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R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror.
Download R-4.4.2 for Windows (83 megabytes, 64 bit) README on the Windows binary distribution. New features in this version. This build requires UCRT, which is part of Windows since Windows 10 and Windows Server 2016. On older systems, UCRT has to be installed manually from here.
Learn R. R is a programming language. R is often used for statistical computing and graphical presentation to analyze and visualize data. Start learning R now »
To enhance productivity and leverage the full potential of R, a variety of tools and packages have been developed. This article delves into the must-have R programming tools that every R programmer should consider integrating into their workflow.
R is a statistical programming tool that’s uniquely equipped to handle data, and lots of it. Wrangling mass amounts of information and producing publication-ready graphics and visualizations is easy with R.
Learn R programming and effective data analysis in this Johns Hopkins University course on Coursera. Install and configure R, explore programming concepts, read data, access packages, write functions, debug, profile code, and organize/comment code with practical examples.
Easily search the documentation for every version of every R package on CRAN and Bioconductor.
a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either on-screen or on hardcopy, and; a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
A collection of 5 essential R programming tools to help you become more efficient and a better data scientist
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics, and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.