dplyr

dplyr

Original author(s)	Hadley Wickham
Initial release	January 7, 2014 (2014-01-07)
Stable release	1.0.0 / June 1, 2020 (2020-06-01)
Written in	R
License	GPLv2
Website	dplyr.tidyverse.org//

One of the core packages of the tidyverse in R, dplyr is primarily a set of functions designed to enable dataframe manipulation in an intuitive, user-friendly way. Data analysts typically use dplyr in order to transform existing datasets into a format better suited for some particular type of analysis, or data visualization.

Authored primarily by Hadley Wickham, dplyr was launched in 2014.

The five core verbs

While dplyr actually includes several dozen functions that enable various forms of data manipulation, the package features five primary verbs:

filter(), which is used to extract rows from a dataframe, based on conditions specified by a user;

select(), which is used to subset a dataframe by its columns;

arrange(), which is used to sort rows in a dataframe based on attributes held by particular columns;

mutate(), which is used to create new variables, by altering and/or combining values from existing columns; and

summarize(), also spelled summarise(), which is used to collapse values from a dataframe into a single summary.

Additional functions

In addition to its five main verbs, dplyr also includes several other functions that enable exploration and manipulation of dataframes. Included among these are:

count(), which is used to sum the number of unique observations that contain some particular value or categorical attribute;

slice_max(), which returns a data subset that contains the rows with the highest number of values for some particular variable;

slice_min(), which returns a data subset that contains the rows with the lowest number of values for some particular variable.

Built-in datasets

The dplyr package comes with five datasets. These are: band_instruments, band_instruments2, band_members, starwars, storms.