When we discuss data analysis, we usually think of the operations performed on data that yield new insights about whatever phenomena the data reflect. However, as a prelude to doing such operations, it is better to clean up the data that we start with and wrangle it into an analyzable form. Unfortunately, such wrangling typically occupies at least as much time as (if not more than) the actual analysis in most real world projects. Thus, data management is probably one of the most useful skills in data analysis, and it is given ample coverage in books on database programming, but little coverage in most texts on R.

Data wrangling is a term that is applied to activities that make data more usable by changing their form, but not their meaning. Data wrangling may involve reformatting data, mapping data from one data model to another, or converting data into more consumable forms. Such data wrangling activities make it easier to submit data to a database or...