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What is R?

Introduction to R

When you see powerful analytics, statistics, and visualizations used by data scientists and business leaders, chances are that the R language is behind them. Open-source R is the statistical programming language that data experts the world over use for everything from mapping broad social and marketing trends online to developing financial and climate models that help drive our economies and communities.

R was first implemented in the early 1990’s by Robert Gentleman and Ross Ihaka, both faculty members at the University of Auckland. The R language was closely modeled on the S Language for Statistical Computing conceived by John Chambers, Rick Becker, Trevor Hastie, Allan Wilks and others at Bell Labs in the mid 1970s, and made publicly available in the early 1980’s. Robert and Ross established R as an open source project in 1995. Since 1997, the R project has been managed by the R Core Group. And, in February 2000, came the first release of R. See also Ross Ihaka’s brief account of how R got started highlights some of the connections between R and S.

They, along with many others, kept working on and using R. They continue to create new tools for R and fing new applications for R every day. There are over 10,000 user-created libraries that were built to enhance R functionality. These packages have crowdsourced quality-validation and support from recognized leaders in every field. All of this is great because R is the best at what it does:

R lets experts quickly, easily interpret and interact with and visualize data

Join the rapidly growing community of R users worldwide to see how open-source R continues to shape the future of statistical analysis and data science.

The R Open Source Project Structure

At the center of the R Open Source Project and R Community is R Core, a group of approximately twenty developers who maintain R and guide its evolution. The official public structure for the R Community is provided by the R Foundation, a not for profit organization with an impressive list of members and supporters. The R Foundation ensures the financial stability of the R-project and holds and administers the copyright of R software and its documentation.

What You Can Expect from R

R is a language! You do data analysis by writing functions and scripts, not by pointing and clicking. That may sound daunting if you are new to programming, but R is an easy language to learn, and a very natural and expressive one for data analysis. Working with R is an interactive experience that encourages experimentation, exploration and play. It is likely that whatever your area of interest, you will find R packages (libraries of functions) that will be immediately helpful. And, of course, R is renowned for its capabilities to visualize data.

About Microsoft R Open

Microsoft R Open is the enhanced distribution of R from Microsoft Corporation. Microsoft R Open is a complete open source platform for statistical analysis and data science, which is free to download and use.

The current version, Microsoft R Open 3.4.0, is based on (and 100% compatible with) the statistical language, R-3.4.0, and includes additional capabilities for performance, reproducibility and platform support. Learn more...

Get Microsoft R Open today! You can download and install Microsoft R Open right from this site.

R Packages

R Packages are collections of R functions, data, and compiled code. While R comes with a set of packages by default, there are many more packages that can be added to extend the capabilities of R. Whether you're using R to optimize portfolios, analyze genomic sequences, or to predict component failure times, experts in every domain have made resources, applications and code available for free, online.

Browse for packages by name, author, title, and published date or find packages organized by task.

Learn more about packages and task views here.

R Contributors

The current version of Open R is the result of years of collaboration from people all over the globe. R was initially written by Robert Gentleman and Ross Ihaka, who were known as "R & R" of the Statistics Department of the University of Auckland.

Since mid-1997, there has been a core group of contributors with write-access to the R source. The current set of contributors are:

  • Douglas Bates
  • John Chambers
  • Peter Dalgaard
  • Robert Gentleman
  • Kurt Hornik
  • Ross Ihaka
  • Tomas Kalibera
  • Michael Lawrence
  • Friedrich Leisch
  • Uwe Ligges
  • Thomas Lumley
  • Martin Maechler
  • Martin Morgan
  • Duncan Murdoch
  • Paul Murrell
  • Martyn Plummer
  • Brian Ripley
  • Deepayan Sarkar
  • Duncan Temple Lang
  • Luke Tierney
  • Simon Urbanek
  • plus Heiner Schwarte up to October 1999, Guido Masarotto up to June 2003, Stefano Iacus up to July 2014 and Seth Falcon up to August 2015.

Read more about these and other contributors.