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RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
The Comprehensive R Archive Network (CRAN) homepage. The Comprehensive R Archive Network (CRAN) is R's central software repository, supported by the R Foundation. [9] It contains an archive of the latest and previous versions of the R distribution, documentation, and contributed R packages. [10]
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.
Free software portal; Shiny is a web framework for developing web applications (apps), originally in R and since 2022 in python.It is free and open source. [2] It was announced by Joe Cheng, CTO of Posit, formerly RStudio, in 2012. [3]
R Commander (Rcmdr) is a GUI for the R programming language, licensed under the GNU General Public License, and developed and maintained by John Fox in the sociology department at McMaster University. [2] Rcmdr looks and works similarly to SPSS GUI by providing a menu of analytic and graphical methods. It also displays the underlying R code ...
R Tools for Visual Studio (RTVS) is a plug-in for the Microsoft Visual Studio integrated development environment (IDE), used to provide support for programming in the language R. It supports IntelliSense , debugging, plotting, remote execution, SQL integration, and more.
knitr is a software engine for dynamic report generation with R. [1] [2] It is a package in the programming language R that enables integration of R code into LaTeX, LyX, HTML, Markdown, AsciiDoc, and reStructuredText documents. The purpose of knitr is to allow reproducible research in R through the means of literate programming.
There is also an active R community around the tidyverse. For example, there is the TidyTuesday social data project organised by the Data Science Learning Community (DSLC), [ 16 ] where varied real-world datasets are released each week for the community to participate, share, practice, and make learning to work with data easier. [ 17 ]