I have an array for which I would like to obtain a measure of the similarity between values in each column. By which I mean I wish to compare the rows between pairwise columns of the array and increment a measure when their values match. The resulting measure would then be at a maximum for two columns exactly the same.
Essentially my problem is the same as discussed here: R: Compare all the columns pairwise in matrix except that I do not wish empty cells to be counted.
With the example data created from code derived from the linked page:
data1 <- c("", "B", "", "", "")
data2 <- c("A", "", "", "", "")
data3 <- c("", "", "C", "", "A")
data4 <- c("", "", "", "", "")
data5 <- c("", "", "C", "", "A")
data6 <- c("", "B", "C", "", "")
my.matrix <- cbind(data1, data2, data3, data4, data5, data6)
similarity.matrix <- matrix(nrow=ncol(my.matrix), ncol=ncol(my.matrix))
for(col in 1:ncol(my.matrix)){
matches <- my.matrix[,col] == my.matrix
match.counts <- colSums(matches)
match.counts[col] <- 0
similarity.matrix[,col] <- match.counts
}
I obtain:
similarity.matrix =
V1 V2 V3 V4 V5 V6
1 0 3 2 4 2 4
2 3 0 2 4 2 2
3 2 2 0 3 5 3
4 4 4 3 0 3 3
5 2 2 5 3 0 3
6 4 2 3 3 3 0
which counts non-value pairs.
My desired output would be:
expected.output =
V1 V2 V3 V4 V5 V6
1 0 0 0 0 0 1
2 0 0 0 0 0 0
3 0 0 0 0 2 1
4 0 0 0 0 0 0
5 0 0 2 0 0 1
6 1 0 1 0 1 0
Thanks,
Matt
So the following is the answer from akrun :
first changing the blank cells to NA's
and then removing the NA's for the
match.counts
Which did indeed give me my desired output:
thank you.