I am still not sure, I understand you correctly.
set.seed(1)
X <- data.frame(matrix(rnorm(20), nrow=10))
Y <- data.frame(matrix(rnorm(20), nrow=10))
#CV
d1 <- density(sapply(X, function(x) sd(x)/mean(x)))
d2 <- density(sapply(Y, function(x) sd(x)/mean(x)))
plot(d1, ylim=c(0,max(d1$y,d2$y)), xlim=range(d1$x,d2$x), col="green", xlab="", main="")
par(new=TRUE)
plot(d2, ylim=c(0,max(d1$y,d2$y)), xlim=range(d1$x,d2$x), col="red", xlab="", main="")
par(new=FALSE)
#covariance
d3 <- density(cov(X))
d4 <- density(cov(Y))
plot(d3, ylim=c(0,max(d3$y,d4$y)), xlim=range(d3$x,d4$x), col="green", xlab="", main="")
par(new=TRUE)
plot(d4, ylim=c(0,max(d3$y,d4$y)), xlim=range(d3$x,d4$x), col="red", xlab="", main="")
par(new=FALSE)