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".
group_by(.data, ..., add = FALSE)group_by_(.data, ..., .dots, add = FALSE)
a tbl
variables to group by. All tbls accept variable names, some will also accept functions of variables. Duplicated groups will be silently dropped.
By default, when add = FALSE, group_by will
override existing groups. To instead add to the existing groups,
use add = TRUE
Used to work around non-standard evaluation. See
vignette("nse") for details.
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: grouped_dt
SQLite: src_sqlite
PostgreSQL: src_postgres
MySQL: src_mysql
ungroup for the inverse operation,
groups for accessors that don't do special evaluation.
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())
by_vs
summarise(by_vs, n = sum(n))
# use ungroup() to remove if not wanted
summarise(ungroup(by_vs), n = sum(n))
# You can group by expressions: this is just short-hand for
# a mutate/rename followed by a simple group_by
group_by(mtcars, vsam = vs + am)
group_by(mtcars, vs2 = vs)
# You can also group by a constant, but it's not very useful
group_by(mtcars, "vs")
# By default, group_by sets groups. Use add = TRUE to add groups
groups(group_by(by_cyl, vs, am))
groups(group_by(by_cyl, vs, am, add = TRUE))
# Duplicate groups are silently dropped
groups(group_by(by_cyl, cyl, cyl))
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