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RStudio: Integrated development environment (IDE) for R

99 points by _benj 3y ago

rrjjww 3y ago
As someone who learned most of my initial coding abilities through R and RStudio in a data science context, and since moved on to more “standard” languages and IDEs, I’ve yet to find anything that comes close to the flexibility and integration of RStudio for hacking together data analytics. VS Code/Python has made some major improvements in the past couple years but it’s still very clunky compared to the ease of running R code line by line without having to start up a debug instance. And now with copilot the most frustrating parts of R (such as remembering all the Tidyverse syntax) have been abstracted away.
- qudat 3y ago
  My partner does a lot of biostats in RStudio and I really think it breds terrible habits. Instead of categorizing code by files, everything is shoved into massive files. Instead of running a file top-to-bottom, code is run out-of-order which makes the code organization and flow of a program a complete disaster. There is something to be said about running and processing large CSVs and keeping that in memory while running other parts of the program as well as having clickable access to all the dataframes loaded into memory.
  - mjhay 3y ago
    There's nothing about RStudio that encourages big single files or writing huge unstructured scripts. RStudio is a pretty good IDE, and R is a highly expressive functional-first [0] language. R was heavily influenced by Scheme, and has its own powerful metaprogramming [1] system - which is used to great effect in Tidyverse[2] libraries to make APIs that are nicer and convenient than anything reasonably practical in Python. The problem with a lot of end-user R code is that it is written by statisticians, not programmers. They'd write the same garbage and huge scripts in Python (trust me, I know). [0] http://adv-r.had.co.nz/Functional-programming.html http://adv-r.had.co.nz/Functional-programming.html [1] https://adv-r.hadley.nz/metaprogramming.html https://adv-r.hadley.nz/metaprogramming.html [2] https://www.tidyverse.org/ https://www.tidyverse.org/
    - cameronh90 3y ago
      I agree that RStudio isn't too awful, but the packaging management and reproducibility situation in R is dire, even compared to Python. I have to deal with getting code from data scientists into production, and simply getting it to run outside of their mutant local environment can take days. Things are starting to get a bit better with packrat initially and now renv/pak/rig and the like, but most DS haven't heard of them, and major breakages between minor library versions are still commonplace, as are undocumeted system library dependencies. Then there is the whole stringsAsFactors nightmare, thankfully slowly on its way out but still around causing occasional catastrophic breakage. There are lots of nice things about R, but it makes it very easy to shoot yourself in the foot.
      - mjhay 3y ago
        Yeah, the package management situation is a big weak spot. There are some issues with renv, but it is usable. It definitely helps to keep a lid on the number of dependencies, and for God's sake never pull anything in from Bioconductor. IMO, new code should always prefer Tidyverse libs for basic stuff, and avoid relying on the ancient and warty standard library. All that said, I still greatly prefer it over Python for DS work.
      - levocardia 3y ago
        >I agree that RStudio isn't too awful, but the packaging management and reproducibility situation in R is dire, even compared to Python. I've had exactly the opposite experience. For R, I download R and install it, and download Rstudio and install it. Then when I need a new package I just install.packages("coolnewpackage") and it just works (TM). Occasionally I get info messages about packages being built in newer versions of R, and once a year or so I eventually get around to looking up how to use the updateR() function, but in five years of doing biostats in R I can't remember a single time I had a dependency issue. Python, on the other hand, is a nightmare. Conda makes life a lot easier, but it is not easy to learn if you are not a software engineer (remember, R was made not just by statisticians, but for them as well). For many projects, my Python flow was something like... Try creating a new conda env with the packages I think I need. Try starting the project, oops I don't have spyder-kernels installed. Oh, and my environment isn't compatible with it. How about just running it in VScode? Well now I don't have my variable explorer. How about Jupyter? How do I get Jupyter to find my conda env again? Oh wait I need this other library it's only on conda-forge, and then the conda environment solver fails. I guess I'll start from scratch with a new conda env, and maybe after several trial-and-error sessions of carefully composing the correct "conda create -n ..." incantation in a text editor before copy-pasting them to the command line, I might get the environment I need up and running, after conda finishes its 10-minute compatibility search and downloads 80 GB of python libraries. And using conda is the easy way of doing it! Don't even get me started on pip and venv...
  - cjk2 3y ago
