dplyris a new package which provides a set of tools for efficiently manipulating datasets in R.
dplyris the next iteration of
plyr, focussing on only data frames.
dplyris faster, has a more consistent API and should be easier to use. There are three key ideas that underlie
- Your time is important, so Romain Francois has written the key pieces in Rcpp to provide blazing fast performance. Performance will only get better over time, especially once we figure out the best way to make the most of multiple processors.
- Tabular data is tabular data regardless of where it lives, so you should use the same functions to work with it. With
dplyr, anything you can do to a local data frame you can also do to a remote database table. PostgreSQL, MySQL, SQLite and Google bigquery support is built-in; adding a new backend is…
View original post 493 more words