Programming in R makes serious statistics serious fun

What do serious statisticians use for doing their work? They all use R.

R is an interactive programming environment designed for data analysis. It has its own language (which can confusingly be called S for historical reasons), its own large library of basic and statistical functions, its own quality-controlled repository of contributed libraries, its own interactive shell with integrated plotting. In its own domain, it as complete a working language as Python, Perl or PHP. (It is certainly more mature than Javascript!)

Here are some features of the language to get programmers excited:

Functions are objects.
rmean = function(x=50) mean(rnorm(x))

Inline anonymous functions are easy.
boot(data, function(data, x){ mean(data) - mean(x) })

Numbers are always arrays.
mean(1) == 1

Arithmetic is vectorized.
c(1,2,3) * 2 == c(2,4,6)

Boolean operations are vectorized.
(c(1,2,3) == 3) ==  c(FALSE, FALSE, TRUE)

Object-oriented support with simple prototype system.
df = data.frame(c(1,2,3))
class(df) == "data.frame"
print.data.frame(df)
print(df) #same as previous because of method lookup

Code blocks are objects.
plot(c(1,2,3))
# graph shows "c(1,2,3)" as axis label... so cool!

More excitement: Django + R graphing .