    This is the defacto standard way of operating it I understand, which is mostly just hacking at stuff in small chunks until it sort of works and leaving comments throughout it with "run this bit on Tuesdays only". I recently had to inherit someone's R stuff and I had to learn R and fix it all. It now runs from a makefile repeatably. Anyway it could be worse. It could be Minitab.
  - ellisv 3y ago
    > Instead of categorizing code by files, everything is shoved into massive files. That's not really RStudio's fault. It is just how many people use R and were taught. > code is run out-of-order which makes the code organization and flow of a program a complete disaster. In my experience, with R Markdown, this is untrue. I see Jupyter Notebooks with cells run out of order much more often.
    - madcaptenor 3y ago
      I have done a lot in R Markdown, and the project I'm currently working on has me mostly working in Databricks notebooks (which are very similar to Jupyter notebooks). My execution gets out of order a lot more often in Databricks.
  - bachmeier 3y ago
    > Instead of running a file top-to-bottom, code is run out-of-order which makes the code organization and flow of a program a complete disaster. That's more a REPL issue than specific to a particular language. It's the tradeoff you make. I write my R programs in Geany and then run the whole thing using Rscript. That gives me a clean environment on every run.
- goosedragons 3y ago
  Emacs + ESS? Way more flexible. Maybe less integration because many of the big R package devs work for Posit. RStudio has a lot of superfluous junk in the UI I just don't need or care about.
  - kqr 3y ago
    I've used ESS for the past few years and recently tried using RStudio when I'm on Windows. For my purposes, which is just a little industrial statistics on the side, they are remarkably similar. I feel right at home in either!
- lylejantzi3rd 3y ago
  > I’ve yet to find anything that comes close to the flexibility and integration of RStudio for hacking together data analytics. Is there a good demo or video you can point to that shows this? I have no experience with R, RStudio, or data science, but you've piqued my interest.
  - ellisv 3y ago
    Any of David Robinson's (or anyone else's) Tidy Tuesday videos. https://www.youtube.com/@safe4democracy/featured https://www.youtube.com/@safe4democracy/featured
- Kalanos 3y ago
  jupyter
- silveraxe93 3y ago
  This works out of the box in VSCode? Just open a .py file, then select the snippet of code you want to run and cmd+enter It will open a new REPL for you (using your selected interpreter) the first time, and after that all commands are run in that same one.
  - wodenokoto 3y ago
    RStudio is just way better at choosing what code to send (if you only send the line the cursor rests on you’re gonna have a bad time. VSCode is a bit better than that but not great. Also, where does your plots get drawn when you use this? RStudio just works in this regards)
- ubiquitination 3y ago
  I agree - I teach statistics at a University and there is really no alternative to Rstudio for working with R. This is especially true considering that the vast majority of folk using R (in my field) have no prior programming experience. Downloading R, Vscode, downloading some R plugin, getting them to talk to each other, and only then starting to learn R - isn't very straightforward. It's also remarkably consistent on different operating systems - something to consider when half the students are on windows, half on macos...
  - bachmeier 3y ago
    RStudio Server on a Digital Ocean instance made my life a lot easier. Students fire up a browser, log in, and they're using R with all the packages. It was horrible when students ran R on their own machines back in the old days. Most of the questions I got were tech support rather than related to the material. And these days it has good Python support too.
- dcreater 3y ago
  Jupiter (ipynb) notebooks in vs code.
- jurimasa 3y ago
  If you work with Python, Spyder comes really, really close and is way better than jupyter
- RobinL 3y ago
  It looks like, as far as I can tell, VS Code doesn't support the interactive window for working in R, which was a bit of a surprise to me when i looked it up. The python interactive window has pretty much fully replaced my use of jupyter, since it gives you notebook-style output without the annoyance of the notebook format. My usual workflow is highlighting lines of code and shift-enter to execute (there's also a cells syntax). I'm surprised by this because it _is_ possible to use R in Jupyter (although I never really liked the experience, R Studio was far superior).
  - yabbs 3y ago
    ? Yes it does.
    - aiisjustanif 3y ago
      Please supply references for the audience.
    - RobinL 3y ago
      I'm specifically referring to: https://code.visualstudio.com/docs/python/jupyter-support-py https://code.visualstudio.com/docs/python/jupyter-support-py The support for R looks a bit different (to me at least?): https://code.visualstudio.com/docs/languages/r https://code.visualstudio.com/docs/languages/r In the screenshot the window on the right does not look comparable to the output in a jupyter notebook. It looks more like a standard terminal. e.g. does it support interactive charts, html tables etc? The Python interactive window uses the ipykernel package to allow rich outputs like that. I still might be wrong and would like to be corrected on this, since it would mean R support in VS Code is now better than I thought (I haven't tried it fora. while)
