# R

> programming language for statistical analysis

**Wikidata**: [Q206904](https://www.wikidata.org/wiki/Q206904)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/R_(programming_language))  
**Source**: https://4ort.xyz/entity/r

## Summary
R is a programming language specifically designed for statistical analysis, data visualization, and data science. It was created in 1993 by Ross Ihaka and Robert Gentleman at the University of Auckland. R is widely used in academia, research, and industry for its powerful capabilities in handling complex statistical operations and producing publication-quality graphics.

## Key Facts
- Created in August 1993 by Ross Ihaka and Robert Gentleman
- First stable version (1.0.0) released in February 2000
- Licensed under GNU General Public License, version 2.0
- Runs on major platforms including Windows, macOS, and Unix-like systems
- Influenced by the S programming language, Common Lisp, and XLispStat
- Maintained by The R Foundation for Statistical Computing
- Used extensively in fields such as statistics, bioinformatics, and data science

## FAQs
### Q: What is R used for?
A: R is primarily used for statistical analysis, data visualization, and data science tasks. It supports various analytical techniques including linear and nonlinear modeling, statistical testing, time-series analysis, classification, clustering, and more. Its extensive package ecosystem makes it suitable for specialized applications like genomics, finance, and social sciences.

### Q: Is R free to use?
A: Yes, R is free software distributed under the GNU General Public License version 2.0. It can be downloaded and used without cost from the official website (https://www.r-project.org). Being part of the free software movement, users have the freedom to run, study, share, and modify the software.

### Q: How does R compare to Python?
A: While both R and Python are popular choices for data science, R has stronger built-in support for statistical analysis and visualization out of the box. Python excels in general-purpose programming and integration with web applications. R's syntax is often considered more intuitive for statisticians, whereas Python offers broader versatility across different domains.

## Why It Matters
R plays a crucial role in modern data analysis and statistical computing. As one of the leading tools in data science, it empowers researchers, analysts, and scientists to perform sophisticated statistical analyses and create compelling visualizations. Its open-source nature fosters innovation through community contributions, resulting in thousands of packages that extend its functionality. From academic research to business intelligence, R provides essential infrastructure for making sense of complex datasets and driving evidence-based decision-making.

## Notable For
- Pioneering integrated statistical computing and graphics in a single open-source platform
- Hosting over 18,000 extension packages through the Comprehensive R Archive Network (CRAN)
- Serving as the foundation for major projects like Bioconductor for genomic data analysis
- Supporting advanced visualization capabilities through ggplot2 and other graphical frameworks
- Being adopted globally in universities, research institutions, and enterprises for statistical computing

## Body
### Origins and Development
R was conceived in 1993 by Ross Ihaka and Robert Gentleman at the Department of Statistics, University of Auckland, New Zealand. The initial public release occurred in 1995, followed by the first stable version (1.0.0) in February 2000. The language draws significant influence from the S programming language developed at Bell Laboratories, along with elements from Common Lisp and XLispStat.

The development of R aligns closely with the principles of the free software movement. It is licensed under the GNU General Public License version 2.0, ensuring users' freedoms to use, study, modify, and redistribute the software. Since its early days, R has been maintained by The R Foundation for Statistical Computing, which continues to oversee its evolution today.

### Technical Characteristics
R operates using multiple programming paradigms including functional, object-oriented, procedural, and reflective programming styles. It employs dynamic typing and supports cross-platform execution on Windows, macOS, and various Unix-like systems including BSD derivatives. Internally, R itself is implemented using a combination of R, Fortran, and C codebases.

Key features include robust support for data manipulation, statistical modeling, and visualization. Users benefit from native support for reading and writing formats such as CSV files, Excel documents, HDF5, and proprietary R data structures. Additionally, R integrates seamlessly with external databases and APIs, enhancing its utility in diverse environments.

### Ecosystem and Community
Central to R’s success is its vibrant ecosystem centered around CRAN—the Comprehensive R Archive Network—which hosts over 18,000 contributed packages spanning numerous disciplines. These range from domain-specific solutions like `limma` for microarray data analysis and `ggtree` for phylogenetic tree visualization, to general-purpose utilities such as `dplyr` for data wrangling and `gganimate` for animated graphics.

Beyond CRAN, additional repositories like Bioconductor cater specifically to biological research, while GitHub serves as a hub for experimental and cutting-edge developments. Active communities exist across forums like Stack Overflow, Reddit (r/rlanguage), and dedicated mailing lists, fostering collaboration among practitioners worldwide.

### Applications and Impact
In practice, R finds widespread adoption across sectors requiring rigorous statistical analysis—from clinical trials in pharmaceuticals to market forecasting in finance. Educational institutions integrate R into curricula due to its accessibility and depth, preparing future generations of data professionals. Tools built atop R, such as RStudio IDE and BlueSky Statistics GUI, further democratize access for non-programmers seeking analytical power without steep learning curves.

Moreover, R contributes significantly to reproducible research practices through literate programming tools like `knitr` and `bookdown`, enabling seamless blending of narrative text with executable code. This capability enhances transparency and rigor in scholarly communication, reinforcing trust in findings derived from empirical studies.

