoted context omitted.

That’s a rather glib interpretation of what I said. I’m being rather charitable when I call the tidyverse “user-friendly”. That might be the goal of tidyverse devs, but it hasn’t been the reality since inception. The point is even if we assume it is or will eventually become user-friendly, are we willing to accept the trade-offs that come with that?

I think the users have clearly delivered the verdict that it is friendlier than base R. Admittedly a low bar. Non R users, which do you prefer: foo[foo$bar == “baz”,] foo |> filter(bar == “baz”) ?

Or maybe

    foo[bar == “baz”]

Re: Too many R packages: CRAN is inundated with submissions

#76

Post by frogperson »

Better search could solve this I think. If packages could be automatically, semantically grouped and made searchable, then there would be a lot less packages. a lot of times is simply faster to remake that to search for something appropriate. I don't think RAG is the right answer, it needs to be more capable than that. i don't know quite what that would look like.

I would love to be able to filter out low effort, bad docs, no tests, no recent contributions and and more after typing a semantic query for a library to use.

Re: Too many R packages: CRAN is inundated with submissions

#77

Post by PaulHoule »

rcbdev wrote: post #74
PaulHoule wrote: post #48

Earlier quoted context omitted.

I've got a very Clark Kent kind of a job doing very ordinary work at a university unit which is authoritative in its domain and don't talk a lot about what I do there because the last thing I want to do is have people think my opinions have anything to do with my employer (and the second to last thing I want to do is post statements to that effect!) I code Java and Javascript by day and mostly Python for my side proj…

This reads like a Markov Chain's output.

People were accusing me of being an LLM before there were LLMs!

Notably I do have an unusual nervous system that sees opportunities and dangers that other people don't see, sometimes I'm right.

I didn't get enough sleep last night and managed to get out of the house without being attacked by the silverware and my evil twin came out for the first time in years but I was able to resorb him in about a minute.

Re: Too many R packages: CRAN is inundated with submissions

#79

Post by flopsamjetsam »

mjhay wrote: post #17
ActionHank wrote: post #16

Earlier quoted context omitted.

I do wonder if there isn't enough computer science / software engineering that is being taught as part of data science. People I've worked with that used R and manged data / did analysis didn't really seem too concerned with long term maintenance. Secondary observation, these same people were the first to preach for the AI coding gospel.

Bingo. The typical data scientist has a masters or PhD in a non-CS quantitative field, and has had exactly zero CS or software eng classes. It’s a shame, because once you get over some of the idiosyncrasies, R is a really powerful and flexible functional language.

I was a programmer, and moved over to biology recently. I was very "wtf is R" when I started, but slowly its strengths are coming through. I found the combination of the REPL plus the IDE, and the language syntax, somehow give me the ability to play around a lot more than I expected. Unlike others, I find tidyverse (especially ggplot2 and dplyr, which reminds me a lot of pandas) to be quite intuitive.
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