      - ZunarJ5 3y ago
        I use r in a Jupyter Notebook in VS via IRKernel. It's a gem.
        3y ago
- jakupovic 3y ago
  cat, grep, sort and awk come pretty close :)
- dcchuck 3y ago
  Came here to share that same experience. RStudio truly made me feel "close" to the data.
- ivansavz 3y ago
  An alternative in the Python world that is definitely worth looking into is the JupyterLab Desktop app, which is a standalone installer that is cross-platform and works great for beginners (no command line needed): https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-ov-file#jupyterlab-desktop https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-... See my other comment in the main thread with more info.
ellisv 3y ago
Are we just submitting GitHub repos as posts now?
- JR1427 3y ago
  I was thinking the same. R studio is certainly not new, either.
- forgotpwd16 3y ago
  Hasn't this been happening ever since GitHub opened?
- wodenokoto 3y ago
  The comment section is the most interesting after all, so why not link to the source instead of digging up a blog post no one will read anyway?
gdevenyi 3y ago
If I complain here will they fix my year old bug? https://github.com/rstudio/rstudio/issues/12508 https://github.com/rstudio/rstudio/issues/12508
- gdevenyi 3y ago
  The answer, it turns out, was yes!
- jmcphers 3y ago
  Can't make any promises -- our dev team is pretty small! -- but it's been flagged for triage.
- cdrv 3y ago
  This particular issue should be resolved in the latest daily builds of RStudio. The underlying issue here was a conda patch included in the conda-provided builds of R, which interfered with the way RStudio attempted to load R. Please see https://github.com/rstudio/rstudio/issues/13184#issuecomment-1992709588 https://github.com/rstudio/rstudio/issues/13184#issuecomment... for more details.
fumeux_fume 3y ago
It’s really nice to have everything you need in one spot. Plus it’ll run on any OS and is free. I started learning how to program with C++ back in the early 2000s which required Windows and a Visual Studio license and it was still a pain to get stuff done. Whether it’s RStudio or Jupyter there’s really never been a better time to start picking up a language and building something useful. Three cheers for the creators, maintainers and community who support tools like this.
- tetris11 3y ago
  Freemium is what they ("Posit") are pivoting to now. https://posit.co/pricing/individual-products/ https://posit.co/pricing/individual-products/ If you want a Rstudio server to host for a research group containing more than 5 people, talk to their sales Rep. Otherwise each person will need to host their own Rstudio server side-by-side on the same machine. Jupyter and JupyterHub is the way forward. Especially if they get multi-kernel notebooks mainlined (read: what Org-Mode has been doing for decades)
  - jmcphers 3y ago
    That pricing sheet is for Posit Workbench; RStudio Server[0] can host as many people as you have the compute for, and it's free and open source. It does only support one session per user, but might meet the needs of a small research group. [0] https://posit.co/download/rstudio-server/ https://posit.co/download/rstudio-server/
wjholden 3y ago
The killer feature of RStudio for me is RMarkdown. I composed almost all my homeworks in grad school using RMarkdown in RStudio. You get LaTeX whenever you need it, code (I usually use it for R or Julia), and markdown for ordinary text. The kable function renders tables nicely from data frames and ggplot2 creates beautiful plots. Mathematica and Jupyter have a few advantages, but overall I'm very happy with RStudio.
- minimaxir 3y ago
  RMarkdown in RStudio was the killer feature, until the VSCode R extension matured. Not only does it support RMarkdown, it adds a ton of features RStudio doesn't have and runs a lot faster. https://github.com/REditorSupport/vscode-R/wiki/R-Markdown https://github.com/REditorSupport/vscode-R/wiki/R-Markdown For my uses, it replaced RStudio 100% of the time.
  - adr1an 3y ago
    Can you use quarto in vscode? It's the next magic from Posit.co
    - minimaxir 3y ago
      Yes, quarto has native support for VSCode: https://quarto.org/docs/get-started/hello/vscode.html https://quarto.org/docs/get-started/hello/vscode.html There isn't much advantage to using it over RMarkdown for R, IMO.
  - dr_kiszonka 3y ago
    Thanks for the link! Is it possible to display plots inline like in notebooks? (The screenshot shows a plot in a preview pane.)
    - minimaxir 3y ago
      Unfortunately no. (tbh I don't like that feature in RStudio anyways: it makes it longer to scroll through large notebooks, and ggsave is better at rendering charts than R's native rendering) For knitting, you can use Markdown image links.
mightyham 3y ago
RStudio and the R language are a couple of my absolute favorite pieces of software. While I'm a software engineer by trade, every once in a while I need to do some data analysis work and throwing together a notebook in RStudio always makes me feel like I'm using a cheat code. For simple tasks, everything is incredibly seamless, plus coworkers who are unfamiliar with R are usually impressed by how nice ggplot visualizations can look.
