Use this tag for questions relating to functions from the dplyr package, such as group_by, summarize, filter, and select.
The r dplyr
package is the next iteration of the plyr package. It has three main goals:
- Identify the most important data manipulation tools needed for data analysis and make them easy to use from R.
- Provide fast performance for in-memory data by writing key pieces in C++.
- Use the same interface to work with data no matter where it's stored, whether in a
data.frame
, adata.table
or a database.
Repositories
Vignettes
Some vignettes have been moved to other related packages.
- Tibbles (from
tibble
package) - Databases (from
dbplyr
package) - Introduction to dplyr
- Adding a new SQL backend (from
dbplyr
package) - Programming with
dplyr
- Two-table verbs
- Window functions and grouped mutate/filter