[scishop]

Things that are likely to trip up new R programmers:

* Function arguments are always passed by value. Objects are copied if they are modified in a function.

* Function arguments are lazy evaluated.

* Watch out for automatic factor conversion when importing data. R will display your string data as text, but behind the scenes it will treat it as an integer.

* R is slow. Really, really slow. All your intensive calculations should be handled by libraries written in C, Fortran or some other compiled language. Your R code should be mostly for glueing things together.

[bachmeier]

In my experience teaching R, the single biggest issue is that it is a dynamic language that is in love with silent casting [or really returning objects with unexpected types]. Although other bugs might be more common, none will frustrate the user more than the type of a variable changing without warning, and most of the time the error message refers to something else.

A couple of examples are stripping the time series attributes of a ts object and default conversion of a row of a matrix to a vector. These are the cases where they come to my office and say they have no idea what's going on. After using R for a decade, I know the language well enough that these are about the only errors I get.

[jghn]

1) can always use environments! :)

Okay, I'll stop at 1).

Having used R for over 15 years now, the one "feature" which still makes me shake my head is the partial evaluation of function arguments. If function foo has an argument 'blah' and you say foo(bl=5), it'll autocomplete that to 'blah' if there's nothing better to use.

The number of bugs I've found due to that ....