lvl102 3y ago
I enjoy RStudio but the best feature of R is data.table. It’s simply unmatched.
- ProjectArcturis 3y ago
  Once you climb that steep learning curve, absolutely.
- th0ma5 3y ago
  Polars is faster? Data.table was a pioneering speed improvement at one point for sure.
  - lvl102 3y ago
    It is but if we are talking speed, I’d just opt for RAPIDS.
uptownfunk 3y ago
I think one of the most underrated pieces of software in modern history. Absolutely brilliant. Huge fan. I am glad to see it getting love. I’ve moved on from data science in a professional capacity but for some pet projects of mine it has been indispensable. I think managing the namespace was one non trivial concern (which may be resolved in modern versions). Otherwise very well built for data science applications. Interesting that it didn’t catch on for LLM training - I think a missed opportunity.
dclaw 3y ago
Ahh cool, now r-studio brings up this instead of the 24 year old data recovery program.... :-(
- stonogo 3y ago
  RStudio is thirteen years old so I'm not sure what changed that makes the search results different "now"
matttproud 3y ago
I'm about as old school as you can get with preference for CLI and simple text-oriented development environments. I recently picked up R again for a long-term data science project (https://matttproud.com/blog/posts/teaser-weather-temp-representation.html https://matttproud.com/blog/posts/teaser-weather-temp-repres...) after having not used it since university. In spite of a fair bit of annoyance with the R language (https://matttproud.com/blog/posts/rant-and-r-melt-function.html https://matttproud.com/blog/posts/rant-and-r-melt-function.h...), I found RStudio to make the prototyping process with R actually tolerable. Big kudos to Posit and the R community for RStudio. There are a couple of things I would love for the R ecosystem: project scaffolding to do bulk data generation (e.g., from continuously generated data sets). What's the best way to do this: makefiles, or what? I have a relatively short entrypoint R file that sources other leaf files to run specific analyses, but it makes the software engineer inside of me want to curl up and die.
- mjhay 3y ago
  reshape2 (where `melt` is from) has been deprecated for some time, and for pretty good reasons. Try dplyr and tidyr instead - they are much nicer and modern. The equivalent of melt would be pivot_longer. For packaging, renv is the usual choice. I wouldn't structure the package as a bunch of scripts with an entrypoint. Just write functions as you would in other languages, and keep any specific analysis script small. https://tidyr.tidyverse.org/ https://tidyr.tidyverse.org/
melondonkey 3y ago
Weird one minute it feels like the internet is screaming that I’m an out-of-touch dinosaur for using R and the next a simple link to its most popular IDE makes the front of HN.
ivansavz 3y ago
The closest Python equivalent to RStudio is the JupyterLab Desktop app[1,2], which I highly recommend. I've entirely switched to using it for teaching, and it is a godsend, since it works the same way across platforms (win/mac/linux), installs its own Python interpreter independent of any system Python the student might have, and even comes with NumPy/SciPy/Pandas/Seaborn/statsmodels already installed, which makes it possible for me to skip the `pip ...` or `conda ...` instructions altogether. Between the standalone desktop app, and the convenience of running JypyterLab in the cloud thanks to https://mybinder.org/ https://mybinder.org/ links, there is now a smooth path for beginners getting into stats/ML/data science: (1) read notebook on github or nbviewer, (2) run notebooks in the cloud via mybinder links, (3) install JupyterLab Desktop app, (4) learn to install Python+env-manager via command line. Previously, new learners were forced to jump straight to (4), but now there are logical steps along the way! [1] https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-ov-file#jupyterlab-desktop https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-... [2] https://blog.jupyter.org/jupyterlab-desktop-app-now-available-b8b661b17e9a https://blog.jupyter.org/jupyterlab-desktop-app-now-availabl...
- wodenokoto 3y ago
  Is it different from running through the web server? I found it to have a lot of potential but not there yet
  - ivansavz 3y ago
    It's the same stack (jupyterlab server backend + web frontend) but wrapped as an electron app. Yeah for sure when I use RStudio it seems much more polished, but I guess my attachment to (and comfort with) Python still makes it worthwhile to use JupterLab rather than switch to RStudio.
Kalanos 3y ago
i use jupyter a lot for python. i occasionally have to use rstudio for bioinformatics. the ux is much, much worse. just haven't bothered to get the R kernel for jupyter working.
rubslopes 3y ago
Is there a way to visualize a dataframe like a spreadsheet, as RStudio does, but for VSCode?
HayBale 3y ago
Ahhh I started my programming with Rstudio. Since than I changed to Emacs with ESS. Rstudio is nice but lacks a lot of nice things from something bigger.
jurimasa 3y ago
If you work with Python, Spyder comes really, really close to RStudio and is way better than jupyter

