plyr: vaggregate – R documentation

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vaggregate

Vector aggregate.

Description

This function is somewhat similar to tapply, but is designed for use in conjunction with id. It is simpler in that it only accepts a single grouping vector (use id if you have more) and uses vapply internally, using the .default value as the template.

Usage

vaggregate(.value, .group, .fun, ..., .default = NULL, .n = nlevels(.group))

Arguments

`.value`	vector of values to aggregate
`.group`	grouping vector
`.fun`	aggregation function
`...`	other arguments passed on to `.fun`
`.default`	default value used for missing groups. This argument is also used as the template for function output.
`.n`	total number of groups

Details

vaggregate should be faster than tapply in most situations because it avoids making a copy of the data.

Examples

# Some examples of use borrowed from ?tapply
n <- 17; fac <- factor(rep(1:3, length.out = n), levels = 1:5)
table(fac)
vaggregate(1:n, fac, sum)
vaggregate(1:n, fac, sum, .default = NA_integer_)
vaggregate(1:n, fac, range)
vaggregate(1:n, fac, range, .default = c(NA, NA) + 0)
vaggregate(1:n, fac, quantile)
# Unlike tapply, vaggregate does not support multi-d output:
tapply(warpbreaks$breaks, warpbreaks[,-1], sum)
vaggregate(warpbreaks$breaks, id(warpbreaks[,-1]), sum)

# But it is about 10x faster
x <- rnorm(1e6)
y1 <- sample.int(10, 1e6, replace = TRUE)
system.time(tapply(x, y1, mean))
system.time(vaggregate(x, y1, mean))

plyr

Tools for Splitting, Applying and Combining Data

v1.8.6

MIT + file LICENSE

Authors

Hadley Wickham [aut, cre]

Initial release