5 ms·

I'm not sure what would lead to you believe this. I've worked in the data science/ML space for over a decade now and I see the majority of pure analytics projec

I'm not sure what would lead to you believe this. I've worked in the data science/ML space for over a decade now and I see the majority of pure analytics projects started in R, including at big tech companies I've worked at recently. Of course, ML projects and other things that need to result in production-grade models are almost always done in Python. This is currently the most visible form of "data project" due to all the ML/AI hype, but it is far from the only data work going on.

aydyn 2y ago
Youre wrong. Python is outpacing R in usage. Every metric you can find proves it. R also has fundamental issues and lacks serious development.
- stoperaticless 2y ago
  s/serious/hyped
  - aydyn 2y ago
    No. R fundamentally has not really improved in the past ~10 years. Do you know much about how R works? Also try: gsub('serious', 'hyped', x)
    - lottin 2y ago
      Maybe because it already does what it intends to do reasonably well? I mean, what do you think needs to be improved?
      - smcin 2y ago
        Here are 14 years of HN discussions/criticisms of R: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&query=R%20language&sort=byPopularity&type=story https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que... "Does what it intends to do reasonably well" is going to be widely subjective, depending on whether the user's use-case is statistical/life-sciences vs more general purpose coding and relying on many packages; prototyping/experimentation vs production code; whether the user uses base-R, or tidyverse/data.table, etc. Here are two of those many posts: * An opinionated view of the Tidyverse “dialect” of the R language (July 5, 2019) https://news.ycombinator.com/item?id=20362626 https://news.ycombinator.com/item?id=20362626 * The R programming language: The good, the bad, and the ugly (epatters.org, 2018) https://news.ycombinator.com/item?id=35571659 https://news.ycombinator.com/item?id=35571659 -> https://www.epatters.org/post/r-lang/ https://www.epatters.org/post/r-lang/
      - aydyn 2y ago
        If youre unironically asserting that R already does everything well enough Im not going to take you seriously.
        lottin 2y ago
        I'm asking what needs to be improved, in your opinion. That's a normal follow-up question that you should be able to answer. Otherwise, why are you even commenting?
        aydyn 2y ago
        No you arent, youre clearly asking in a rhetorical way. Re-read your post. Any criticism brought up you'd dismiss. Heres one: lack of native 64 bit integers.
        lottin 2y ago
        No, I was just asking out of curiosity. You're overthinking too much.
        aydyn 2y ago
        No, you were clearly asserting that R already does everything needed. Stop trying to gaslight.
        lottin 2y ago
        You're crazy.
        dang 2y ago
        Please don't cross into personal attack or name-calling, and please especially avoid this sort of tit-for-tat spat with another user. It's way against the site guidelines and makes for boring reading. I know it's not always easy to extricate oneself but it's helpful to remember that the only way to 'win' is to stop. If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.
  - openrisk 2y ago
    The issue is that even if you peel the hype (which is a fact), python is still far larger. If you check e.g. the journal of open source software (which does not have much ML/AI bias), most of the papers are python, with an occasional R and julia submission.
- vixen99 2y ago
  Not to dispute because I have no idea so I'll assume you're correct. But how many metrics did you find and how were they obtained? And how would you know they are representative of all R users?
  - 0cf8612b2e1e 2y ago
    For whatever it is worth, the TIOBE index lists Python as #1, R at #21. Python is the first language many people are exposed to today. It has a library and tooling for every use case. https://www.tiobe.com/tiobe-index/ https://www.tiobe.com/tiobe-index/
    - kuhewa 2y ago
      R has a pretty particular use case though, Python use for statistical programming/data analysis would be an apples to apples comparison. People doing a coding 101 course in Python don't really count against the R user base.
      - aydyn 2y ago
        No one is disputing that R has usage in niche arenas.
boringg 2y ago
Im curious about the people who use R in big tech companies that you've worked at. Were the R users the people who had just come out of school and still working using their academic dev environment before weening off? I always found that was the group who used R - kind of a use what you are used to until it gets out of step with the remaining workflow. I also would say that the amount of R I see is far less than python.
- disgruntledphd2 2y ago
  So, (speaking as someone who started with R and now predominantly writes Python), I think there's a bunch of things going on here. 1. R is 100% better for analytics work and statistical modelling. There's just no contest. 2. Python is much, much better for data getting (APIs/scraping etc) and dealing with non table-like data. Again, there's basically no contest here. 3. Software engineers hate R (in most cases), which means that it's easier to hand over work for production in Python. This leads to a situation where it looks like most of the prod-level work is being done in Python, but if you look under the covers you'll discover that most prototyping/analysis/exploration is done in R and then ported to Python if it works. Like, Python is a great language for lots of things, but it's pretty terrible for exploratory DS work (pandas is like the worst features of base R and base Python mashed together in an unholy hybrid). There's also the fact that all the NN stuff is predominantly Python, so lots of companies believe that they need Python people, which reinforces the stereotype. And finally, while I love R, Python has more guardrails, and it's harder to make an unmaintainable mess with it (relative to R). Particularly when people use all the various lazy evaluation packages that the tidyverse has used over the past decade (I once maintained a codebase that used all of these in different places, it was not a fun experience).
  - greentxt 2y ago
    One of the better comments in this thread, I would only qualify that different levels of ability mediate much of the "how hard is it to make an unmaintainable mess" dimension. Dplyr/tidy code can be pasta, as can pandas, and there is really a whole new level of that given llm generated nonesense edited/tweaked by novices masquerading as seniors. Apropos this idea of a vs code competitor, I wish they would spend more effort on existing products. I find quarto frustratingly buggy and meanwhile see no reason to move my workflow from vscode to this new thing. Ymmv

aydyn 2y ago

Youre wrong. Python is outpacing R in usage. Every metric you can find proves it. R also has fundamental issues and lacks serious development.

