I have a data.frame that is made up several hundreds factors. These factors have two wierd levels: "" and "true".
I must quite simply transform the levels into "0" and "1".
Problem is, I am unable to do it. I tried several solutions existing on stackoverflow, e.g. here but I am unable to do it.
The data is here
If I simply change the factor levels on the individual variables it works (of course)
export <- read.csv("factordata.csv")
str(export)
'data.frame': 16 obs. of 124 variables:
$ caddy1_prod_detail_2456 : Factor w/ 2 levels "","true": 2 1 1 1 1 1 1 1 1 1 ...
str(export$caddy1_prod_detail_2456)
#Factor w/ 2 levels "","true": 2 1 1 1 1 1 1 1 1 1 ...
levels(export$caddy1_prod_detail_2456)<-c(0,1)
str(export$caddy1_prod_detail_2456)
#Factor w/ 2 levels "0","1": 2 1 1 1 1 1 1 1 1 1 ...
But if I try to use a for loop, as here
for (var in export ) {
levels(var)<-c("0","1")
}
simply nothing happens to the data; if instead I try the solution proposed in the other question, as in here
export[] <- lapply(export, function(x){
levels(x) <- c(0,1)
})
it transforms my factors in numeric and destroys existing data converting the variables to lists of 0 and 1.
str(export)
'data.frame': 16 obs. of 124 variables:
$ caddy1_prod_detail_2456 : num 0 1 0 1 0 1 0 1 0 1 ...
$ caddy1_prod_detail_2456_ingredients: num 0 1 0 1 0 1 0 1 0 1 ...
What am I doing wrong? Cannot be that difficult!
