The R language 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 a modern dialect of S, one of several statistical programming languages designed at Bell Laboratories.
R is much more than a programming language. It’s an interactive suite of software facilities for data manipulation, calculation, and graphical display. 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. What else makes R awesome? Here’s a taster.
- It’s free, open source, and available for every major platform. So anyone can repeat your work whatever platform they run.
- A huge set of high quality packages for statistical modelling, machine learning, visualization, and importing and manipulating data.
- Cutting edge tools.
- A suite of operators for calculations on arrays, in particular matrices.
- Deep-seated language support for data analysis. This includes features likes missing values, data frames, and subsetting.
- Powerful tools for communicating your results.
- Produce publication-quality graphs, including mathematical symbols. Dynamic and interactive graphics are available through additional packages. R packages make it easy to produce HTML or PDF, and create interactive websites with Shiny, a sublime R package.
- A strong foundation in functional programming. The ideas of functional programming are well suited to solving many of the challenges of data analysis. R provides a powerful and flexible toolkit which allows you to write concise yet descriptive code.
- RStudio, a powerful integrated development environment.
- Powerful metaprogramming facilities; a fantastic environment for interactive data analysis.
- Connects to high-performance programming languages like C, Fortran, and C++.
- An amazingly vibrant and helpful community.
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 15,000 packages, and Bioconductor is home to over 1,800 packages.
Here’s our recommended tutorials to learn R. If you’re looking for free R programming books, check here.
1. Introduction to R and RStudio for Data Science by LinuxLinks
This is a crash course in data science designed for the absolute beginner. Get up to speed in 20 minutes. It assumes only basic computer skills and no programming knowledge. If you’re interested in learning about data science, this is a great place to start.
2. Cookbook for R by Winston Chang
The goal of the cookbook is to provide solutions to common tasks and problems in analyzing data.
3. R Tutorial for Beginners: Learning R Programming by guru99
This is a complete course on R for beginners and covers basics to advance topics like machine learning algorithm, linear regression, time series, statistical inference etc.
4. Elementary Statistics with R by R Tutorial
The R solutions are short, self-contained and requires minimal R skill. Most of them are just a few lines in length.
5. R Tutorial by Kelly Black
These materials are designed to offer an introduction to the use of R. It is not exhaustive, but is designed to just provide the basics. It has been developed for students who are new to R but have had some basic experience working with computers.
6. R Programming Tutorials by thenewboston
A set of videos with good coverage.
7. 15 Page Tutorial for R by Study Trails
A 15 page example based tutorial that covers the basics of R.
These tutorials are designed for beginners in R, but they can also be used by experienced programmers as a refresher course or as reference.
All tutorials in this series:
|Free Programming Tutorials|
|Java||General-purpose, concurrent, class-based, object-oriented, high-level language|
|C||General-purpose, procedural, portable, high-level language|
|Python||General-purpose, structured, powerful language|
|C++||General-purpose, portable, free-form, multi-paradigm language|
|C#||Combines the power and flexibility of C++ with the simplicity of Visual Basic|
|PHP||PHP has been at the helm of the web for many years|
|Ruby||General purpose, scripting, structured, flexible, fully object-oriented language|
|Assembly||As close to writing machine code without writing in pure hexadecimal|
|Swift||Powerful and intuitive general-purpose programming language|
|Groovy||Powerful, optionally typed and dynamic language|
|Go||Compiled, statically typed programming language|
|Pascal||Imperative and procedural language designed in the late 1960s|
|Perl||High-level, general-purpose, interpreted, scripting, dynamic language|
|R||De facto standard among statisticians and data analysts|
|COBOL||Common Business-Oriented Language|
|Scala||Modern, object-functional, multi-paradigm, Java-based language|
|Fortran||The first high-level language, using the first compiler|
|Scratch||Visual programming language designed for 8-16 year-old children|
|Lua||Designed as an embeddable scripting language|
|Logo||Dialect of Lisp that features interactivity, modularity, extensibility|
|Rust||Ideal for systems, embedded, and other performance critical code|
|Lisp||Unique features - excellent to study programming constructs|
|Ada||ALGOL-like programming language, extended from Pascal and others|
|Haskell||Standardized, general-purpose, polymorphically, statically typed language|
|Scheme||General-purpose, functional, language descended from Lisp and Algol|
|Prolog||General purpose, declarative, logic programming language|
|Forth||Imperative stack-based programming language|
|Clojure||Dialect of the Lisp programming language|
|Julia||High-level, high-performance language for technical computing|
|SQL||Access and manipulate data held in a relational database management system|
|Erlang||General-purpose, concurrent, declarative, functional language|
|VimL||Powerful scripting language of the Vim editor|
|OCaml||General-purpose, powerful, high-level language|
|Awk||Versatile language designed for pattern scanning and processing|
|Racket||Platform for programming language design and implementation|
|BASIC||Family of general-purpose, high-level programming languages|
|LaTeX||Professional document preparation system and document markup language|
|Elixir||Relatively new functional language that runs on the Erlang virtual machine|
|Dart||Client-optimized programming language for fast apps|
|ABAP||Advanced Business Application Programming|
|F#||General purpose, strongly typed, multi-paradigm language. Part of ML|
|Chapel||Parallel-programming language in development at Cray Inc.|
|Dylan||Multi-paradigm language, supports functional & object-oriented programming|
|D||General-purpose systems programming language with a C-like syntax|
|Solidity||Object-oriented, high-level language for implementing smart contracts|
|XML||Set of rules for defining semantic tags that describe the structure and meaning|
|Vala||Object-oriented language with a self-hosting compiler that generates C code|
|ECMAScript||Best known as the language embedded in web browsers|
|Kotlin||Statically typed, general-purpose programming language with type inference|
|Markdown||Plain text formatting syntax designed to be easy-to-read and easy-to-write|
|Pike||Interpreted, general-purpose, high-level, cross-platform, dynamic language|
|HTML||HyperText Markup Language|
|Factor||Dynamic stack-based language|
|Objective-C||General purpose language which is a superset of C|
|Standard ML||One of the two main dialects of the ML language|
|Alice||Educational language with an integrated development environment|
|Agda||Dependently typed functional language based on intuitionistic type theory|
|Icon||High-level, general-purpose language|
|PureScript||Small strongly, statically typed language with expressive types|
|Tcl||Dynamic language based on concepts of Lisp, C, and Unix shells|