
Hello all,
 
I'm new to R and trying to figure out how to perform calculations on a large dataset (300 000 datapoints). I have already made some code to do this but it is awfully slow. What I want to do is add a new column for each "rep_ " column where I have taken each value and divide it by the mean of all values where "PlateNo" is the same. My data is in the following format: 
 
> data 




PlateNo

Well

rep_1

rep_2

rep_3


1

A01

1312

963

1172


1

A02

10464

6715

5628


1

A03

3301

3257

3281


1

A04

3895

3350

3496


1

A05

8731

7389

5701


2

A01

7893

6748

5920


2

A02

2912

2385

2586


2

A03

985

785

809


2

A04

1346

1018

1001


2

A05

794

314

486
 
To generate it copy: 
a <- c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2)
b <- c("A01", "A02", "A03", "A04", "A05", "A01", "A02", "A03", "A04", "A05")
c <- c(1312, 10464,  3301,  3895,  8731,  7893,  2912,   985,  1346,   794)
d <- c(963, 6715, 3257, 3350, 7389, 6748, 2385, 785, 1018,  314)
e <- c(1172, 5628, 3281, 3496, 5701, 5920, 2586,  809, 1001,  486)
data <- data.frame(plateNo = a, Well = b, rep_1 = c, rep_2 = d, rep_3 = e)
 
Here is the code I have come up with:
 
                rows <- length(data$plateNo)
                reps <- 3
                norm <- list()
                for (rep in 1:reps) {
                                x <- paste("rep_",rep,sep="")   
                                normx <- paste("normalised_",rep,sep="")
                                for (row in 1:rows) {
                                                plateMean <- mean(data[[x]][data$plateNo == data$plateNo[row]])
                                                wellData <- data[[x]][row]
                                                norm[[normx]][row] <- wellData / plateMean
                                }
                }
 
 
Any help or tips would be greatly appreciated!
Thanks, 
Haakon   		 	   		  
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