R is a programming language and software environment for statistical computing and graphics that is freely available under the GNU General Public License. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that R is one of the most popular programming languages for data science and statistical computing.
R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. The R language is based on the S language, which was developed at Bell Labs by John Chambers and colleagues. R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, etc.), graphical (interactive graphics, high-quality publication-ready plots), and programming (object-oriented programming, functional programming, porting S code, etc.) facilities. It is a GNU project which means that R is free software, freely available under the GNU General Public License, and comes with ABSOLUTELY NO WARRANTY.
R is a powerful tool for data analysis and visualization. It is easy to learn and use, and there is a large community of users and developers who contribute to its development and maintenance. R is used by researchers and practitioners in a wide range of fields, including biology, medicine, finance, and economics.
Here is a brief history of R:
- 1991: Ross Ihaka and Robert Gentleman create the R language at the University of Auckland, New Zealand.
- 1993: The first version of R is released.
- 1995: R is released under the GNU General Public License.
- 1997: The R Development Core Team is formed.
- 2000: R 1.0.0 is released.
- 2005: R 2.0.0 is released.
- 2010: R 3.0.0 is released.
- 2015: R 3.4.0 is released.
- 2020: R 4.0.0 is released.
R is a rapidly evolving language, and new features and capabilities are added on a regular basis. The R Development Core Team is committed to making R the best possible statistical computing environment, and they are always looking for ways to improve the language.
