Normalize rows of a matrix within range 0 and 1

Question

I am trying to normalize all rows of my matrix data at once within range 0 and 1. But I don\'t know how to do it.. For example, I want to normalize each \"obs1\", \"obs2\",

Answer 1

To normalize for each row, you can use apply and then subtract the minimum from each column and divide by the difference between maximum and minimum:

t(apply(mydata, 1, function(x)(x-min(x))/(max(x)-min(x))))

gives you

              a         b         c         d         e
obs1 0.05553973 1.0000000 0.8889038 0.2777796 0.0000000
obs2 0.00000000 1.0000000 0.6805144 0.4848262 0.3945675
obs3 0.00000000 0.3289472 1.0000000 0.8605280 0.8736849

What happens is that you apply the function

function(x){
   (x-min(x))/(max(x)-min(x))
}

to each row of your data frame.

Answer 2

You could use the apply with rescale as the following:

apply(mydata, 1, rescale)

where the second argument 1 tells apply to work with rows.

The default range is [0, 1] but a custom range can be specified with the to argument that will be forwarded to the rescale function:

apply(mydata, 1, rescale, to=c(1,2))

Dependecy:

if(!require(scales)){
    install.packages("scales", dependencies=TRUE)
    library(scales)
}

Answer 3

for(i in 2:length(mydata[1,])){

    mydata[,i] <- prop.table(mydata[,i])

}

Normalized matrix will be updated in mydata