group_by

0th

Percentile

Group a tbl by one or more variables.

Most data operations are useful done on groups defined by variables in the the dataset. The group_by function takes an existing tbl and converts it into a grouped tbl where operations are performed "by group".

Usage
group_by(x, ..., add = TRUE)
Arguments
x
a tbl
...
variables to group by. All tbls accept variable names, some will also accept functons of variables. Duplicated groups will be silently dropped.
add
By default, when add = TRUE, group_by will add groups to existing. To instead set the groups to a set of new values, use add = FALSE
Tbl types

group_by is an S3 generic with methods for the three built-in tbls. See the help for the corresponding classes and their manip methods for more details:

See Also

ungroup for the inverse operation, group for accessors that don't do special evaluation.

Aliases
  • group_by
Examples
by_cyl <- group_by(mtcars, cyl)
summarise(by_cyl, mean(disp), mean(hp))
filter(by_cyl, disp == max(disp))

# summarise peels off a single layer of grouping
by_vs_am <- group_by(mtcars, vs, am)
by_vs <- summarise(by_vs_am, n = n())
groups(by_vs)
summarise(by_vs, n = sum(n))
# use ungroup() to remove if not wanted

# You can group by expressions: this is just short-hand for
# a mutate followed by a simple group_by
group_by(mtcars, vsam = vs + am)

# By default, group_by increases grouping. Use add = FALSE to set groups
groups(group_by(by_cyl, vs, am))
groups(group_by(by_cyl, vs, am, add = FALSE))

# Duplicate groups are silently dropped
groups(group_by(by_cyl, cyl, cyl))
Documentation reproduced from package dplyr, version 0.1.1, License: MIT + file LICENSE

Community examples

Kaleema.bi@gmail.com at Nov 23, 2017 dplyr v0.7.3

by_cyl <- mtcars %>% group_by(cyl) # grouping doesn't change how the data looks (apart from listing # how it's grouped): by_cyl # It changes how it acts with the other dplyr verbs: by_cyl %>% summarise( disp = mean(disp), hp = mean(hp) ) by_cyl %>% filter(disp == max(disp)) # Each call to summarise() removes a layer of grouping by_vs_am <- mtcars %>% group_by(vs, am) by_vs <- by_vs_am %>% summarise(n = n()) by_vs by_vs %>% summarise(n = sum(n)) # To removing grouping, use ungroup by_vs %>% ungroup() %>% summarise(n = sum(n)) # You can group by expressions: this is just short-hand for # a mutate/rename followed by a simple group_by mtcars %>% group_by(vsam = vs + am) # By default, group_by overrides existing grouping by_cyl %>% group_by(vs, am) %>% group_vars() # Use add = TRUE to instead append by_cyl %>% group_by(vs, am, add = TRUE) %>% group_vars() # }