Description Usage Arguments Tbl types Scoped grouping See Also Examples
Most data operations are done on groups defined by variables.
group_by()
takes an existing tbl and converts it into a grouped tbl
where operations are performed "by group". ungroup()
removes grouping.
1 2 3 |
.data |
a tbl |
... |
Variables to group by. All tbls accept variable names. Some tbls will accept functions of variables. Duplicated groups will be silently dropped. |
add |
When |
x |
A |
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:
data.frame: grouped_df
data.table: dtplyr::grouped_dt
SQLite: src_sqlite()
PostgreSQL: src_postgres()
MySQL: src_mysql()
The three scoped variants (group_by_all()
, group_by_if()
and
group_by_at()
) make it easy to group a dataset by a selection of
variables.
Other grouping functions: group_by_all
,
group_indices
, group_rows
,
group_size
, groups
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | 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()
|
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