[R] "apply" a function that takes two or more vectors as arguments, such as cor(x, y), over a "category" or "grouping variable" or "index"?

[Kelly Thompson]

#Q. How can I "apply" a function that takes two or more vectors as
arguments, such as cor(x, y), over a "category" or "grouping variable"
or "index"?
#I'm using cor() as an example, I'd like to find a way to do this for
any function that takes 2 or more vectors as arguments.


#create example data

my_category <- rep ( c("a","b","c"),  4)

set.seed(12345)
my_x <- rnorm(12)

set.seed(54321)
my_y <- rnorm(12)

my_df <- data.frame(my_category, my_x, my_y)

#review data
my_df

#If i wanted to get the correlation of x and y grouped by category, I
could use this code and loop:

my_category_unique <- unique(my_category)

my_results <- vector("list", length(my_category_unique) )
names(my_results) <- my_category_unique

#start i loop
  for (i in 1:length(my_category_unique) ) {
    my_criteria_i <- my_category == my_category_unique[i]
    my_x_i <- my_x[which(my_criteria_i)]
    my_y_i <- my_y[which(my_criteria_i)]
    my_correl_i <- cor(x = my_x_i, y = my_y_i)
    my_results[i] <- list(my_correl_i)
} # end i loop

#review results
my_results

#Q. Is there a better or more "elegant" way to do this, using by(),
aggregate(), apply(), or some other function?

#This does not work and results in this error message: "Error in
FUN(dd[x, ], ...) : incompatible dimensions"
by (data = my_x, INDICES = my_category, FUN = cor, y = my_y)

#This does not work and results in this error message: "Error in
cor(my_df$x, my_df$y) : ... supply both 'x' and 'y' or a matrix-like
'x' "
by (data = my_df, INDICES = my_category, FUN = function(x, y) { cor
(my_df$x, my_df$y) } )


#if I wanted the mean of x by category, I could use by() or aggregate():
by (data = my_x, INDICES = my_category, FUN = mean)

aggregate(x = my_x, by = list(my_category), FUN = mean)

#Thanks!