vaggregate: Vector aggregate.

In plyr: Tools for Splitting, Applying and Combining Data

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 documentation built on Oct. 2, 2023, 9:07 a.m.