loop functions
lapply(list,function)
example:
x <- list(a = 1:5, b = rnorm(10))
lapply(x, mean)
x <- list(a = 1:4, b = rnorm(10), c = rnorm(20, 1), d = rnorm(100, 5))
lapply(x, mean)
x <- 1:4
lapply(x, runif)
x <- list(a = matrix(1:4, 2, 2), b = matrix(1:6, 3, 2))
lapply(x, function(elt) { elt[,1] })
sapply(list,function)
The sapply() function behaves similarly to lapply()
- If the result is a list where every element is length 1, then a vector is returned
- If the result is a list where every element is a vector of the same length (> 1), a matrix is returned.
- If it can’t figure things out, a list is returned
tapply(vector,INDEX,function)
- INDEX is a factor or a list of factors (or else they are coerced to factors)
example:
x <- c(rnorm(10), runif(10), rnorm(10, 1))
f <- gl(3, 10)
tapply(x, f, mean)
apply(array,dims,function)
example:
x <- matrix(rnorm(200), 20, 10)
apply(x, 2, mean) ## Take the mean of each column
apply(x, 1, sum) ## Take the mean of each row
x <- matrix(rnorm(200), 20, 10)
apply(x, 1, quantile, probs = c(0.25, 0.75))
a <- array(rnorm(2 * 2 * 10), c(2, 2, 10))
apply(a, c(1, 2), mean)
Col/RowSumsandMeans
rowSums = apply(x, 1, sum)
rowMeans = apply(x, 1, mean)
colSums = apply(x, 2, sum)
colMeans = apply(x, 2, mean)
mapply(function,argument1,argument2,argument3...)
example:
mapply(rep, 1:4, 4:1)
## "1:4" is the first argument of function "rep"
## "4:1" is the second argument of function "rep"
noise <- function(n, mean, sd) { rnorm(n, mean, sd) }
mapply(noise, 1:5, 1:5, 2)
## "1:5" is the first argument of function "noise"
## "1:5" is the second argument of function "noise"
## "2" is the third argument of function "noise"
split(vector or list or data frame,factor)
The split() function takes a vector or other objects and split sitin to groups determined by a factor or list of factors.
example:
x <- c(rnorm(10), runif(10), rnorm(10, 1))
f <- gl(3, 10)
split(x, f)
lapply(split(x, f), mean)
library(datasets)
head(airquality)
s <- split(airquality, airquality$Month)
lapply(s, function(x) { colMeans(x[, c("Ozone", "Solar.R", "Wind")]) })
sapply(s, function(x) { colMeans(x[, c("Ozone", "Solar.R", "Wind")], na.rm = TRUE)
x <- rnorm(10)
f1 <- gl(2, 5)
f2 <- gl(5, 2)
interaction(f1, f2)
str(split(x, list(f1, f2)))
str(split(x, list(f1, f2), drop = TRUE))