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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. RSt
by 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 agoOne 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 agoOn 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 agoThere 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