Question

Let’s say I have rows like this:

    First, Last, Address, Address 2, Email, Custom1, Custom2, Custom3
1    A, B, C, D, [e-mail],1,2,3
2    A,  , C, D, [e-mail],1,2,
3     ,  ,  ,  , [e-mail],1, ,  

What I would like to to do is create a function that pulls that row which is most complete and I’m wondering if there are any packages or pre-existing methods (recommendations, even) for doing this. In the example above, I would like to to have a function that chooses row 1.

I can’t use complete.cases() or na.omit() because in many circumstances the cases are not complete and contain at least one NA. I’ve tried combining unique() with a number of specific pulls… but I’m not having much luck automating this manipulation task.

Answer 1

You can convert to character and the count row-wise how many non-emptys you have:

R> Lines <- "
+ First, Last, Address, Address 2, Email, Custom1, Custom2, Custom3
+  A, B, C, D, [e-mail],1,2,3
+  A,  , C, D, [e-mail],1,2,
+   ,  ,  ,  , [e-mail],1, ,
+ "
R> 
R> con <- textConnection(Lines)
R> df <- read.table(con, header=TRUE, sep=",")
R> close(con)
R> 
R> m <- as.matrix(df)  # now all char
R> 
R> counts <- apply(m, 1, function(r) { r <- gsub("^ $", "", r); 
+                                      sum(na.omit(r) != "") } )
R> 
R> df[which.max(counts), ]   # pick row of maximum
  First Last Address Address.2    Email Custom1 Custom2 Custom3
1     A    B       C         D  [e-mail]       1       2       3
R>