99 points by _benj 3y ago

As someone who learned most of my initial coding abilities through R and RStudio in a data science context, and since moved on to more “standard” languages and IDEs, I’ve yet to find anything that comes close to the flexibility and integration of RStudio for hacking together data analytics. VS Code/Python has made some major improvements in the past couple years but it’s still very clunky compared to the ease of running R code line by line without having to start up a debug instance. And now with copilot the most frustrating parts of R (such as remembering all the Tidyverse syntax) have been abstracted away.

qudat 3y ago
My partner does a lot of biostats in RStudio and I really think it breds terrible habits. Instead of categorizing code by files, everything is shoved into massive files. Instead of running a file top-to-bottom, code is run out-of-order which makes the code organization and flow of a program a complete disaster. There is something to be said about running and processing large CSVs and keeping that in memory while running other parts of the program as well as having clickable access to all the dataframes loaded into memory.
- mjhay 3y ago
  There's nothing about RStudio that encourages big single files or writing huge unstructured scripts. RStudio is a pretty good IDE, and R is a highly expressive functional-first [0] language. R was heavily influenced by Scheme, and has its own powerful metaprogramming [1] system - which is used to great effect in Tidyverse[2] libraries to make APIs that are nicer and convenient than anything reasonably practical in Python. The problem with a lot of end-user R code is that it is written by statisticians, not programmers. They'd write the same garbage and huge scripts in Python (trust me, I know). [0] http://adv-r.had.co.nz/Functional-programming.html http://adv-r.had.co.nz/Functional-programming.html [1] https://adv-r.hadley.nz/metaprogramming.html https://adv-r.hadley.nz/metaprogramming.html [2] https://www.tidyverse.org/ https://www.tidyverse.org/
  - cameronh90 3y ago
    I agree that RStudio isn't too awful, but the packaging management and reproducibility situation in R is dire, even compared to Python. I have to deal with getting code from data scientists into production, and simply getting it to run outside of their mutant local environment can take days. Things are starting to get a bit better with packrat initially and now renv/pak/rig and the like, but most DS haven't heard of them, and major breakages between minor library versions are still commonplace, as are undocumeted system library dependencies. Then there is the whole stringsAsFactors nightmare, thankfully slowly on its way out but still around causing occasional catastrophic breakage. There are lots of nice things about R, but it makes it very easy to shoot yourself in the foot.
    - mjhay 3y ago
      Yeah, the package management situation is a big weak spot. There are some issues with renv, but it is usable. It definitely helps to keep a lid on the number of dependencies, and for God's sake never pull anything in from Bioconductor. IMO, new code should always prefer Tidyverse libs for basic stuff, and avoid relying on the ancient and warty standard library. All that said, I still greatly prefer it over Python for DS work.
    - levocardia 3y ago
      >I agree that RStudio isn't too awful, but the packaging management and reproducibility situation in R is dire, even compared to Python. I've had exactly the opposite experience. For R, I download R and install it, and download Rstudio and install it. Then when I need a new package I just install.packages("coolnewpackage") and it just works (TM). Occasionally I get info messages about packages being built in newer versions of R, and once a year or so I eventually get around to looking up how to use the updateR() function, but in five years of doing biostats in R I can't remember a single time I had a dependency issue. Python, on the other hand, is a nightmare. Conda makes life a lot easier, but it is not easy to learn if you are not a software engineer (remember, R was made not just by statisticians, but for them as well). For many projects, my Python flow was something like... Try creating a new conda env with the packages I think I need. Try starting the project, oops I don't have spyder-kernels installed. Oh, and my environment isn't compatible with it. How about just running it in VScode? Well now I don't have my variable explorer. How about Jupyter? How do I get Jupyter to find my conda env again? Oh wait I need this other library it's only on conda-forge, and then the conda environment solver fails. I guess I'll start from scratch with a new conda env, and maybe after several trial-and-error sessions of carefully composing the correct "conda create -n ..." incantation in a text editor before copy-pasting them to the command line, I might get the environment I need up and running, after conda finishes its 10-minute compatibility search and downloads 80 GB of python libraries. And using conda is the easy way of doing it! Don't even get me started on pip and venv...
- cjk2 3y ago
  This is the defacto standard way of operating it I understand, which is mostly just hacking at stuff in small chunks until it sort of works and leaving comments throughout it with "run this bit on Tuesdays only". I recently had to inherit someone's R stuff and I had to learn R and fix it all. It now runs from a makefile repeatably. Anyway it could be worse. It could be Minitab.
- ellisv 3y ago