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## References

1. Free Software Directory
2. [Source](https://www.r-project.org/logo/)
3. [Source](https://www.r-project.org/contributors.html)
4. [Source](https://marketplace.sshopencloud.eu/tool-or-service/vehc3B)
5. [Source](https://tapor.ca/tools/238)
6. [Source](https://github.com/JohnMarkOckerbloom/ftl/blob/master/data/wikimap)
7. Library of Congress Authorities
8. [Source](https://www.r-project.org/about.html)
9. [Source](http://librestats.com/2011/08/27/how-much-of-r-is-written-in-r/)
10. [R: A Language for Data Analysis and Graphics](https://www.jstor.org/stable/1390807)
11. [R 3.0.1 is released. 2013](https://stat.ethz.ch/pipermail/r-announce/2013/000563.html)
12. [2013](http://www.r-bloggers.com/r-3-0-2-and-rstudio-0-9-8-are-released/)
13. [2013](https://stat.ethz.ch/pipermail/r-announce/2013/000567.html)
14. [R 3.0.0 is released. 2013](https://stat.ethz.ch/pipermail/r-announce/2013/000561.html)
15. [R 3.0.3 is released. 2014](https://stat.ethz.ch/pipermail/r-announce/2014/000569.html)
16. [R 3.1.0 is released. 2014](https://stat.ethz.ch/pipermail/r-announce/2014/000572.html)
17. [R 3.1.1 is released. 2014](https://stat.ethz.ch/pipermail/r-announce/2014/000575.html)
18. [R-1.0.0 is released. 2000](https://stat.ethz.ch/pipermail/r-announce/2000/000127.html)
19. [R 2.0.0 is released. 2004](https://stat.ethz.ch/pipermail/r-announce/2004/000427.html)
20. [R 3.1.2 is released. 2014](https://stat.ethz.ch/pipermail/r-announce/2014/000578.html)
21. [R 3.2.2 is released. 2015](https://stat.ethz.ch/pipermail/r-announce/2015/000589.html)
22. [R 3.2.3 released. 2015](http://www.r-bloggers.com/r-3-2-3-released/)
23. [R 3.2.3 is released. 2015](https://stat.ethz.ch/pipermail/r-announce/2015/000593.html)
24. [R 3.1.3 is released. 2015](https://stat.ethz.ch/pipermail/r-announce/2015/000582.html)
25. [R 3.2.4 is released. 2016](https://stat.ethz.ch/pipermail/r-announce/2016/000597.html)
26. [R 3.2.4-revised is released. 2016](https://stat.ethz.ch/pipermail/r-announce/2016/000598.html)
27. [R 3.2.5 is released. 2016](https://stat.ethz.ch/pipermail/r-announce/2016/000601.html)
28. [2016](https://www.r-bloggers.com/r-3-3-0-is-released/)
29. [R 3.3.0 is released. 2016](https://stat.ethz.ch/pipermail/r-announce/2016/000602.html)
30. [R 3.3.1 is released. 2016](https://stat.ethz.ch/pipermail/r-announce/2016/000604.html)
31. [Source](https://cran.cnr.berkeley.edu/src/base/R-3/)
32. [R 3.3.2 is released. 2016](https://stat.ethz.ch/pipermail/r-announce/2016/000608.html)
33. [Source](https://cran.r-project.org/doc/manuals/r-release/NEWS.html)
34. [Source](https://stat.ethz.ch/pipermail/r-announce/2017/000612.html)
35. [Source](https://stat.ethz.ch/pipermail/r-announce/2017/000616.html)
36. [Source](https://stat.ethz.ch/pipermail/r-announce/2017/000619.html)
37. [Source](https://stat.ethz.ch/pipermail/r-announce/2017/000623.html)
38. [Source](https://stat.ethz.ch/pipermail/r-announce/2018/000626.html)
39. [Source](https://stat.ethz.ch/pipermail/r-announce/2018/000628.html)
40. [Source](https://stat.ethz.ch/pipermail/r-announce/2018/000630.html)
41. [Source](https://hypatia.math.ethz.ch/pipermail/r-announce/2018/000634.html)
42. [R 3.5.3 is released](https://stat.ethz.ch/pipermail/r-announce/2019/000638.html)
43. [R 3.5.3 now available](https://www.r-bloggers.com/r-3-5-3-now-available/)
44. [R 3.6.0 is released](https://stat.ethz.ch/pipermail/r-announce/2019/000641.html)
45. [Source](https://stat.ethz.ch/pipermail/r-announce/2019/000643.html)
46. [R 3.6.2 is released. 2019](https://stat.ethz.ch/pipermail/r-announce/2019/000647.html)
47. [R 3.6.3 is released. 2020](https://stat.ethz.ch/pipermail/r-announce/2020/000650.html)
48. [R 4.0.0 is released. 2020](https://stat.ethz.ch/pipermail/r-announce/2020/000653.html)
49. [R 4.0.1 is released. 2020](https://stat.ethz.ch/pipermail/r-announce/2020/000655.html)
50. [R 4.0.2 is released. 2020](https://stat.ethz.ch/pipermail/r-announce/2020/000658.html)