Extensions to the R statistical programming language
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R packages areextensions to theR statistical programming language. R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralisedsoftware repository such as CRAN (the Comprehensive R Archive Network).[1][2] The large number of packages available for R, and the ease of installing and using them, has been cited as a major factor driving the widespread adoption of the language indata science.[3][4][5][6]
Compared tolibraries in other programming languages, R packages must conform to a relatively strict specification.[3] TheWriting R Extensions manual[7] specifies a standarddirectory structure for R source code, data, documentation, and packagemetadata, which enables them to be installed and loaded using R's in-builtpackage management tools.[3] Packages distributed on CRAN must meet additional standards.[3][8] According toJohn Chambers, whilst these requirements "impose considerable demands" on package developers, they improve theusability and long-term stability of packages for end users.[3]
The number of CRAN packages hasgrown exponentially for many years,[18] and as of 2018[update] an average of 21 submissions of new or updated packages were made every day.[6] Since each submission is manually reviewed by a small team of CRAN maintainers, many of whom, according to R core developerPeter Dalgaard, are "approaching pensionable age", there is a concern that this system is not sustainable in the long term.[6] The growth of CRAN has exposed limitations of itsdependency management infrastructure, particularly the fact that it assumes that dependencies always refer to the latest version of a package, meaning that new releases of CRAN packages must always bebackwards compatible,[19] and that CRAN packages cannot have dependencies that are not on CRAN.[20] It has also led to concerns about declining quality of packages.[21]
Homepage for the Microsoft R Application Network (MRAN)
The Microsoft R Application Network (MRAN) is a mirror of CRAN maintained byMicrosoft which is based on the company's downstream distribution of R,Microsoft R Open (formerly Revolution R Open).[22] It also includes an archive of daily CRAN snapshots, branded as the "CRAN Time Machine", which enables users of MRAN to bypass the dependency versioning limitations of CRAN by installing a fixed set of R package versions via the package checkpoint.[23][24] In January 2023 Microsoft announced that MRAN was being retired and the associated websites and repositories became unavailable in July 2023.[25]
Homepage for the Posit Package Manager
The Posit Package Manager (formerly RStudio Package Manager) is a similar tool produced by the developers ofRStudio which, in addition to CRAN snapshots, includes an archive of R packages from Bioconductor andPython packages from thePython Package Index.[26] It also distributes pre-compiled binary packages for Linux (only Windows and macOS binaries are included on CRAN).[27]
R-Forge,[29] is a central platform for the collaborative development of R packages, R-related software, and projects. R-Forge also hosts many unpublished beta packages, and development versions of CRAN packages.
R is distributed with fifteen "base packages": base, compiler, datasets, grDevices, graphics, grid, methods, parallel, splines, stats, stats4, tcltk, tools, translations, and utils.[30]
In addition, there are fifteen "recommended packages" from CRAN which are included with binary distributions of R: KernSmooth, MASS, Matrix, boot, class, cluster, codetools, foreign, lattice, mgcv, nlme, nnet, rpart, spatial, and survival.[30]
A group of packages called thetidyverse, which can be considered a "dialect of the R language", is increasingly popular in the R ecosystem. As of 2020-06-13, Metacran[17] listed 7 of the 8 core packages of the tidyverse in the list of most downloaded R packages. The group of packages strives to provide a cohesive collection of functions to deal with common data science tasks, includingdata import, cleaning, transformation andvisualisation (notably with theggplot2 package).
The R Infrastructure packages[31] support coding and the development of R packages and as of 2021-05-04, Metacran[17] lists 16 of these packages among the 25 most downloaded packages.
^Hornik, Kurt (2020-02-20)."Frequently Asked Questions on R".The Comprehensive R Archive Network. 7.29: What is the difference between package and library?.Archived from the original on 2011-07-09. Retrieved2 November 2020.{{cite web}}: CS1 maint: location (link)
^Wickham, Hadley; Bryan, Jennifer. "Introduction".R Packages (2nd ed.).Archived from the original on 2022-06-29. Retrieved2020-11-02.
^abCRAN Repository Maintainers."CRAN Repository Policy".The Comprehensive R Archive Network. R Project.Archived from the original on 11 November 2020. Retrieved20 November 2020.
^abHornik, Kurt (2020-02-20)."Frequently Asked Questions on R".The Comprehensive R Archive Network. 2.1: What is CRAN?: R Project.Archived from the original on 2011-07-09. Retrieved20 November 2020.{{cite web}}: CS1 maint: location (link)
^CRAN Repository Maintainers."CRAN - Contributed Packages".The Comprehensive R Archive Network. CRAN.Archived from the original on 24 November 2020. Retrieved20 November 2020.
^abHornik, Kurt (2020-02-20)."Frequently Asked Questions on R".The Comprehensive R Archive Network. 5.1: Which add-on packages exist for R?.Archived from the original on 2011-07-09. Retrieved2 November 2020.{{cite web}}: CS1 maint: location (link)
