What are the differences between R and S?
Python is more of a deep learning language and is a language for development and deployment. Codes in R need more maintenance as it is a vector-based language. Python is more robust and easy to maintain. R offers multiple packages for accomplishing one task, while Python has a few packages for a single task.
R simplifies quality plotting and graphing. R libraries such as ggplot2 and plotly advocates for visually appealing and aesthetic graphs which set R apart from other programming languages.
The R FAQ does a decent job answering this question:
We can regard S as a language with three current implementations or “engines”, the “old S engine” (S version 3; S-Plus 3.x and 4.x), the “new S engine” (S version 4; S-Plus 5.x and above), and R. Given this understanding, asking for “the differences between R and S” really amounts to asking for the specifics of the R implementation of the S language, i.e., the difference between the R and S engines.
[...]
If you're talking about working from the command prompt or with scripts, the biggest difference will be package support. The most fundamental difference is the underscore assignment operator. In S y_2
is the same as y=2
. In R y_2
is just a string/object. When I moved from S to R several years ago (was on S 5.x at the time) I found most of my functions and scripts ran pretty well by just replacing the underscores with <-
. An example for me was the spatial stats implementation. At the time the S spatial stats package was about 8 years old with no updating. R had several packages available and most of the new research seemed to be implemented for R (free goes a long way with academics).
S-Plus has a huge GUI front-end and ostensibly that's what the several grand price tag is for. However my S experience is several versions old now.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With