If you’ve been using R for a while, you’ve likely accumulated a hodgepodge of useful code along the way. Said hodgepodge might include functions you source into multiple projects; bits and bobs that you copy and paste where needed; or code that solved a particularly esoteric problem and will never be applicable elsewhere, but you still enjoy revisiting sometimes. We all do it. If you’re anything like me, your personal library of code has grown gradually and haphazardly.
When discussing how to speed up slow R code, my first question is what is your computer spec? It’s always surprised me that people are wondering why analysing big data is slow, yet they are using a five-year-old cheap laptop. Spending a few thousand pounds would often make their problems disappear. To quantify the impact of the CPU on analysis, I created the package {benchmarkme}. The aim of this package is to provide a set of benchmarks routines and data from past runs.