A simple function that takes a dataframe and compares named columns to one another

apply.function.colwise

apply.function.colwise <- function(FUNC, x, x.columns = rownames(x), y.columns = colnames(x), ignore.diag = identical(x.columns, y.columns), ...) {

    checks <- c(is.numeric, is.character);

    # passing in a factor results in unexpected results, due to implicit numeric recasting
    stopifnot(
        any(sapply(checks, function(FUN) FUN(y.columns))),
        any(sapply(checks, function(FUN) FUN(x.columns)))
        );

    distance.matrix  <- matrix(
        NA,
        nrow = length(y.columns),
        ncol = length(x.columns),
        dimnames = list(y.columns, x.columns)
        );

    # could be smarter if function is known to be symmetric like most distance metrics, but will
    # leave as is in case ppl want to use inv() etc
    for(i in 1:nrow(distance.matrix)){
        for(j in 1:ncol(distance.matrix)){
            if(ignore.diag & i == j) next;
            distance.matrix[i, j] <- FUNC(
                x[,y.columns[i]],
                x[,x.columns[j]],
                ...
                );
            }
        }
    return(distance.matrix);
    }

Usage:

library(datasets)
apply.function.colwise(
  cor, 
  x = Seatbelts, 
  x.columns = colnames(Seatbelts), 
  y.columns = colnames(Seatbelts),
  method = sample(c("pearson", "spearman"),1) 
)