  > Instead of categorizing code by files, everything is shoved into massive files. That's not really RStudio's fault. It is just how many people use R and were taught. > code is run out-of-order which makes the code organization and flow of a program a complete disaster. In my experience, with R Markdown, this is untrue. I see Jupyter Notebooks with cells run out of order much more often.
  - madcaptenor 3y ago
    I have done a lot in R Markdown, and the project I'm currently working on has me mostly working in Databricks notebooks (which are very similar to Jupyter notebooks). My execution gets out of order a lot more often in Databricks.
- bachmeier 3y ago
  > Instead of running a file top-to-bottom, code is run out-of-order which makes the code organization and flow of a program a complete disaster. That's more a REPL issue than specific to a particular language. It's the tradeoff you make. I write my R programs in Geany and then run the whole thing using Rscript. That gives me a clean environment on every run.
goosedragons 3y ago
Emacs + ESS? Way more flexible. Maybe less integration because many of the big R package devs work for Posit. RStudio has a lot of superfluous junk in the UI I just don't need or care about.
- kqr 3y ago
  I've used ESS for the past few years and recently tried using RStudio when I'm on Windows. For my purposes, which is just a little industrial statistics on the side, they are remarkably similar. I feel right at home in either!
lylejantzi3rd 3y ago
> I’ve yet to find anything that comes close to the flexibility and integration of RStudio for hacking together data analytics. Is there a good demo or video you can point to that shows this? I have no experience with R, RStudio, or data science, but you've piqued my interest.
- ellisv 3y ago
  Any of David Robinson's (or anyone else's) Tidy Tuesday videos. https://www.youtube.com/@safe4democracy/featured https://www.youtube.com/@safe4democracy/featured
Kalanos 3y ago
jupyter
silveraxe93 3y ago
This works out of the box in VSCode? Just open a .py file, then select the snippet of code you want to run and cmd+enter It will open a new REPL for you (using your selected interpreter) the first time, and after that all commands are run in that same one.
- wodenokoto 3y ago
  RStudio is just way better at choosing what code to send (if you only send the line the cursor rests on you’re gonna have a bad time. VSCode is a bit better than that but not great. Also, where does your plots get drawn when you use this? RStudio just works in this regards)
ubiquitination 3y ago
I agree - I teach statistics at a University and there is really no alternative to Rstudio for working with R. This is especially true considering that the vast majority of folk using R (in my field) have no prior programming experience. Downloading R, Vscode, downloading some R plugin, getting them to talk to each other, and only then starting to learn R - isn't very straightforward. It's also remarkably consistent on different operating systems - something to consider when half the students are on windows, half on macos...
- bachmeier 3y ago
  RStudio Server on a Digital Ocean instance made my life a lot easier. Students fire up a browser, log in, and they're using R with all the packages. It was horrible when students ran R on their own machines back in the old days. Most of the questions I got were tech support rather than related to the material. And these days it has good Python support too.
dcreater 3y ago
Jupiter (ipynb) notebooks in vs code.
jurimasa 3y ago
If you work with Python, Spyder comes really, really close and is way better than jupyter
RobinL 3y ago
It looks like, as far as I can tell, VS Code doesn't support the interactive window for working in R, which was a bit of a surprise to me when i looked it up. The python interactive window has pretty much fully replaced my use of jupyter, since it gives you notebook-style output without the annoyance of the notebook format. My usual workflow is highlighting lines of code and shift-enter to execute (there's also a cells syntax). I'm surprised by this because it _is_ possible to use R in Jupyter (although I never really liked the experience, R Studio was far superior).
- yabbs 3y ago
  ? Yes it does.
  - aiisjustanif 3y ago
    Please supply references for the audience.
  - RobinL 3y ago
    I'm specifically referring to: https://code.visualstudio.com/docs/python/jupyter-support-py https://code.visualstudio.com/docs/python/jupyter-support-py The support for R looks a bit different (to me at least?): https://code.visualstudio.com/docs/languages/r https://code.visualstudio.com/docs/languages/r In the screenshot the window on the right does not look comparable to the output in a jupyter notebook. It looks more like a standard terminal. e.g. does it support interactive charts, html tables etc? The Python interactive window uses the ipykernel package to allow rich outputs like that. I still might be wrong and would like to be corrected on this, since it would mean R support in VS Code is now better than I thought (I haven't tried it fora. while)
    - ZunarJ5 3y ago
      I use r in a Jupyter Notebook in VS via IRKernel. It's a gem.
      - 3y ago
jakupovic 3y ago
cat, grep, sort and awk come pretty close :)
dcchuck 3y ago
Came here to share that same experience. RStudio truly made me feel "close" to the data.
ivansavz 3y ago
An alternative in the Python world that is definitely worth looking into is the JupyterLab Desktop app, which is a standalone installer that is cross-platform and works great for beginners (no command line needed): https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-ov-file#jupyterlab-desktop https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-... See my other comment in the main thread with more info.

