What I Can Do With R?

Question

Hello,

I was seeing that here we have a new language(for me it is), R, but I was viewing it's site and as I can see we only can do graphics with it, but there is more things that we can do with it?

Answer 1

R is a statistical programming environment. If you want to do statistical analysis, you may find R very useful. But I wouldn't recommend it for non-statistical programming. The language is hard to understand unless you think like a statistician. Here are some notes on coming to R from other programming languages.

Answer 2

Roughly, anything.

R is a high-level programming language (i.e. built on top of other languages like c), but it was designed primarily for statistics.

In my experience, it is becoming the best language for all kinds of data analysis, thanks in part to the strong community around CRAN. You will quickly see the power of the language if you spend a few minutes browsing the R questions on stackoverflow.

A better question would be what should I do with R?

Answer 3

I disagree that this is hard language. Indeed this is for statistical purposes, but I was sucessfully working with R to process finantial (trading) data.

It has very nice plugin management approach. Building plugins is very easy (c/c++) for any external inputs (Excel, db's).

PS. Its not new language.

Answer 4

If everything else fails, you can always read the documentation, starting with the FAQ which answers, among others, this question:

2.1 What is R?

R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files.

The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S (see What is S?) and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme. See What are the differences between R and S?, for further details.

The core of R is an interpreted computer language which allows branching and looping as well as modular programming using functions. Most of the user-visible functions in R are written in R. It is possible for the user to interface to procedures written in the C, C++, or FORTRAN languages for efficiency. The R distribution contains functionality for a large number of statistical procedures. Among these are: linear and generalized linear models, nonlinear regression models, time series analysis, classical parametric and nonparametric tests, clustering and smoothing. There is also a large set of functions which provide a flexible graphical environment for creating various kinds of data presentations. Additional modules (“add-on packages”) are available for a variety of specific purposes (see R Add-On Packages).

R was initially written by Ross Ihaka and Robert Gentleman at the Department of Statistics of the University of Auckland in Auckland, New Zealand. In addition, a large group of individuals has contributed to R by sending code and bug reports.

Since mid-1997 there has been a core group (the “R Core Team”) who can modify the R source code archive. The group currently consists of Doug Bates, John Chambers, Peter Dalgaard, Robert Gentleman, Kurt Hornik, Stefano Iacus, Ross Ihaka, Friedrich Leisch, Thomas Lumley, Martin Maechler, Duncan Murdoch, Paul Murrell, Martyn Plummer, Brian Ripley, Duncan Temple Lang, Luke Tierney, and Simon Urbanek.

R has a home page at http://www.R-project.org/. It is free software distributed under a GNU-style copyleft, and an official part of the GNU project (“GNU S”).

The original FAQ entry has a few hyperlinks that the copy&paste omitted.