Remove variable labels attached with foreign/Hmisc SPSS import functions

Question

As usual, I got some SPSS file that I've imported into R with spss.get function from Hmisc package. I'm bothered with labelled class that Hmisc::spss.get adds to all variables in data.frame, hence want to remove it.

labelled class gives me headaches when I try to run ggplot or even when I want to do some menial analysis! One solution would be to remove labelled class from each variable in data.frame. How can I do that? Is that possible at all? If not, what are my other options?

I really want to bypass reediting variables "from scratch" with as.data.frame(lapply(x, as.numeric)) and as.character where applicable... And I certainly don't want to run SPSS and remove labels manually (don't like SPSS, nor care to install it)!

Thanks!

Answer 1

Here's how I get rid of the labels altogether. Similar to Jyotirmoy's solution but works for a vector as well as a data.frame. (Partial credits to Frank Harrell)

clear.labels <- function(x) {
  if(is.list(x)) {
    for(i in 1 : length(x)) class(x[[i]]) <- setdiff(class(x[[i]]), 'labelled') 
    for(i in 1 : length(x)) attr(x[[i]],"label") <- NULL
  }
  else {
    class(x) <- setdiff(class(x), "labelled")
    attr(x, "label") <- NULL
  }
  return(x)
}

Use as follows:

my.unlabelled.df <- clear.labels(my.labelled.df)

EDIT

Here's a bit of a cleaner version of the function, same results:

clear.labels <- function(x) {
  if(is.list(x)) {
    for(i in seq_along(x)) {
      class(x[[i]]) <- setdiff(class(x[[i]]), 'labelled') 
      attr(x[[i]],"label") <- NULL
    } 
  } else {
    class(x) <- setdiff(class(x), "labelled")
    attr(x, "label") <- NULL
  }
  return(x)
}

Answer 2

A belated note/warning regarding class membership in R objects. The correct method for identification of "labelled" is not to test for with an is function or equality {==) but rather with inherits. Methods that test for a specific location will not pick up cases where the order of existing classes are not the ones assumed.

You can avoid creating "labelled" variables in spss.get with the argument: , use.value.labels=FALSE.

w <- spss.get('/tmp/my.sav', use.value.labels=FALSE, datevars=c('birthdate','deathdate'))

The code from Bhattacharya could fail if the class of the labelled vector were simply "labelled" rather than c("labelled", "factor") in which case it should have been:

class(x[[i]]) <- NULL  # no error from assignment of empty vector

The error you report can be reproduced with this code:

> b <- 4:6
> label(b) <- 'B Label'
> str(b)
Class 'labelled'  atomic [1:3] 4 5 6
  ..- attr(*, "label")= chr "B Label"
> class(b) <- class(b)[-1]
Error in class(b) <- class(b)[-1] : 
  invalid replacement object to be a class string

Answer 3

You can try out the read.spss function from the foreign package.

A rough and ready way to get rid of the labelled class created by spss.get

for (i in 1:ncol(x)) {
    z<-class(x[[i]])
    if (z[[1]]=='labelled'){
       class(x[[i]])<-z[-1]
       attr(x[[i]],'label')<-NULL
    }
}

But can you please give an example where labelled causes problems?

If I have a variable MAED in a data frame x created by spss.get, I have:

> class(x$MAED)
[1] "labelled" "factor"  
> is.factor(x$MAED)
[1] TRUE

So well-written code that expects a factor (say) should not have any problems.