r - Looking for a more concise way to recategorise a variable -

i have vector of integer ages want turn multiple categories:

ages <- round(runif(10, 0, 99)) 

now want variable binned 3 categories, depending on age. want output object, ages.cat this:

   young mid old 1      0   0   1 2      1   0   0 3      1   0   0 4      1   0   0 5      1   0   0 6      0   1   0 7      1   0   0 8      0   0   1 9      0   1   0 10     0   1   0 

at present creating object following code:

ages.cat <- array(0, dim=c(10,3)) # create categorical object 3 bins ages.cat[ages < 30, 1] <- 1 ages.cat[ages >= 30 & ages < 60, 2] <- 1 ages.cat[ages >= 60, 3] <- 1  ages.cat <- data.frame(ages.cat) names(ages.cat) <- c("young", "mid", "old") 

there must faster , more concise way recode data - had play dplyr couldn't see solution particular problem functions. ideas? what's 'canonical' solution problem in base r or using package? whatever alternatives, i'm they'll more concise clunky code!

its 2 one-liners.

use cut create factor:

ages <- round(runif(10, 0, 99)) agef=cut(ages,c(-inf,30,60,inf),labels=c("young","mid","old")) > agef  [1] young mid   young young old   mid   old   young old   old   levels: young mid old 

usually you'd leave factor , work it, if using r's modelling functions they'll work out matrix you. if doing yourself:

use model.matrix create matrix, -1 remove intercept , create columns each level:

> m = model.matrix(~agef-1) > m    agefyoung agefmid agefold 1          1       0       0 2          0       1       0 3          1       0       0 4          1       0       0 5          0       0       1 6          0       1       0 7          0       0       1 8          1       0       0 9          0       0       1 10         0       0       1 attr(,"assign") [1] 1 1 1 attr(,"contrasts") attr(,"contrasts")$agef [1] "contr.treatment" 

you can ignore contrasty stuff @ end, matrix attributes modelling.