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I was expecting a rant, but the OP's article is actually very thoughtful. He definitely knows what he's talking about. The thing about R, for me and many other

I was expecting a rant, but the OP's article is actually very thoughtful. He definitely knows what he's talking about. The thing about R, for me and many others, is that it's very much an everyday grind language. Especially with Rstudio, its natural domain is as one of "notebook" languages like python, julia, matlab, and mathematica but with a more clear focus towards the tasks of data-analysis. I just tell the BI-tool people that R is excel on 'roids. R frustrates me a lot, however. But I think the frustration comes out of the fact that when I am using R and get stuck, I am always in the middle of doing something that I need to get done and I don't feel like diving into a long "vignette". Moreover, the documentation is usually too terse and generalized for me to just understand it immediately. Even though I've been using R for years (albeit in fits and starts rather than continuously), there are things about it that I've just never picked up-- I just DON'T KNOW (or care) what F S3 and S4 mean. Unlike the OP, who clearly knows more R than myself, I grit my teeth when I am looking at docs and see the "..." in the arg list. I suspect that this is part of the heritage from R's beginnings. I once tried to read John Chamber's book but found the presentation complete ass-backwards and impractical for my immediate needs. The Tidyverse has been great, it's far more consistent and ggplot is a kick-ass tool to have in your box. The drawback is that it makes Base-R seem really alien and if you want to be good at R, you have to know more than just the Tidyverse, IMHO.