stoperaticless 2y ago
s/serious/hyped
- aydyn 2y ago
  No. R fundamentally has not really improved in the past ~10 years. Do you know much about how R works? Also try: gsub('serious', 'hyped', x)
  - lottin 2y ago
    Maybe because it already does what it intends to do reasonably well? I mean, what do you think needs to be improved?
    - smcin 2y ago
      Here are 14 years of HN discussions/criticisms of R: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&query=R%20language&sort=byPopularity&type=story https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que... "Does what it intends to do reasonably well" is going to be widely subjective, depending on whether the user's use-case is statistical/life-sciences vs more general purpose coding and relying on many packages; prototyping/experimentation vs production code; whether the user uses base-R, or tidyverse/data.table, etc. Here are two of those many posts: * An opinionated view of the Tidyverse “dialect” of the R language (July 5, 2019) https://news.ycombinator.com/item?id=20362626 https://news.ycombinator.com/item?id=20362626 * The R programming language: The good, the bad, and the ugly (epatters.org, 2018) https://news.ycombinator.com/item?id=35571659 https://news.ycombinator.com/item?id=35571659 -> https://www.epatters.org/post/r-lang/ https://www.epatters.org/post/r-lang/
    - aydyn 2y ago
      If youre unironically asserting that R already does everything well enough Im not going to take you seriously.
      - lottin 2y ago
        I'm asking what needs to be improved, in your opinion. That's a normal follow-up question that you should be able to answer. Otherwise, why are you even commenting?
        aydyn 2y ago
        No you arent, youre clearly asking in a rhetorical way. Re-read your post. Any criticism brought up you'd dismiss. Heres one: lack of native 64 bit integers.
        lottin 2y ago
        No, I was just asking out of curiosity. You're overthinking too much.
        aydyn 2y ago
        No, you were clearly asserting that R already does everything needed. Stop trying to gaslight.
        lottin 2y ago
        You're crazy.
        dang 2y ago
        Please don't cross into personal attack or name-calling, and please especially avoid this sort of tit-for-tat spat with another user. It's way against the site guidelines and makes for boring reading. I know it's not always easy to extricate oneself but it's helpful to remember that the only way to 'win' is to stop. If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.
- openrisk 2y ago
  The issue is that even if you peel the hype (which is a fact), python is still far larger. If you check e.g. the journal of open source software (which does not have much ML/AI bias), most of the papers are python, with an occasional R and julia submission.
vixen99 2y ago
Not to dispute because I have no idea so I'll assume you're correct. But how many metrics did you find and how were they obtained? And how would you know they are representative of all R users?
- 0cf8612b2e1e 2y ago
  For whatever it is worth, the TIOBE index lists Python as #1, R at #21. Python is the first language many people are exposed to today. It has a library and tooling for every use case. https://www.tiobe.com/tiobe-index/ https://www.tiobe.com/tiobe-index/
  - kuhewa 2y ago
    R has a pretty particular use case though, Python use for statistical programming/data analysis would be an apples to apples comparison. People doing a coding 101 course in Python don't really count against the R user base.
    - aydyn 2y ago
      No one is disputing that R has usage in niche arenas.

boringg 2y ago

Im curious about the people who use R in big tech companies that you've worked at. Were the R users the people who had just come out of school and still working using their academic dev environment before weening off? I always found that was the group who used R - kind of a use what you are used to until it gets out of step with the remaining workflow. I also would say that the amount of R I see is far less than python.

disgruntledphd2 2y ago
So, (speaking as someone who started with R and now predominantly writes Python), I think there's a bunch of things going on here. 1. R is 100% better for analytics work and statistical modelling. There's just no contest. 2. Python is much, much better for data getting (APIs/scraping etc) and dealing with non table-like data. Again, there's basically no contest here. 3. Software engineers hate R (in most cases), which means that it's easier to hand over work for production in Python. This leads to a situation where it looks like most of the prod-level work is being done in Python, but if you look under the covers you'll discover that most prototyping/analysis/exploration is done in R and then ported to Python if it works. Like, Python is a great language for lots of things, but it's pretty terrible for exploratory DS work (pandas is like the worst features of base R and base Python mashed together in an unholy hybrid). There's also the fact that all the NN stuff is predominantly Python, so lots of companies believe that they need Python people, which reinforces the stereotype. And finally, while I love R, Python has more guardrails, and it's harder to make an unmaintainable mess with it (relative to R). Particularly when people use all the various lazy evaluation packages that the tidyverse has used over the past decade (I once maintained a codebase that used all of these in different places, it was not a fun experience).
- greentxt 2y ago
  One of the better comments in this thread, I would only qualify that different levels of ability mediate much of the "how hard is it to make an unmaintainable mess" dimension. Dplyr/tidy code can be pasta, as can pandas, and there is really a whole new level of that given llm generated nonesense edited/tweaked by novices masquerading as seniors. Apropos this idea of a vs code competitor, I wish they would spend more effort on existing products. I find quarto frustratingly buggy and meanwhile see no reason to move my workflow from vscode to this new thing. Ymmv