Question

I am sure the answer to this is up somewhere, but I don’t think I’ve been using the right search terms.

Here is my issue. I have multiple matrices (I will simplify to just two here), where each row is a uniquely labeled individual (some of which are shared between matrices, and some of which are not), and common column headings that are shared.

For example:

first<-matrix(rbinom(20,1,.5),4,5)
first[,1]=c(122,145,186,199)
colnames(first)<-c("ID",901,902,903,904)
first
      ID 901 902 903 904
[1,] 122   1   0   0   0
[2,] 145   0   0   0   1
[3,] 186   0   0   1   1
[4,] 199   1   0   0   0

second<-matrix(rbinom(30,1,.5),6,5)
second[,1]=c(122,133,142,151,186,199)
colnames(second)<-c("ID",901,902,903,904)
second
      ID 901 902 903 904
[1,] 122   0   1   1   1
[2,] 133   0   0   0   1
[3,] 142   1   1   0   1
[4,] 151   0   1   0   0
[5,] 186   1   0   1   1
[6,] 199   1   0   0   0

I would like to add ‘first’ and ‘second’ together based upon the ‘ID’ and column names. This should result in a matrix with 7 rows (since there are 4 IDs in the ‘first’ matrix, and 3 new and 3 old IDs in the ‘second’ matrix: “122,133,142,145,151,186,199”), and the same number of columns.

In this example, the result I would want would be:

      ID 901 902 903 904
[1,] 122   1   1   1   1
[2,] 133   0   0   0   1
[3,] 142   1   1   0   1
[4,] 145   0   0   0   1
[5,] 151   0   1   0   0
[6,] 186   1   0   2   2
[7,] 199   2   0   0   0

Answer 1

I was looking for a solution without a “for” loop using builtin functions without success.
So here is my approach

set.seed(1) # make it reproducible
first <- matrix(rbinom(20,1,.5),4,5)
first[ ,1] <- c(122, 145, 186, 199)
colnames(first) <- c("ID", 901, 902, 903, 904)

second <- matrix(rbinom(30, 1, .5), 6, 5)
second[ ,1] <- c(122, 133, 142, 151, 186, 199)
colnames(second) <- c("ID", 901, 902, 903, 904)

first

      ID 901 902 903 904
[1,] 122   0   1   1   1
[2,] 145   1   0   0   1
[3,] 186   1   0   1   0
[4,] 199   1   0   0   1

second
      ID 901 902 903 904
[1,] 122   0   0   1   1
[2,] 133   0   0   0   1
[3,] 142   1   1   1   0
[4,] 151   0   1   1   0
[5,] 186   0   1   1   1
[6,] 199   1   0   1   1

## stack them rowise
mat <- rbind(first, second)

ind <- unique(mat[,"ID"])

result <- matrix(nrow = length(ind), ncol = 5)
result[,1] <- ind

for (i in seq_along(ind)) {
    result[i,-1] <- colSums(mat[mat[ ,"ID"] == ind[i], -1, drop = FALSE])
}
colnames(result) <- colnames(mat)

result
      ID 901 902 903 904
[1,] 122   0   1   2   2
[2,] 145   1   0   0   1
[3,] 186   1   1   2   1
[4,] 199   2   0   1   2
[5,] 133   0   0   0   1
[6,] 142   1   1   1   0
[7,] 151   0   1   1   0