Matrix Transformation in R - from aggregate output to outer-like matrix

Question

I need to transform the output of an aggregate (mean) into a matrix outer-like style.

data(mtcars)
aggregate(disp ~ cyl + gear, data = mtcars, FUN = mean )

  cyl gear     disp
  4    3 120.1000
  6    3 241.5000
  8    3 357.6167
  4    4 102.6250
  6    4 163.8000
  4    5 107.7000
  6    5 145.0000
  8    5 326.0000

What I need is to put the means of disp into a matrix with gear in columns and cyl in rows

Like this

    3   4   5
4 120 102 107
6 241 163 145
8 357 NA 326

Do you have any suggestion how I could do this transformation ?

Is there a way to use the function

outer 

?

structure(list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3, 
24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4, 
30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8, 
19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 
8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4), 
disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8, 
167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7, 
71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145, 
301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95, 
123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 
150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9, 
3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 
3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76, 
3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11
), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19, 
3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2, 
1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14, 
1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61, 
19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6, 
18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87, 
17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6
), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 
0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1, 
1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3, 
3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 
3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4, 
2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 
2, 2, 4, 6, 8, 2)), .Names = c("mpg", "cyl", "disp", "hp", 
"drat", "wt", "qsec", "vs", "am", "gear", "carb"), row.names = c("Mazda RX4", 
"Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout", 
"Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280", 
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood", 
"Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic", 
"Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin", 
"Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2", 
"Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora", 
"Volvo 142E"), class = "data.frame")

Answer 1

You can try tapply

with(mtcars, tapply(disp, list(cyl, gear), FUN=mean))
#       3       4     5
#4 120.1000 102.625 107.7
#6 241.5000 163.800 145.0
#8 357.6167      NA 326.0

If you are looking to reshape the output of aggregate, we can use acast from reshape2

d1 <- aggregate(disp ~ cyl + gear, data = mtcars, FUN = mean )
acast(d1, cyl~gear, value.var='disp')