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

What is the correct way to change the levels of afactorcolumn in adata.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

You can still set them the traditional way:

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

This should be plenty fast unlessmydtis 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 ofmydt:

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

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

You can also rename and add to your levels using a related approach, which can be very handy, especially if you are making a plot that needs more informative labels in a particular order (as opposed to the default):

f <- factor(c("a","b"))
levels(f) <- list(C = "C", D = "a", B = "b")

(modified from?levels)

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, themeat of the re-assignmentis 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 herelevels(mydt$value) <- c("X","Y","Z")verynon-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.

Simplest way to change a column's levels:

dat$colname <- as.factor(as.vector(dat$colname));

Tags: data.table
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