How does one change the levels of a factor column in a data.table

Question

What is the correct way to change the levels of a factor column in a data.table (note: not data frame)

  library(data.table)   mydt <- data.table(id=1:6, value=as.factor(c("A", "A", "B", "B", "B", "C")), key="id")    mydt[, levels(value)]   [1] "A" "B" "C" 

I am looking for something like:

mydt[, levels(value) <- c("X", "Y", "Z")] 

But of course, the above line does not work.

    # Actual               # Expected result     > mydt                  > mydt        id value                id value     1:  1     A             1:  1     X     2:  2     A             2:  2     X     3:  3     B             3:  3     Y     4:  4     B             4:  4     Y     5:  5     B             5:  5     Y     6:  6     C             6:  6     Z 

Answer 1

You can still set them the traditional way:

levels(mydt$value) <- c(...) 

This should be plenty fast unless mydt is very large since that traditional syntax copies the entire object. You could also play the un-factoring and refactoring game... but no one likes that game anyway.

To change the levels by reference with no copy of mydt :

setattr(mydt$value,"levels",c(...)) 

but be sure to assign a valid levels vector (type character of sufficient length) otherwise you'll end up with an invalid factor (levels<- does some checking as well as copying).

Answer 2

I would rather go the traditional way of re-assignment to the factors

> mydt$value # This we what we had originally [1] A A B B B C Levels: A B C > levels(mydt$value) # just checking the levels [1] "A" "B" "C" **# Meat of the re-assignment** > levels(mydt$value)[levels(mydt$value)=="A"] <- "X" > levels(mydt$value)[levels(mydt$value)=="B"] <- "Y" > levels(mydt$value)[levels(mydt$value)=="C"] <- "Z" > levels(mydt$value) [1] "X" "Y" "Z" > mydt # This is what we wanted    id value 1:  1     X 2:  2     X 3:  3     Y 4:  4     Y 5:  5     Y 6:  6     Z 

As you probably notices, the meat of the re-assignment is very intuitive, it checks for the exact level(use grepl in case there's a fuzzy math, regular expressions or likewise)

levels(mydt$value)[levels(mydt$value)=="A"] <- "X" This explicitly checks the value in the levels of the variable under consideration and then reassigns X (and so on) to it - The advantage- you explicitly KNOW what labeled what.

I find renaming levels as here levels(mydt$value) <- c("X","Y","Z") very non-intuitive, since it just assigns X to the 1st level it SEES in the data (so the order really matters)

PPS : In case of too many levels, use looping constructs.