『Data Science』R语言学习笔记，基础语法

apply is used to a evaluate a function (often an anonymous one) over the margins of an array.

• It is most often used to apply a function to the rows or columns of a matrix.
• It can be used with general arrays,e.g. taking the average of an array of matrices.
• It is not really faster than writing a loop,but it works in one line!

> str(apply)
function (X,MARGIN,...)

• x is an array
• MARGIN is an integer vector indicating which margins should be "retained"
• FUN is a function to be applied.
• ... is for other arguments to be passed to FUN

> x <- matrix(1:4,2)
> x
     [,2]
[1,]    1    3
[2,]    2    4
> apply(x,mean)
[1] 2 3
> apply(x,mean)
[1] 1.5 3.5

• MARGIN = 1 Compute the mean at every row,and return a vector as result.
• MARGIN = 1 Compute the mean at every column,and return a vector as result.

Other shortcuts.

• rowSums = apply(x,sum)
• rowMeans = apply(x,mean)
• colSums = apply(x,sum)
• colMeans = apply(x,mean)

Apply in multiple dimensions array,in the source below,we use a vector as a MARGIN value to complete the compute of multiple dimensions compute.

> a <- array(rnorm(2 * 2 * 10),c(2,10))
> apply(a,c(1,mean)
           [,1]        [,]  0.6869065 -0.66529430
[2,] -0.1136978 -0.04124547

mapply

mapply is a multivariate apply of sorts which applies a function in parallel over a set of arguments.

> str(mapply)
function (FUN,...,MoreArgs = NULL,SIMPLIFY = TRUE,USE.NAMES = TRUE)

• FUN is a function to apply.
• ... contains arguments to apply over.
• MoreArgs is a list of other arguments to FUN.
• SIMPLIFY indicates whether the result should be simplified.

tapply

tapply is used to apply a function over subsets of a vector.

split

split divides the data in the vector x into the groups defined by f. The replacement forms replace values corresponding to such a division. unsplit reverses the effect of split.

> s <- split(airquality,airquality$Month)
> sapply(s,function(x) colMeans(x[,c("Ozone","Wind")]))
             5        6        7        8     9
Ozone       NA       NA       NA       NA    NA
Wind  11.62258 10.26667 8.941935 8.793548 10.18

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