| website | https://www.r-project.org/ |
| download | https://cran.r-project.org/ |
| wikipedia | |
| R Packages | https://cran.r-project.org/web/packages/index.html |
| Rtools | https://cran.r-project.org/bin/windows/Rtools/ |
| R Journal | https://journal.r-project.org/ |
| R Manuals | https://cran.r-project.org/manuals.html |
| Rstudio | https://posit.co/ |
| getting started with R | https://mran.microsoft.com/documents/getting-started |
| April 24, 2024 | R 4.4.0 |
R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software.[6] Users have created packages to augment the functions of the R language.
According to user surveys and studies of scholarly literature databases, R is one of the most commonly used programming languages used in data mining.[7] As of March 2022, R ranks 11th in the TIOBE index, a measure of programming language popularity, in which the language peaked in 8th place in August 2020.[8][9]
The official R software environment is an open-source free software environment within the GNU package, available under the GNU General Public License. It is written primarily in C, Fortran, and R itself (partially self-hosting). Precompiled executables are provided for various operating systems. R has a command line interface.[10] Multiple third-party graphical user interfaces are also available, such as RStudio, an integrated development environment, and Jupyter, a notebook interface.
https://cran.r-project.org/bin/windows/base/rw-FAQ.html
2.2 How do I install R for Windows?
Current binary versions of R are known to run on Windows 7 or later. R 4.1 is the last version that supported 32-bit versions: See Can I use R on 64-bit Windows?. R 4.2.0 requires the Universal C Runtime (UCRT), which is included in Windows 10 and Windows Server 2016 or newer. On earlier versions of Windows, UCRT has to be installed before installing R. UCRT is available for Windows since Windows Vista SP2 and Windows Server 2008 SP2. Windows XP is no longer supported.
2.26 Can I use R on 64-bit Windows?
Yes, and this is the primarily used and the only tested option now. Since R 4.2.0, 32-bit builds are no longer provided.
R IDE(integrated development environment)
Rstudio
https://posit.co/download/rstudio-desktop/
Jupyter Notebook
https://www.practicaldatascience.org/html/jupyter_r_notebooks.html
install.packages("IRkernel")
IRkernel::installspec()
nteract
install.packages(c('repr', 'IRdisplay', 'evaluate', 'crayon', 'pbdZMQ', 'devtools', 'uuid', 'digest'))
devtools::install_github('IRkernel/IRkernel')
IRkernel::installspec()
Rcode
http://www.pgm-solutions.com/rcode/download
Tinn-R
Visual Studio Code
https://code.visualstudio.com/
RKWard
https://rkward.kde.org/index.html
Microsoft R
Running R in the cloud
https://www.tutorialspoint.com/execute_r_online.php
JASP
Jamovi
https://www.jamovi.org/
History of R
Robert Gentleman
Ross Ihaka
R is an implementation of the S programming language combined with lexical scoping semantics, inspired by Scheme.[1] S was created by John Chambers in 1976 while at Bell Labs. A commercial version of S was offered as S-PLUS starting in 1988.
Much of the code written for S-PLUS runs unaltered in R.[10]
In 1991 Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, began an alternative implementation of the basic S language, completely independent of S-PLUS, which they began publicizing in 1993.[11] It was named partly after the first names of the first two R authors and partly as a play on the name of S.[12] In 1995, Martin Maechler convinced Ihaka and Gentleman to make R free and open-source software under Version 2 of the GNU General Public License.[13][14] The R Core Team was formed in 1997 to further develop the language.[12] As of 2021, it consisted of Gentleman, Ihaka, and Maechler, plus Douglas Bates, John Chambers, Peter Dalgaard, Kurt Hornik, Tomas Kalibera, Michael Lawrence, Friedrich Leisch, Uwe Ligges, Thomas Lumley, Martin Morgan, Paul Murrell, Martyn Plummer, Brian Ripley, Deepayan Sarkar, Duncan Temple Lang, Luke Tierney, and Simon Urbanek. Heiner Schwarte, Guido Masarotto, Stefano Iacus, Seth Falcon, and Duncan Murdoch were also formerly members.[15]
The first official release came in 1995.[11] The Comprehensive R Archive Network (CRAN) was officially announced 23 April 1997 with 3 mirrors and 12 contributed packages.[16] The first official "stable beta" version (v1.0) was released 29 February 2000.[17][18]
The CRAN package repository features 18391 available packages on August 10, 2022.
https://cran.r-project.org/web/packages/index.html
https://www.tiobe.com/tiobe-index/r/
Downloads (https://cranlogs.r-pkg.org/badges/mltools)
Downloads in last day (https://cranlogs.r-pkg.org/badges/last-day/mltools)
Grand total (https://cranlogs.r-pkg.org/badges/grand-total/mltools)
App for r package downloads(David Robinson)
https://ipub.com/dev-corner/apps/r-package-downloads/
https://www.analyticsvidhya.com/wp-content/uploads/2016/07/DataAnalysis_R.pdf
Microsoft R Application Network: https://mran.microsoft.com/
Quick-R
R bloggers
Data Science Made simple
http://www.datasciencemadesimple.com/learn-r-what-is-r/
Data Camp
Try R
Database using R
R for excel
https://www.rforexcelusers.com/
- Handling Strings with R. This book aims to help you get started with manipulating strings with R (new bookdown version, work in progress).
- Handling and Processing Strings in R (old pdf version).
- Pack YouR Code. This book aims to help you get started with the creation of an R package (work in progress).
- A Matrix Algebra Companion for Statistical Learning. The purpose of this book is to help you understand how statistical notions are connected to matrix algebra concepts that constantly appear around Statistical Learning methods (work in progress).
- PLS Path Modeling with R. This book provides a hands-on introduction to Partial Least Squares Path Modeling (PLS-PM) using the R package "plspm".
- The Saga of PLS. This text narrates the story behind the origins, development, and evolution of Partial Least Squares (PLS) methods.