Argthtjtr

dat <- data.frame(s=c(1,1,1,1,2,2,2,2,3,3,3,3),               

                 c1=c("w","x","y","z","w","x","y","z","w","x","y","z"), 

                 c2=c("m","m","m","m","f","f","f","f","m","m","m","m"), 

                 c3=c(1,2,3,4,5,6,7,8,9,10,11,12))



> dat

       s c1 c2 c3

    1  1  w  m  1

    2  1  x  m  2

    3  1  y  m  3

    4  1  z  m  4

    5  2  w  f  5

    6  2  x  f  6

    7  2  y  f  7

    8  2  z  f  8

    9  3  w  m  9

    10 3  x  m 10

    11 3  y  m 11

    12 3  z  m 12

I'd like to calculate the difference between the c3 values for every combination of c1 (w-x, x-y, etc) and for every s. The output could look like this

s  diff  c2  c3

1  w-x   m   -1

1  w-y   m   -2

1  w-z   m   -3

1  x-y   m   -1

etc

I thought the aggregate function should work but I don't know how to define the combinations and pass them to the function argument.

If you are willing to use dplyr something like this should work.

dat <- data.frame(s=c(1,1,1,1,2,2,2,2,3,3,3,3), c1=c("w","x","y","z","w","x","y","z","w","x","y","z"), c2=c("m","m","m","m","f","f","f","f","m","m","m","m"), c3=c(1,2,3,4,5,6,7,8,9,10,11,12))



library(dplyr)

dat$c1 <- as.character(dat$c1)

dat2 <- dat %>%

  left_join(dat, by = c("s", "c2")) %>%

  filter(c1.x > c1.y) %>%

  transmute(s, diff = paste(c1.y, c1.x, sep = "-"), c2, c3 = c3.y - c3.x)



dat2



##    s diff c2 c3

## 1  1  w-x  m -1

## 2  1  w-y  m -2

## 3  1  x-y  m -1

## 4  1  w-z  m -3

## 5  1  x-z  m -2

## 6  1  y-z  m -1

## 7  2  w-x  f -1

## 8  2  w-y  f -2

## 9  2  x-y  f -1

## 10 2  w-z  f -3

## 11 2  x-z  f -2

## 12 2  y-z  f -1

## 13 3  w-x  m -1

## 14 3  w-y  m -2

## 15 3  x-y  m -1

## 16 3  w-z  m -3

## 17 3  x-z  m -2

## 18 3  y-z  m -1

do.call(rbind, lapply(split(dat, dat$s), function(a){

    a$c1 = as.character(a$c1)

    d = setNames(data.frame(t(combn(unique(a$c1), 2, FUN = function(x){

        list(x[1], x[2], a$c3[a$c1 == x[1]] - a$c3[a$c1 == x[2]])

    }))), c("col1", "col2", "val"))

    d$s = a$s[1]

    d$c2 = a$c2[1]

    d

}))

#    col1 col2 val s c2

#1.1    w    x  -1 1  m

#1.2    w    y  -2 1  m

#1.3    w    z  -3 1  m

#1.4    x    y  -1 1  m

#1.5    x    z  -2 1  m

#1.6    y    z  -1 1  m

#2.1    w    x  -1 2  f

#2.2    w    y  -2 2  f

#2.3    w    z  -3 2  f

#2.4    x    y  -1 2  f

#2.5    x    z  -2 2  f

#2.6    y    z  -1 2  f

#3.1    w    x  -1 3  m

#3.2    w    y  -2 3  m

#3.3    w    z  -3 3  m

#3.4    x    y  -1 3  m

#3.5    x    z  -2 3  m

#3.6    y    z  -1 3  m