[steve19]

I love R, but it can be frustrating to code with and learn. Some of its datatypes are immensely powerful but work in mysterious ways. It allows you to manipulate expressions in a LISP macro-like fashion which, when used badly by library authors, can make many things appear magical (and inconsistant). There are many inconsistencies in the standard library because of different programming paradigms used (for example (s|m|t|r)apply() vs. Map() and filtering with df$col[] vs. subset() vs. Filter() ).

Yet I love writing code in it. So much can be done in so little code. I am always amazed at how little code I write to accomplish a task.

The RStudio IDE ( http://rstudio.org/ ) is a very pleasant environment to write code in.

[disgruntledphd2]

Map and subset would be discouraged, they are just wrappers around the apply functions and [] anyway.

[wildanimal]

I wouldn't discourage them uniquivocally - for instance, 'subset' is an idiom often used in the context of data/relational tables. That matters a little bit (enough to pay a little penalty in raw performance), I would think.

[minikomi]

What sort of tasks have you found where it really shines?