How to collapse categories or recategorize variables?

Question

In R, I have 600,000 categorical variables, each of which is classified as "0", "1", or "2".

What I would like to do is collapse "1" and "2" and leave "0" by itself, such that after re-categorizing "0" = "0"; "1" = "1" and "2" = "1". In the end I only want "0" and "1" as categories for each of the variables.

Also, if possible, I would rather not create 600,000 new variables, if I can replace the existing variables with the new values that would be great!

What would be the best way to do this?

Answer 1

I find this is even more generic using factor(new.levels[x]):

> x <- factor(sample(c("0","1","2"), 10, replace=TRUE)) 
> x
 [1] 0 2 2 2 1 2 2 0 2 1
Levels: 0 1 2
> new.levels<-c(0,1,1)
> x <- factor(new.levels[x])
> x
 [1] 0 1 1 1 1 1 1 0 1 1
Levels: 0 1

The new levels vector must the same length as the number of levels in x, so you can do more complicated recodes as well using strings and NAs for example

x <- factor(c("old", "new", NA)[x])
> x
 [1] old    <NA>   <NA>   <NA>   new <NA>   <NA>   old   
 [9] <NA>   new    
Levels: new old

Answer 2

recode()'s a little overkill for this. Your case depends on how it's currently coded. Let's say your variable is x.

If it's numeric

x <- ifelse(x>1, 1, x)

if it's character

x <- ifelse(x=='2', '1', x)

if it's factor with levels 0,1,2

levels(x) <- c(0,1,1)

Any of those can be applied across a data frame dta to the variable x in place. For example...

 dta$x <- ifelse(dta$x > 1, 1, dta$x)

Or, multiple columns of a frame

 df[,c('col1','col2'] <- sapply(df[,c('col1','col2'], FUN = function(x) ifelse(x==0, x, 1))