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I've used quite a bit of R and Python and I've never touched Matlab. Similarly to your comment - Python has nothing that comes even close to RStudio for working

by 0xd171 7y ago

I've used quite a bit of R and Python and I've never touched Matlab. Similarly to your comment - Python has nothing that comes even close to RStudio for working with data. Jupyter, Spyder, PyCharm, VSCode/Atom with data science extensions - none of them are as good.

spinningslate 7y ago
Agreed. R might not have the breadth of Python, and it's less conventional as a language (procedural, vector based). It has some key strengths though: 1. RStudio IDE as you note. It's a really great, focused IDE for doing most of the things people do with R. 2. Shiny. Such a well conceived and constructed toolkit for building interactive apps 3. The package ecosystem: lots of really good quality, high performance packages 4. RStudio the company, who contribute a lot to the community - both open source (RStudio IDE, Shiny, tidyverse, ...) and commercial (RSConnect, Package Manager). From a language design pov I like Julia over Python over R. But for number-heavy computing I prefer the R ecosystem overall.
- kgwgk 7y ago
  One of the packages created by RStudio is reticulate, which allows integration with python. They have also recently added some support for python to the IDE: https://rstudio.github.io/reticulate/articles/rstudio_ide.html https://rstudio.github.io/reticulate/articles/rstudio_ide.ht...
- 0xd171 7y ago
  On the other hand, base R has to maintain (some degree of?) compatibility with S. Which means that all the strange design choices and weird behaviour in base R have little hope of ever changing. No number of additional packages can fix this.
  - tylermw 7y ago
    There is one nice thing about R core's focus on maintaining backwards compatibility, however: code from a decade ago (more often than not) will run without a hiccup on current versions of R. Related tweets: https://twitter.com/hrbrmstr/status/1124016682413039616 https://twitter.com/hrbrmstr/status/1124016682413039616 https://twitter.com/hrbrmstr/status/1122186751987073025 https://twitter.com/hrbrmstr/status/1122186751987073025
overkalix 7y ago
What about Rodeo? From the looks of it, it's getting close. And honestly, at this point I continue to use R because of RStudio and the tidyverse, otherwise I would have ditched the language a long time ago.
- overkalix 7y ago
  Disregard my previous comment. I looked into it and apparently Rodeo's company was acquired and the IDE became unsupported and is now a dumpster fire. Also, it used electron. So long live RStudio, I guess.
- 0xd171 7y ago
  > I continue to use R because of RStudio and the tidyverse Tidyverse is massively overrated if you ask me. The good parts of it (dplyr and ggplot) are nice for interactive work. And that's about it - if you're deploying the code in an application, you're best off sticking to base R as much as possible.

by 0xd171 7y ago

spinningslate 7y ago

Agreed. R might not have the breadth of Python, and it's less conventional as a language (procedural, vector based). It has some key strengths though: 1. RStudio IDE as you note. It's a really great, focused IDE for doing most of the things people do with R. 2. Shiny. Such a well conceived and constructed toolkit for building interactive apps 3. The package ecosystem: lots of really good quality, high performance packages 4. RStudio the company, who contribute a lot to the community - both open source (RStudio IDE, Shiny, tidyverse, ...) and commercial (RSConnect, Package Manager). From a language design pov I like Julia over Python over R. But for number-heavy computing I prefer the R ecosystem overall.

kgwgk 7y ago
One of the packages created by RStudio is reticulate, which allows integration with python. They have also recently added some support for python to the IDE: https://rstudio.github.io/reticulate/articles/rstudio_ide.html https://rstudio.github.io/reticulate/articles/rstudio_ide.ht...
0xd171 7y ago
On the other hand, base R has to maintain (some degree of?) compatibility with S. Which means that all the strange design choices and weird behaviour in base R have little hope of ever changing. No number of additional packages can fix this.
- tylermw 7y ago
  There is one nice thing about R core's focus on maintaining backwards compatibility, however: code from a decade ago (more often than not) will run without a hiccup on current versions of R. Related tweets: https://twitter.com/hrbrmstr/status/1124016682413039616 https://twitter.com/hrbrmstr/status/1124016682413039616 https://twitter.com/hrbrmstr/status/1122186751987073025 https://twitter.com/hrbrmstr/status/1122186751987073025

overkalix 7y ago

What about Rodeo? From the looks of it, it's getting close. And honestly, at this point I continue to use R because of RStudio and the tidyverse, otherwise I would have ditched the language a long time ago.

overkalix 7y ago
Disregard my previous comment. I looked into it and apparently Rodeo's company was acquired and the IDE became unsupported and is now a dumpster fire. Also, it used electron. So long live RStudio, I guess.
0xd171 7y ago
> I continue to use R because of RStudio and the tidyverse Tidyverse is massively overrated if you ask me. The good parts of it (dplyr and ggplot) are nice for interactive work. And that's about it - if you're deploying the code in an application, you're best off sticking to base R as much as possible.