Data Analysis using R
Unit 1
History and Overview of R
• The R language came to use quite a bit after S had been
developed. One key limitation of the S
• language was that it was only available in a commericial
package, S-PLUS.
• In 1991, R was created by Ross Ihaka and Robert Gentleman
in the Department of Statistics at the University of Auckland.
• In 1993 the first announcement of R was made to the public.
• Ross’s and Robert’s experience developing R is documented
in a 1996 paper in the Journal of Computational and
Graphical Statistics.
History and Overview of R
• In 1995, Martin Mächler made an important contribution by convincing
Ross and Robert to use the GNU General Public License to make R free
software.
• This was critical because it allowed for the source code for the entire R
system to be accessible to anyone who wanted to tinker with it (more on
free software later).
• In 1996, a public mailing list was created (the R-help and R-devel lists)
and in 1997 the R Core Group was formed, containing some people
associated with S and S-PLUS.
• Currently, the core group controls the source code for R and is solely able
to check in changes to the main R source tree.
• Finally, in 2000 R version 1.0.0 was released to the public.
History and Overview of R
Basic Features of R
• In the early days, a key feature of R was that its syntax is very similar to
S, making it easy for S-PLUS users to switch over. While the R’s syntax is
nearly identical to that of S’s, R’s semantics, while superficially similar
to S, are quite different.
• In fact, R is technically much closer to the Scheme language than it is
to the original S language when it comes to how R works under the
hood.
• Today R runs on almost any standard computing platform and
operating system. Its open source nature means that anyone is free to
adapt the software to whatever platform they choose. Indeed, R has
been reported to be running on modern tablets, phones, PDAs, and
game consoles.
History and Overview of R
Basic Features of R
• One nice feature that R shares with many popular open source projects
is frequent releases. These days there is a major annual release,
typically in October, where major new features are incorporated and
released to the public.
• Throughout the year, smaller-scale bugfix releases will be made as
needed.
• The frequent releases and regular release cycle indicates active
development of the software and ensures that bugs will be addressed in
a timely manner.
• Of course, while the core developers control the primary source tree for
R, many people around the world make contributions in the form of
new feature, bug fixes, or both.
History and Overview of R
Basic Features of R
• Another key advantage that R has over many other statistical
packages (even today) is its sophisticated graphics capabilities. R’s
ability to create “publication quality” graphics has existed since the
very beginning and has generally been better than competing
packages.
• Today, with many more visualization packages available than
before, that trend continues.
• R’s base graphics system allows for very fine control over
essentially every aspect of a plot or graph.
• Other newer graphics systems, like lattice and ggplot2 allow for
complex and sophisticated visualizations of high-dimensional data.
History and Overview of R
Basic Features of R
• Finally, one of the joys of using R has nothing to do with the
language itself, but rather with the active and vibrant user
community.
• In many ways, a language is successful inasmuch as it creates a
platform with which many people can create new things.
• R is that platform and thousands of people around the world
have come together to make contributions to R, to develop
packages, and help each other use R for all kinds of applications.
• The R-help and R-devel mailing lists have been highly active for
over a decade now and there is considerable activity on web sites
like Stack Overflow.
History and Overview of R
Design of the R System
• The primary R system is available from the
Comprehensive R Archive Network, also known as
CRAN. CRAN also hosts many add-on packages that
can be used to extend the functionality of R.
• The R system is divided into 2 conceptual parts
1. The “base” R system that you download from
CRAN: Linux¹⁶ Windows¹⁷ Mac¹⁸ Source Code¹⁹
2. Everything else.
History and Overview of R
Design of the R System
• R functionality is divided into a number of packages.
• The “base” R system contains, among other things, the base
package which is required to run R and contains the most
fundamental functions.
• The other packages contained in the “base” system include
utils, stats, datasets, graphics, grDevices, grid, methods,
tools, parallel, compiler, splines, tcltk, stats4.
• There are also “Recommended” packages: boot, class,
cluster, codetools, foreign, KernSmooth, lattice, mgcv, nlme,
rpart, survival, MASS, spatial, nnet, Matrix.
R data types and objects
Entering Input
• At the R prompt we type expressions. The <- symbol is the
assignment operator.
> x <- 1
> print(x)
[1] 1
>x
[1] 1
> msg <- "hello"
The grammar of the language determines whether an expression
is complete or not.
