R
R is an interpreted, open source programming language with powerful data manipulation and graphical capabilities. It has a thriving package ecosystem and is one of the most popular languages for data science.
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About R
R is an open source, programming lingua franca of statistics. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, who wanted a language that was better suited to statistical computing and easier to use than comparable software designed by computer scientists.
In addition to being a programming language, R is also an environment for interactive data analysis. Its powerful metaprogramming capabilities allow for magically succinct and concise functions. It can also integrate with high-performance programming languages like Fortran, C, and C++. These combined attributes provide an excellent environment for designing domain-specific languages.
Ross Ihaka describes R as "a real demonstration of the power of collaboration". R has a fantastic community of both users and developers, who contribute to a massive (and rapidly growing) collection of packages for importing, manipulating and visualising data, as well as cutting edge methods for statistical modelling and machine learning.
Learn more on r-project.org!
Key Features of R
Domain Specific
R is a language and environment for statistical computing and graphics.
Cross-platform
It is free, open source, and available on every major platform.
Multi-paradigm
R has a functional programming foundation, but facilitates procedural or object-oriented approaches.
Metaprogramming
R’s metaprogramming capabilities allow for magically succinct and concise functions.
Tooling
R provides powerful tools for data manipulation, visualisation, modelling, and machine learning.
Community
R has a diverse and welcoming community.
Domain Specific
R is a language and environment for statistical computing and graphics.
Cross-platform
It is free, open source, and available on every major platform.
Multi-paradigm
R has a functional programming foundation, but facilitates procedural or object-oriented approaches.
Metaprogramming
R’s metaprogramming capabilities allow for magically succinct and concise functions.
Tooling
R provides powerful tools for data manipulation, visualisation, modelling, and machine learning.
Community
R has a diverse and welcoming community.
