Messy data, no matter what definition you use, presents a huge roadblock for people who work with data. This chapter focused on two of the most notorious and prolific culprits: missing data and data that has not been cleaned or audited for quality.
On unsanitized data, we saw that the perhaps optimal solution (visually auditing the data) was untenable for moderately sized datasets or larger. We discovered that the grammar of the package assertr provides a mechanism to offload this auditing process to R. You now have a few assertr checking recipes under your belt for some of the more common manifestations of the mistakes that plague data that have not been scrutinized.
