How to use the 'sweep' function

sweep() is typically used when you operate a matrix by row or by column, and the other input of the operation is a different value for each row / column. Whether you operate by row or column is defined by MARGIN, as for apply(). The values used for what I called "the other input" is defined by STATS. So, for each row (or column), you will take a value from STATS and use in the operation defined by FUN.

For instance, if you want to add 1 to the 1st row, 2 to the 2nd, etc. of the matrix you defined, you will do:

sweep (M, 1, c(1: 4), "+")

I frankly did not understand the definition in the R documentation either, I just learned by looking up examples.

sweep() can be great for systematically manipulating a large matrix either column by column, or row by row, as shown below:

> print(size)     Weight Waist Height[1,]    130    26    140[2,]    110    24    155[3,]    118    25    142[4,]    112    25    175[5,]    128    26    170> sweep(size, 2, c(10, 20, 30), "+")     Weight Waist Height[1,]    140    46    170[2,]    120    44    185[3,]    128    45    172[4,]    122    45    205[5,]    138    46    200

Granted, this example is simple, but changing the STATS and FUN argument, other manipulations are possible.

This question is a bit old, but since I've recently faced this problem a typical use of sweep can be found in the source code for the stats function cov.wt, used for computing weighted covariance matrices. I'm looking at the code in R 3.0.1. Here sweep is used to subtract out column means before computing the covariance. On line 19 of the code the centering vector is derived:

 center <- if (center)         colSums(wt * x)    else 0

and on line 54 it is swept out of the matrix

x <- sqrt(wt) * sweep(x, 2, center, check.margin = FALSE)

The author of the code is using the default value FUN = "-", which confused me for a while.