R

R Programming Language Profile

R

The R language (and open-source software) is the de facto standard among statisticians for the development of statistical software, and is widely used for statistical software development and data analysis.

R is much more than a programming language. It’s an interactive environment for performing statistics. R offers a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.

The ability to download and install R packages is a key factor which makes R an excellent language to learn. Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. The CRAN package repository hosts over 10,000 packages, and Bioconductor hosts nearly 1,300 packages.


FACTS

Type of Language: Multi-paradigm: Array, object-oriented, imperative, functional, procedural, reflective
Designed by: Ross Ihaka and Robert Gentleman
Public Release: 1993
License: GNU GPL v2
Website: www.r-project.org


RECOMMENDED OPEN SOURCE BOOKS

Open-Source R Books


OPEN SOURCE SOFTWARE FOR DEVELOPERS

RStudio – Integrated Development Environment.


USEFUL RESOURCES

CRAN – The Comprehensive R Archive Network.
Bioconductor – Open Source Software for Bioinformatics.
R-Bloggers – an informative blog aggregator of content contributed by bloggers who write about R.
Google’s R Style Guide


RECOMMENDED BOOK TO BUY

R in Action

PROGRAMMING LANGUAGE PROFILES

Ada, Assembly, C, C++, C#, Clojure, CoffeeScript, ECMAScript, Erlang, Forth, Go, Haskell, HTML, Java, JavaScript, Lisp, Logo, Lua, OCaml, Pascal, Perl, PHP, Prolog, Python, R, Ruby, Rust, Scala, Scratch, Swift, VimL