Arithmetic operations on R factors

Question

I have an R dataframe and I'm trying to subtract one column from another. I extract the columns using the $ operator but the class of the columns is 'factor' and R won't perform arithmetic operations on factors. Are there special functions to do this?

Answer 1

You should double check how you're pulling in the data first. If these are truly numeric columns R should recognize this (Excel messes up sometimes). Either way, it could be being coerced to a factor because there are other undesirables in the columns. The responses that you've received so far haven't mentioned that as.numeric() only returns the level numbers. Meaning that you won't be performing the operation on the actual numbers that have been converted to factors but rather the level numbers associated with each factor.

Answer 2

You can define your own operators to do that, see ? Arith. Without group generics, you can define your own binary operators %operator%:

%-% <- function (factor1, factor2){
  # put in the code here to calculate difference 
  # of two factors (e.g. facor1 level cat - factor2 level mouse = ?)
}

Answer 3

If you really want the levels of the factor to be used, you're either doing something very wrong or too clever for its own good.

If what you have is a factor containing numbers stored in the levels of the factor, then you want to coerce it to numeric first using as.numeric(as.character(...)):

dat <- data.frame(f=as.character(runif(10)))

You can see the difference between accessing the factor indices and assigning the factor contents here:

> as.numeric(dat$f)
 [1]  9  7  2  1  4  6  5  3 10  8
> as.numeric(as.character(dat$f))
 [1] 0.6369432 0.4455214 0.1204000 0.0336245 0.2731787 0.4219241 0.2910194
 [8] 0.1868443 0.9443593 0.5784658

Timings vs. an alternative approach which only does the conversion on the levels shows it's faster if levels are not unique to each element:

dat <- data.frame( f = sample(as.character(runif(10)),10^4,replace=TRUE) )
library(microbenchmark)
microbenchmark(
  as.numeric(as.character(dat$f)),
  as.numeric( levels(dat$f) )[dat$f] ,
  as.numeric( levels(dat$f)[dat$f] ),
  times=50
  )

                              expr     min      lq  median      uq     max
1  as.numeric(as.character(dat$f)) 7835865 7869228 7919699 7998399 9576694
2 as.numeric(levels(dat$f))[dat$f]  237814  242947  255778  270321  371263
3 as.numeric(levels(dat$f)[dat$f]) 7817045 7905156 7964610 8121583 9297819

Therefore, if length(levels(dat$f)) < length(dat$f), use as.numeric(levels(dat$f))[dat$f] for a substantial speed gain.

If length(levels(dat$f)) is approximately equal to length(dat$f), there is no speed gain:

dat <- data.frame( f = as.character(runif(10^4) ) )
library(microbenchmark)
microbenchmark(
  as.numeric(as.character(dat$f)),
  as.numeric( levels(dat$f) )[dat$f] ,
  as.numeric( levels(dat$f)[dat$f] ),
  times=50
  )

                              expr     min      lq  median      uq      max
1  as.numeric(as.character(dat$f)) 7986423 8036895 8101480 8202850 12522842
2 as.numeric(levels(dat$f))[dat$f] 7815335 7866661 7949640 8102764 15809456
3 as.numeric(levels(dat$f)[dat$f]) 7989845 8040316 8122012 8330312 10420161

Answer 4

You'll need to convert the factors to numeric arrays.

a <- factor(c(5,6,5))
b <- factor(c(3,2,1))
df <- data.frame(a, b)

# WRONG: Factors can't be subtracted.
df$a - df$b

# CORRECT: Get the levels and substract
as.numeric(levels(df$a)[df$a]) - as.numeric(levels(df$b)[df$b])