ellisv 3y ago

Are we just submitting GitHub repos as posts now?

JR1427 3y ago
I was thinking the same. R studio is certainly not new, either.
forgotpwd16 3y ago
Hasn't this been happening ever since GitHub opened?
wodenokoto 3y ago
The comment section is the most interesting after all, so why not link to the source instead of digging up a blog post no one will read anyway?

gdevenyi 3y ago

If I complain here will they fix my year old bug? https://github.com/rstudio/rstudio/issues/12508 https://github.com/rstudio/rstudio/issues/12508

gdevenyi 3y ago
The answer, it turns out, was yes!
jmcphers 3y ago
Can't make any promises -- our dev team is pretty small! -- but it's been flagged for triage.
cdrv 3y ago
This particular issue should be resolved in the latest daily builds of RStudio. The underlying issue here was a conda patch included in the conda-provided builds of R, which interfered with the way RStudio attempted to load R. Please see https://github.com/rstudio/rstudio/issues/13184#issuecomment-1992709588 https://github.com/rstudio/rstudio/issues/13184#issuecomment... for more details.

fumeux_fume 3y ago

It’s really nice to have everything you need in one spot. Plus it’ll run on any OS and is free. I started learning how to program with C++ back in the early 2000s which required Windows and a Visual Studio license and it was still a pain to get stuff done. Whether it’s RStudio or Jupyter there’s really never been a better time to start picking up a language and building something useful. Three cheers for the creators, maintainers and community who support tools like this.

tetris11 3y ago
Freemium is what they ("Posit") are pivoting to now. https://posit.co/pricing/individual-products/ https://posit.co/pricing/individual-products/ If you want a Rstudio server to host for a research group containing more than 5 people, talk to their sales Rep. Otherwise each person will need to host their own Rstudio server side-by-side on the same machine. Jupyter and JupyterHub is the way forward. Especially if they get multi-kernel notebooks mainlined (read: what Org-Mode has been doing for decades)
- jmcphers 3y ago
  That pricing sheet is for Posit Workbench; RStudio Server[0] can host as many people as you have the compute for, and it's free and open source. It does only support one session per user, but might meet the needs of a small research group. [0] https://posit.co/download/rstudio-server/ https://posit.co/download/rstudio-server/

wjholden 3y ago

The killer feature of RStudio for me is RMarkdown. I composed almost all my homeworks in grad school using RMarkdown in RStudio. You get LaTeX whenever you need it, code (I usually use it for R or Julia), and markdown for ordinary text. The kable function renders tables nicely from data frames and ggplot2 creates beautiful plots. Mathematica and Jupyter have a few advantages, but overall I'm very happy with RStudio.

minimaxir 3y ago
RMarkdown in RStudio was the killer feature, until the VSCode R extension matured. Not only does it support RMarkdown, it adds a ton of features RStudio doesn't have and runs a lot faster. https://github.com/REditorSupport/vscode-R/wiki/R-Markdown https://github.com/REditorSupport/vscode-R/wiki/R-Markdown For my uses, it replaced RStudio 100% of the time.
- adr1an 3y ago
  Can you use quarto in vscode? It's the next magic from Posit.co
  - minimaxir 3y ago
    Yes, quarto has native support for VSCode: https://quarto.org/docs/get-started/hello/vscode.html https://quarto.org/docs/get-started/hello/vscode.html There isn't much advantage to using it over RMarkdown for R, IMO.
- dr_kiszonka 3y ago
  Thanks for the link! Is it possible to display plots inline like in notebooks? (The screenshot shows a plot in a preview pane.)
  - minimaxir 3y ago
    Unfortunately no. (tbh I don't like that feature in RStudio anyways: it makes it longer to scroll through large notebooks, and ggsave is better at rendering charts than R's native rendering) For knitting, you can use Markdown image links.

mightyham 3y ago

RStudio and the R language are a couple of my absolute favorite pieces of software. While I'm a software engineer by trade, every once in a while I need to do some data analysis work and throwing together a notebook in RStudio always makes me feel like I'm using a cheat code. For simple tasks, everything is incredibly seamless, plus coworkers who are unfamiliar with R are usually impressed by how nice ggplot visualizations can look.

lvl102 3y ago

I enjoy RStudio but the best feature of R is data.table. It’s simply unmatched.

