The tidyverse set of packages (including dplyr, tidyr, and magrittr) have had a huge influence on data processing and analysis in R through their application of the tidy way of working. In essence, this means that data is kept in a particular tidy format, in which each row holds a single observation and each column keeps all observations of a single variable. Such a structure means that analytical steps have predictable inputs and outputs and can be built into fluid and expressive pipelines. However, most base R objects are not tidy and can often need significant programming work to extract the bits that are needed to assemble objects for use downstream. In this recipe, we'll look at some functions for automatically converting some common base R objects into a tidy dataframe.