clove 5y ago
I've used R for 19 years and do not have any other programming language ability. I am curious: What is frustrating to you about R relative to other languages?
- vharuck 5y ago
  In my experience: - It has a bunch of different types of classes, and they all behave differently. Debugging isn't awful, but it's harder than it should be. Also, the documentation isn't clear about which classes to use. - A lot of the workhorse functions suffer from parameter glut. Despite having different kinds of classes, almost all functions expect plain vectors. Packages like survival show how objects make it easier to read code, reuse data, and validate data. Without the base packages doing it more, everyone's chosen their own systems. The community's been gravitating to organizing "objects" as rows in tables (i.e. tidy). - The way a function uses an argument might surprisingly change based on other arguments given (e.g., `binom.test`). And then the documentation won't have examples for the different use cases. - Most users don't have the time or desire to become better R programmers. They have other work to do. For my own work, I write packages with custom classes, functions, and template documents. For collaboration, I keep things very plain and rarely go beyond dplyr; very often, the script goes between two steps executed in a GUI software.
- rvanlaar 5y ago
  I'm not OP. To me, it's the tooling around it. Everything is done in R-studio and it's focus is to generate statistical documents. The result is a sub optimum solution. It lacks good tooling around installing and running R programs. R programs don't import, they include. It doesn't make it more readable. R-studio is very Emacs like in the sense that it just lacks a decent editor. Due to R-studio being the default, there's not much support for other editors.
  - Mikeb85 5y ago
    > Due to R-studio being the default, there's not much support for other editors. But RStudio is amazing... Easily best environment I've used for any programming language (well, except Pharo).
  - lottin 5y ago
    Emacs has had excellent R support since much before R-studio came around. In fact to me R-studio has always felt like a stand-alone implementation of ESS (minus Emacs).
  - kafkaIncarnate 5y ago
    I use Vim with the R command line wrapped around Makefiles. I don't even have RStudio installed. Works great. I can even pop up an interactive R command prompt session and do whatever I want in it, even quick ggplot2 graphs. Help shows up just as you would expect, and plots pop up in new windows. RStudio is much less advanced than people think it is, it's really just managing R's windows for you and doing generic IDE work. R is doing all the heavy lifting. If you're wanting a more "import" like thing you might want to look into making R packages instead of scripts. You don't have to submit them to CRAN, and you can execute them pretty simply on the R command line as well. That being said, it's really not an OOP or software development tool. It's definitely geared toward data science, but you can automate that very well for generating graphs automatically and reporting for whatever reason needed.
    - racl101 5y ago
      Do you have notes or documentation on how to get this working without RStudio? Preferably on a Macbook?
- svnt 5y ago
  In decades I have not encountered any development environment where the obscurity of error message presentation can touch R. If one uses other languages or build environments the error messages can frequently be used to diagnose the issue. In R they default to just vomiting some internal exception often with no context, and I can count the times I have encountered helpful or even seemingly deliberately constructed error messaging in single-place base five. Even kernel development is in some sense better because at least there you are in context and the layers are traversable. Seemingly one of the primary skills of an R programmer is serving as an informal database of “what the fuck does this mean?” when the issue is something trivially detectable like passing a list vs a vector.
- crispyambulance 5y ago
  FWIW, I do prefer R to all other "notebook" languages. It has everything I need for answering questions about data, working with files, text, and visualization. Libraries that do everything I could imagine are easily available. For me it's a pragmatic workhorse tool that I use and aside from frequently getting frustrated with the task at hand, it has never failed me in the end. I think R is much like a handheld power tool. I have no interest in diving deep into the workings of the tool because when I need to use a drill, for instance, I just need to drill holes and anything else is an annoying distraction (I realize that sounds bad!). I've also worked with Mathematica and JMP in the past. They're very capable, but not as good at general-purpose data-wrangling as R is today (given Rstudio, knitr, shiny, all the specialized libraries, and most especially the tidyverse).
epistasis 5y ago
The tidyverse docs are the only ones with the super frustrating ... of impenetrable gnostic "documentation" that I know of. In general the tidyverse documentation is horrible, almost as bad as typical Python docs, IMHO. Other parts of base R are wonderfully documented in my opinion.
- magnio 5y ago
  > almost as bad as typical Python docs I found numpy, scipy, pandas, and plotly docs to be quite clear and extensive. The only docs I have found to be confusing are matplotlib's and the Python standard library's. Not sure what packages you are referring to?
  - deleted 5y ago
    [deleted]
  - bscphil 5y ago
    On the other hand, I'm curious what you've found to be lacking about the standard library documentation. I've found it to be generally very thorough, in some cases fantastic, though there's an occasional weak point.
    - magnio 5y ago
      For me, the stdlib docs isn't lacking in material, but it is hard to navigate. I think that is partly because it mixes different types of documentations together (tutorial, reference, and changelog). They should split each module's docs into two pages: a tutorial with examples of the most common use-case of the module, and a reference listing all of the classes, methods, etc. of the module. Also, the built-in types are documented in one page, going from boolean to sequence types and even type annotations. Every Ctrl + F gives me 20 different results, which is annoying as hell.
- hadley 5y ago
  Do you have any specific examples that illustrate the general problem? I'd love to better understand what you're looking for in docs.

clove 5y ago

I've used R for 19 years and do not have any other programming language ability. I am curious: What is frustrating to you about R relative to other languages?