ProjectArcturis 3y ago
Once you climb that steep learning curve, absolutely.
th0ma5 3y ago
Polars is faster? Data.table was a pioneering speed improvement at one point for sure.
- lvl102 3y ago
  It is but if we are talking speed, I’d just opt for RAPIDS.

uptownfunk 3y ago

I think one of the most underrated pieces of software in modern history. Absolutely brilliant. Huge fan. I am glad to see it getting love. I’ve moved on from data science in a professional capacity but for some pet projects of mine it has been indispensable. I think managing the namespace was one non trivial concern (which may be resolved in modern versions). Otherwise very well built for data science applications. Interesting that it didn’t catch on for LLM training - I think a missed opportunity.

dclaw 3y ago

Ahh cool, now r-studio brings up this instead of the 24 year old data recovery program.... :-(

stonogo 3y ago
RStudio is thirteen years old so I'm not sure what changed that makes the search results different "now"

matttproud 3y ago

I'm about as old school as you can get with preference for CLI and simple text-oriented development environments. I recently picked up R again for a long-term data science project (https://matttproud.com/blog/posts/teaser-weather-temp-representation.html https://matttproud.com/blog/posts/teaser-weather-temp-repres...) after having not used it since university. In spite of a fair bit of annoyance with the R language (https://matttproud.com/blog/posts/rant-and-r-melt-function.html https://matttproud.com/blog/posts/rant-and-r-melt-function.h...), I found RStudio to make the prototyping process with R actually tolerable. Big kudos to Posit and the R community for RStudio. There are a couple of things I would love for the R ecosystem: project scaffolding to do bulk data generation (e.g., from continuously generated data sets). What's the best way to do this: makefiles, or what? I have a relatively short entrypoint R file that sources other leaf files to run specific analyses, but it makes the software engineer inside of me want to curl up and die.

mjhay 3y ago
reshape2 (where `melt` is from) has been deprecated for some time, and for pretty good reasons. Try dplyr and tidyr instead - they are much nicer and modern. The equivalent of melt would be pivot_longer. For packaging, renv is the usual choice. I wouldn't structure the package as a bunch of scripts with an entrypoint. Just write functions as you would in other languages, and keep any specific analysis script small. https://tidyr.tidyverse.org/ https://tidyr.tidyverse.org/

melondonkey 3y ago

Weird one minute it feels like the internet is screaming that I’m an out-of-touch dinosaur for using R and the next a simple link to its most popular IDE makes the front of HN.

ivansavz 3y ago

The closest Python equivalent to RStudio is the JupyterLab Desktop app[1,2], which I highly recommend. I've entirely switched to using it for teaching, and it is a godsend, since it works the same way across platforms (win/mac/linux), installs its own Python interpreter independent of any system Python the student might have, and even comes with NumPy/SciPy/Pandas/Seaborn/statsmodels already installed, which makes it possible for me to skip the `pip ...` or `conda ...` instructions altogether. Between the standalone desktop app, and the convenience of running JypyterLab in the cloud thanks to https://mybinder.org/ https://mybinder.org/ links, there is now a smooth path for beginners getting into stats/ML/data science: (1) read notebook on github or nbviewer, (2) run notebooks in the cloud via mybinder links, (3) install JupyterLab Desktop app, (4) learn to install Python+env-manager via command line. Previously, new learners were forced to jump straight to (4), but now there are logical steps along the way! [1] https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-ov-file#jupyterlab-desktop https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-... [2] https://blog.jupyter.org/jupyterlab-desktop-app-now-available-b8b661b17e9a https://blog.jupyter.org/jupyterlab-desktop-app-now-availabl...

wodenokoto 3y ago
Is it different from running through the web server? I found it to have a lot of potential but not there yet
- ivansavz 3y ago
  It's the same stack (jupyterlab server backend + web frontend) but wrapped as an electron app. Yeah for sure when I use RStudio it seems much more polished, but I guess my attachment to (and comfort with) Python still makes it worthwhile to use JupterLab rather than switch to RStudio.

Kalanos 3y ago

i use jupyter a lot for python. i occasionally have to use rstudio for bioinformatics. the ux is much, much worse. just haven't bothered to get the R kernel for jupyter working.

rubslopes 3y ago

Is there a way to visualize a dataframe like a spreadsheet, as RStudio does, but for VSCode?

HayBale 3y ago

Ahhh I started my programming with Rstudio. Since than I changed to Emacs with ESS. Rstudio is nice but lacks a lot of nice things from something bigger.

jurimasa 3y ago

If you work with Python, Spyder comes really, really close to RStudio and is way better than jupyter