Recently, I was trying to calculate the percentiles of a set of variables within a data set grouped by another variable. However, I quickly ran into the realization that this is not very straight forward when using dplyr’s summarize. Before I demonstrate, let’s load the libraries that we will need. library(dplyr) library(purrr) If you don’t believe me when I say that it is not straight forward, go ahead and try to run the following block of code.
Introduction purrr is an incredibly powerful package that has greatly enhanced my R programming abilities. purrr has applications in pretty much any situation. One of the most useful situations, IMHO, is in the creation of a dynamic number of shiny UI elements. This can be extremely useful if you want to be able to create a dynamic number of ui elements (whether that be inputs or outputs) based on either user selection or the data being used.
Introduction The other day, a question was posted on RStudio Community about performing Principal Component Analysis (PCA) in a tidyverse workflow. Conveniently, I had literally just worked through this process the day before and was able to post an answer. While most questions and answers are good as they are on forum sites, I thought this one might be worth exploring a little more since using the tidyverse framework makes PCA much easier, in my opinion.