summarise_all {dplyr} | R Documentation |
summarise_all()
and mutate_all()
apply the functions
to all (non-grouping) columns. summarise_at()
and
mutate_at()
allow you to select columns
using the same name-based select_helpers
as with
select()
. summarise_if
() and
mutate_if
() operate on columns for which a predicate returns
TRUE
. Finally, summarise_each()
and
mutate_each()
are older variants that will be
deprecated in the future.
summarise_all(.tbl, .funs, ...) mutate_all(.tbl, .funs, ...) summarise_if(.tbl, .predicate, .funs, ...) mutate_if(.tbl, .predicate, .funs, ...) summarise_at(.tbl, .cols, .funs, ...) mutate_at(.tbl, .cols, .funs, ...) summarize_all(.tbl, .funs, ...) summarize_at(.tbl, .cols, .funs, ...) summarize_if(.tbl, .predicate, .funs, ...)
.tbl |
a tbl |
.funs |
List of function calls generated by
|
... |
Additional arguments for the function calls. These are evaluated only once. |
.predicate |
A predicate function to be applied to the columns
or a logical vector. The columns for which |
.cols |
A list of columns generated by |
A data frame. By default, the newly created columns have the shortest names needed to distinguish the output. To force inclusion of a name, even when not needed, name the input (see examples for details).
by_species <- iris %>% group_by(Species) # One function by_species %>% summarise_all(n_distinct) by_species %>% summarise_all(mean) # Use the _at and _if variants for conditional mapping. by_species %>% summarise_if(is.numeric, mean) # summarise_at() can use select() helpers with the vars() function: by_species %>% summarise_at(vars(Petal.Width), mean) by_species %>% summarise_at(vars(matches("Width")), mean) # You can also specify columns with column names or column positions: by_species %>% summarise_at(c("Sepal.Width", "Petal.Width"), mean) by_species %>% summarise_at(c(1, 3), mean) # You can provide additional arguments. Those are evaluated only once: by_species %>% summarise_all(mean, trim = 1) by_species %>% summarise_at(vars(Petal.Width), mean, trim = 1) # You can provide an expression or multiple functions with the funs() helper. by_species %>% mutate_all(funs(. * 0.4)) by_species %>% summarise_all(funs(min, max)) # Note that output variable name must now include function name, in order to # keep things distinct. # Function names will be included if .funs has names or whenever multiple # functions are used. by_species %>% mutate_all(funs("in" = . / 2.54)) by_species %>% mutate_all(funs(rg = diff(range(.)))) by_species %>% summarise_all(funs(med = median)) by_species %>% summarise_all(funs(Q3 = quantile), probs = 0.75) by_species %>% summarise_all(c("min", "max")) # Two functions, continued by_species %>% summarise_at(vars(Petal.Width, Sepal.Width), funs(min, max)) by_species %>% summarise_at(vars(matches("Width")), funs(min, max))