My vote:
1. Symbolic function arguments:
fn = function(a, b)
{
a/b
}
fn(b=10, a=2)
2. Names for elements of a vector and matrices
v = c(a=1, b=2)
v['a'] = v['a'] * 2
same for matrices
3. about 10,000 user-contributed packages on CRAN
4. weird things like
a = numeric(10)
a[1:10] = 1:2
<no error message>
a
answer: five times 1:2
which guarantee happy debugging
5. and, of course, much built-in statistical stuff
Am 20.08.2012 20:02, schrieb johannes rara:
My intention is to give a presentation about R programming language
for software developers. I would like to ask, what are the things that
make R different from other programming languages? What are the
specific cases where Java/C#/Python developer might say "Wow, that was
neat!"? What are the things that are easy in R, but very difficult in
other programming languages (like Java)?
Thanks,
-J
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