I recently completed Colin Fay’s excellent DataCamp course, Intermediate Functional Programming with purrr (full disclosure: I work at DataCamp, but part of why I joined was that I was a big fan of the short, interactive course format). Although I’ve used the purrr package before, there were a lot of functions in this course that were new to me. I wrote this post to hopefully demystify purrr a bit for those who find it overwhelming and illustrate some of its lesser known functions.
In early 2018, I gave a few conference talks on “The Lesser Known Stars of the Tidyverse.” I focused on some packages and functions that aren’t as well known as the core parts of ggplot2 and dplyr but are very helpful in exploratory analysis. I walked through an example analysis of Kaggle’s 2017 State of Data Science and Machine Learning Survey to show how I would use these functions in an exploratory analysis.