summarise_each

0th

Percentile

Summarise and mutate multiple columns.

Apply one or more functions to one or more columns. Grouping variables are always excluded from modification.

Usage
summarise_each(tbl, funs, ...)

summarise_each_(tbl, funs, vars)

mutate_each(tbl, funs, ...)

mutate_each_(tbl, funs, vars)

Arguments
tbl
a tbl
funs
List of function calls, generated by funs, or a character vector of function names.
vars,...
Variables to include/exclude in mutate/summarise. You can use same specifications as in select. If missing, defaults to all non-grouping variables.

For standard evaluation versions (ending in _q) these can be either a list of expressions or a character vector.

Aliases
  • mutate_each
  • mutate_each_
  • mutate_each_q
  • summarise_each
  • summarise_each_
  • summarise_each_q
Examples
# One function
by_species <- iris %>% group_by(Species)
by_species %>% summarise_each(funs(length))
by_species %>% summarise_each(funs(mean))
by_species %>% summarise_each(funs(mean), Petal.Width)
by_species %>% summarise_each(funs(mean), matches("Width"))

by_species %>% mutate_each(funs(half = . / 2))
by_species %>% mutate_each(funs(min_rank))

# Two functions
by_species %>% summarise_each(funs(min, max))
by_species %>% summarise_each(funs(min, max), Petal.Width, Sepal.Width)
by_species %>% summarise_each(funs(min, max), matches("Width"))

# Alternative function specification
iris %>% summarise_each(funs(ul = length(unique(.))))
by_species %>% summarise_each(funs(ul = length(unique(.))))

by_species %>% summarise_each(c("min", "max"))

# Alternative variable specification
summarise_each_(iris, funs(max), names(iris)[-5])
summarise_each_(iris, funs(max), list(quote(-Species)))
Documentation reproduced from package dplyr, version 0.3, License: MIT + file LICENSE

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