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Awesome R resources, packages and FAQS
| Platform | Version | Distributive Link | Direct download link | Size, Mb | SHA-1 |
|---|---|---|---|---|---|
| MacOS | 3.4.1 | https://cran.r-project.org/bin/macosx/ | MacOS Link | 61 | 4138852c052a2056ce648d886b9b47d8a514b762 |
| Linux | 3.4.1 | https://cran.r-project.org/bin/linux/ | 61 | ||
| Windows | 3.4.1 | https://cran.r-project.org/bin/windows/base/ | Windows Link | 74 | 25527cd39a30b500e45cb65d967c45572ea183b6 |
Best free and Open Source IDE for R: https://www.rstudio.com/products/RStudio/
| Installers | Size | Date | MD5 |
|---|---|---|---|
| RStudio 1.0.153 - Windows Vista/7/8/10 | 81.9 MB | 2017年07月20日 | b3b4bbc82865ab105c21cb70b17271b3 |
| RStudio 1.0.153 - Mac OS X 10.6+ (64-bit) | 71.2 MB | 2017年07月20日 | 8773610566b74ec3e1a88b2fdb10c8b5 |
| RStudio 1.0.153 - Ubuntu 12.04-15.10/Debian 8 (32-bit) | 85.5 MB | 2017年07月20日 | 981be44f91fc07e5f69f52330da32659 |
| RStudio 1.0.153 - Ubuntu 12.04-15.10/Debian 8 (64-bit) | 91.7 MB | 2017年07月20日 | 2d0769bea2bf6041511d6901a1cf69c3 |
| RStudio 1.0.153 - Ubuntu 16.04+/Debian 9+ (64-bit) | 61.9 MB | 2017年07月20日 | d584cbab01041777a15d62cbef69a976 |
| RStudio 1.0.153 - Fedora 19+/RedHat 7+/openSUSE 13.1+ (32-bit) | 84.7 MB | 2017年07月20日 | 8dfee96059b05a063c49b705eca0ceb4 |
| RStudio 1.0.153 - Fedora 19+/RedHat 7+/openSUSE 13.1+ (64-bit) | 85.7 MB | 2017年07月20日 | 16c2c8334f961c65d9bfa8fb813ad7e7 |
Russian
- Основы программирования на R (by Bioinformatics Institute)
- Анализ данных в R (by Bioinformatics Institute)
- Анализ данных в R. Часть 2 (by Bioinformatics Institute)
- Основы статистики (by Bioinformatics Institute)
- Основы статистики. Часть 2 (by Bioinformatics Institute)
- Основы статистики. Часть 3 (by Bioinformatics Institute)
Coursera
- Data Science Specialization (by Johns Hopkins University)
Other:
- BookDown - Write HTML, PDF, ePub, and Kindle books with R Markdown
- FreeComputerBooks R EBooks
- Effective Graphs with Microsoft R Open
- Little Book of R for Time Series (by Avril Coghlan)
- Little Book of R for Biomedical Statistics (by Avril Coghlan)
- Little Book of R for Multivariate Analysis (by Avril Coghlan)
- Text Mining with R (by Julia Silge and David Robinson)
- An Introduction to Statistical Learning with Applications in R (by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani)
- Advanced R Programming (by Hadley Wickham)
- Cookbook for R (by Winston Chang)
- Introduction to Probability and Statistics Using R (by G. Jay Kerns (PDF))
- Learning Statistics with R (by Daniel Navarro)
- Machine Learning with R (by Brett Lantz, Packt.
- ModernDive (by Chester Ismay and Albert Y. Kim)
- Practical Regression and Anova using R (by Julian J. Faraway (PDF))
- R for Data Science (by Garrett Grolemund and Hadley Wickham
- R for Spatial Analysis (PDF)
- R Language for Programmers (by John D. Cook)
- R Packages (by Hadley Wickham)
- R Practicals (PDF)
- R Programming
- R Programming for Data Science (Needs valid email)
- R Succinctly, Syncfusion (PDF, Kindle)
- The caret Package (by Max Kuhn)
- The R Inferno (by Patrick Burns (PDF))
- The R Language
- The R Manuals
- Tidy Text Mining with R (by Julia Silge and David Robinson)
- R Programming for Data Science (by Roger D. Peng)