vharuck 5y ago
In my experience: - It has a bunch of different types of classes, and they all behave differently. Debugging isn't awful, but it's harder than it should be. Also, the documentation isn't clear about which classes to use. - A lot of the workhorse functions suffer from parameter glut. Despite having different kinds of classes, almost all functions expect plain vectors. Packages like survival show how objects make it easier to read code, reuse data, and validate data. Without the base packages doing it more, everyone's chosen their own systems. The community's been gravitating to organizing "objects" as rows in tables (i.e. tidy). - The way a function uses an argument might surprisingly change based on other arguments given (e.g., `binom.test`). And then the documentation won't have examples for the different use cases. - Most users don't have the time or desire to become better R programmers. They have other work to do. For my own work, I write packages with custom classes, functions, and template documents. For collaboration, I keep things very plain and rarely go beyond dplyr; very often, the script goes between two steps executed in a GUI software.
rvanlaar 5y ago
I'm not OP. To me, it's the tooling around it. Everything is done in R-studio and it's focus is to generate statistical documents. The result is a sub optimum solution. It lacks good tooling around installing and running R programs. R programs don't import, they include. It doesn't make it more readable. R-studio is very Emacs like in the sense that it just lacks a decent editor. Due to R-studio being the default, there's not much support for other editors.
- Mikeb85 5y ago
  > Due to R-studio being the default, there's not much support for other editors. But RStudio is amazing... Easily best environment I've used for any programming language (well, except Pharo).
- lottin 5y ago
  Emacs has had excellent R support since much before R-studio came around. In fact to me R-studio has always felt like a stand-alone implementation of ESS (minus Emacs).
- kafkaIncarnate 5y ago
  I use Vim with the R command line wrapped around Makefiles. I don't even have RStudio installed. Works great. I can even pop up an interactive R command prompt session and do whatever I want in it, even quick ggplot2 graphs. Help shows up just as you would expect, and plots pop up in new windows. RStudio is much less advanced than people think it is, it's really just managing R's windows for you and doing generic IDE work. R is doing all the heavy lifting. If you're wanting a more "import" like thing you might want to look into making R packages instead of scripts. You don't have to submit them to CRAN, and you can execute them pretty simply on the R command line as well. That being said, it's really not an OOP or software development tool. It's definitely geared toward data science, but you can automate that very well for generating graphs automatically and reporting for whatever reason needed.
  - racl101 5y ago
    Do you have notes or documentation on how to get this working without RStudio? Preferably on a Macbook?
svnt 5y ago
In decades I have not encountered any development environment where the obscurity of error message presentation can touch R. If one uses other languages or build environments the error messages can frequently be used to diagnose the issue. In R they default to just vomiting some internal exception often with no context, and I can count the times I have encountered helpful or even seemingly deliberately constructed error messaging in single-place base five. Even kernel development is in some sense better because at least there you are in context and the layers are traversable. Seemingly one of the primary skills of an R programmer is serving as an informal database of “what the fuck does this mean?” when the issue is something trivially detectable like passing a list vs a vector.
crispyambulance 5y ago
FWIW, I do prefer R to all other "notebook" languages. It has everything I need for answering questions about data, working with files, text, and visualization. Libraries that do everything I could imagine are easily available. For me it's a pragmatic workhorse tool that I use and aside from frequently getting frustrated with the task at hand, it has never failed me in the end. I think R is much like a handheld power tool. I have no interest in diving deep into the workings of the tool because when I need to use a drill, for instance, I just need to drill holes and anything else is an annoying distraction (I realize that sounds bad!). I've also worked with Mathematica and JMP in the past. They're very capable, but not as good at general-purpose data-wrangling as R is today (given Rstudio, knitr, shiny, all the specialized libraries, and most especially the tidyverse).

epistasis 5y ago

The tidyverse docs are the only ones with the super frustrating ... of impenetrable gnostic "documentation" that I know of. In general the tidyverse documentation is horrible, almost as bad as typical Python docs, IMHO. Other parts of base R are wonderfully documented in my opinion.

magnio 5y ago
> almost as bad as typical Python docs I found numpy, scipy, pandas, and plotly docs to be quite clear and extensive. The only docs I have found to be confusing are matplotlib's and the Python standard library's. Not sure what packages you are referring to?
- deleted 5y ago
  [deleted]
- bscphil 5y ago
  On the other hand, I'm curious what you've found to be lacking about the standard library documentation. I've found it to be generally very thorough, in some cases fantastic, though there's an occasional weak point.
  - magnio 5y ago
    For me, the stdlib docs isn't lacking in material, but it is hard to navigate. I think that is partly because it mixes different types of documentations together (tutorial, reference, and changelog). They should split each module's docs into two pages: a tutorial with examples of the most common use-case of the module, and a reference listing all of the classes, methods, etc. of the module. Also, the built-in types are documented in one page, going from boolean to sequence types and even type annotations. Every Ctrl + F gives me 20 different results, which is annoying as hell.
hadley 5y ago
Do you have any specific examples that illustrate the general problem? I'd love to better understand what you're looking for in docs.