R (programming language)
R (programming language)
R is a programming language and free software environment for statistical computing and graphics. It is widely used among statisticians, data analysts, and researchers for developing statistical software and performing data analysis. R is part of the GNU Project and is available under the GNU General Public License. Its source code is written primarily in C, Fortran, and R itself. The language is extensible through packages, many of which are collected in the Comprehensive R Archive Network (CRAN).
History
R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and first released in 1995. The name derives from the first names of the two authors and as a play on the earlier S (programming language). In 1997, the R Core Team was formed to oversee development. The first stable version, 1.0.0, was released in 2000. Since then, the language has undergone continuous updates, with major versions appearing regularly. R's popularity grew significantly in the 2000s and 2010s, driven by the rise of data science and big data.
Features
R provides a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, and clustering. Its graphics capabilities are highly customizable, with packages such as ggplot2 and lattice enabling publication-quality plots. R also supports functional programming, object-oriented programming, and integration with other languages like C++ and Python (programming language).
The language includes built-in support for matrices and arrays, making it suitable for numerical analysis. Its package ecosystem, hosted on CRAN, Bioconductor, and GitHub, contains thousands of packages contributed by the community. Common packages include dplyr for data manipulation, tidyr for data tidying, and shiny for interactive web applications.
Usage
R is used in academia, government, and industry for statistical analysis, data visualization, and machine learning. It is a standard tool in fields such as bioinformatics, econometrics, and social sciences. RStudio, an integrated development environment, provides a user-friendly interface for R development.