This is from a session I did with the UBC R Study Group. Loops can be convenient for applying the same steps to big/distributed datasets, running simulations, and writing your own resampling/bootstrapping analyses. Here are some ways to make them faster.
1. Don’t grow things in your loops.
2. Vectorize where possible. i.e. pull things out of the loop.
3. Do less work in the loop if you can.