I received an email from one of my students expressing deep frustration with a seemingly simple problem. He had a factor containing names of potato lines and wanted to set some levels to
NA. Using simple letters as example names he was baffled by the result of the following code:
lines <- factor(LETTERS) lines #  A B C D E F G H... # Levels: A B C D E F G H... linesNA <- ifelse(lines %in% c('C', 'G', 'P'), NA, lines) linesNA #  1 2 NA 4 5 6 NA 8...
The factor has been converted to numeric and there was no trace of the level names. Even forcing the conversion to be a factor loses the level names. Newbie frustration guaranteed!
linesNA <- factor(ifelse(lines %in% c('C', 'G', 'P'), NA, lines)) linesNA #  1 2
4 5 6 8... # Levels: 1 2 4 5 6 8...
Under the hood factors are numerical vectors (of class factor) that have associated character vectors to describe the levels (see Patrick Burns's R Inferno PDF for details). We can deal directly with the levels using this:
linesNA <- lines levels(linesNA)[levels(linesNA) %in% c('C', 'G', 'P')] <- NA linesNA #  A B
D E F H... #Levels: A B D E F H...
We could operate directly on lines (without creating linesNA), which is there to maintain consistency with the previous code. Another way of doing the same would be:
linesNA <- factor(as.character(ifelse(lines %in% c('C', 'G', 'P'), NA, lines))) linesNA #  A B
D E F H... #Levels: A B D E F H...
I can believe that there are good reasons for the default behavior of operations on factors, but the results can drive people crazy (at least rhetorically speaking).
0 responses to “R pitfall #3: friggin’ factors”
Maybe this is more intuitive (also it is not really different to your approach):
lines <- factor(LETTERS)
linesNA <- lines
levels(linesNA) <- ifelse(levels(linesNA) %in% c('C', 'G', 'P'), NA, levels(lines))
You can do:
lines[lines %in% c('C', 'G', 'P')] <- NA
My latest complaint about factors is this:
 a b c d e f g h i j
Levels: a b c d e f g h i j
 1 1 1 1 1 1 1 1 1 2
Wow! R is counting the number of characters of the internal numeric representation of levels. Devious and nightmarish to debug! I share your pain.
Several stumbling blocks with factors are shown at the beginning of Circle 8.2 of 'The R Inferno' http://www.burns-stat.com/pages/Tutor/R_inferno.p…
Thanks for pointing out the exact location. I like very much your writing in the Inferno!
You know, I have a embarrasing pitfall with the simple function "save". I can't save an R object in a file, because it saves a character string of the object instead of the contents of the object! Then I tried saving the whole session, and it saves a vector of all the objects' names. :facepalm:
The sad thing is I had'nt solve it yet.
P.D. In moments like this is when I wish to have formal training in R programming.
It should be straightforward; for example:
a = c('a', 'b', 'c')
save(a, file = 'whatever.Rdata')
However, if you put the object name between quotes—save('a', file = 'whatever.Rdata')—you will get the name, which is not what you want. I hope this helps, Luis.
Thanks to Rbloggers I solved this "easy" task. The problem is that I did something like this:
> x.var <- rnorm(100)
> save(x.var, file="foo")
> something <- load("foo")
My fail was to assign to a variable that is not needed, with the line load("foo") is enough. My line of thought was: "Is good to save my models, temporary data and other stuff inside variables, so you can interact with that stuff later, in that case, let's load the R-object and let's put it inside a variable!"
Maybe I had a weird line of thought…
Seems that most of the issue here is the idea that factors are both a numeric list, and a set of accompanying labels. This is a powerful representation, but needs to be taken into account when dealing with the factor structure.
So, when you want the character count of the labels, you have to tell R it is the labels you are thinking about…
I manually posted your comment. It seems that it was trapped in the system just while I was doing the transition between Intense Debate and WordPress’s default system and ended up nowhere to be seen.