I'm trying to write a function that turns empty strings into NA. A summary of one of my column looks like this:
a b
12 210 468
I'd like to change the 12 empty values to NA. I also have a few other factor columns for which I'd like to change empty values to NA, so I borrowed some stuff from here and there to come up with this:
# change nulls to NAs
nullToNA <- function(df){
# split df into numeric & non-numeric functions
a<-df[,sapply(df, is.numeric), drop = FALSE]
b<-df[,sapply(df, Negate(is.numeric)), drop = FALSE]
# Change empty strings to NA
b<-b[lapply(b,function(x) levels(x) <- c(levels(x), NA) ),] # add NA level
b<-b[lapply(b,function(x) x[x=="",]<- NA),] # change Null to NA
# Put the columns back together
d<-cbind(a,b)
d[, names(df)]
}
However, I'm getting this error:
> foo<-nullToNA(bar) Error in x[x == "", ] <- NA : incorrect number of subscripts on matrix Called from: FUN(X[[i]], ...)
I have tried the answer found here: Replace all 0 values to NA but it changes all my columns to numeric values.
You can directly index fields that match a logical criterion. So you can just write:
df[is_empty(df)] = NA
Where is_empty
is your comparison, e.g. df == ""
:
df[df == ""] = NA
But note that is.null(df)
won’t work, and would be weird anyway1. I would advise against merging the logic for columns of different types, though! Instead, handle them separately.
1 You’ll almost never encounter NULL
inside a table since that only works if the underlying vector is a list
. You can create matrices and data.frames with this constraint, but then is.null(df)
will never be TRUE
because the NULL
values are wrapped inside the list).