To find the row-wise correlation of two matrices X and Y, the output should have a correlation value for row 1 of X and row 1 of Y, ..., hence in total ten values (because there are ten rows):
X <- matrix(rnorm(2000), nrow=10)
Y <- matrix(rnorm(2000), nrow=10)
sapply(1:10, function(row) cor(X[row,], Y[row,]))
Now, how should I apply this function to two lists (containing around 50 dataframes each)?
Consider list A has dataframes $1, $2, $3... and so on and list B has similar number of dataframes $1, $2, $3. So the function should be applied to listA$1,listB$1
and listA$2,listB$2
... and so on for other dataframes in the list. In the end I will have ten values in case of comparison 1 (listA$1
and listB$1
) and for others as well.
Could this be done using "lapply"?
You seem to be looking for mapply
. Here's an example:
listA <- list(matrix(rnorm(2000), nrow=10),
matrix(rnorm(2000), nrow=10))
listB <- list(matrix(rnorm(2000), nrow=10),
matrix(rnorm(2000), nrow=10))
mapply(function(X,Y) {
sapply(1:10, function(row) cor(X[row,], Y[row,]))
}, X=listA, Y=listB)