What makes R appealing is basically all statistical methods are available in it -- and it is often the initial implementation language of new methods in statistics. Often an R program involves very little programming as such other than to read in data, run some existing statistical methods on it and print or plot the results. I'm not a particular fan of the language itself (I kind of wish XLispStat hadn't died), but every time I feel like checking out Python or Julia I find things I need that haven't been implemented yet in those languages that are in R.