In this section, we're going to share some of the common data mining and aggregation operations that can be performed on data.frame, dplyr, and data.table.
First, we are going to learn how to use a few functions in Base R to perform basic manipulation operations. We'll then cover dplyr and data.table—two of the most well known and powerful packages in the R world today for managing data. tibble is an alternative to data.frame that is used widely in conjunction with dplyr and adheres more closely to how data.frame behave and uses the same conventions for slicing, indexing, and other operations as data.frame. The latter, data.table, uses a slightly different convention, but is extremely powerful, especially for ...
