Data Structure in R

Today we will begin a trip into the Tidyverse. One of the strongest cases for R is the ease with which it enables us to manipulate data for analyses and generate visualizations. Common manipulations that we need to do to data before we can start descriptive or modeling work include filtering to relevant observations, transforming variables, and generating summary statistics. The Tidyverse set of packages, and dplyr in particular, provide an increasingly popular approach to implement these types of manipulations in R.