Merging rows with shared information

Question

I have a data.frame with several rows which come from a merge which are not completely merged:

b <- read.table(text = \"
      ID   Age    Steatosis               


        

Answer 1

Here is a base R method that should work, for a version of the data that you provided:

aggregate(b[-grep("^(ID|Age)$", names(b))], b[c("ID", "Age")], 
          FUN=function(x) if(all(is.na(x))) NA else x[!is.na(x)][1])

   ID Age Steatosis       Mallory Lille_dico Lille_3  Bili.AHHS2cat
 1 HA-09  16      <33% no/occasional         NA       5  1          

It uses aggregate together with an if else check. This will return the first element that is not missing if any should exist. I take the first element as there is at least one observation. The i in the code could be replaced by length(x) to select the last element.

As suggested by @jdobres in a comment to another answer, it would be possible to use paste with the collapse argument to combine multiple non-missing elements. This, of course would convert the type of the vector to character, which may not be desirable if the variable is numeric.

Note: I edited my original answer to include "Age" in the key, thanks to @sebastian-c for pointing this out.

---

If "Age" is not part of the key, then

aggregate(b[-grep("^(ID)$", names(b))], b["ID"], 
          FUN=function(x) if(all(is.na(x))) NA else x[!is.na(x)][1])

will work.

data

b <- read.table(text = "
      ID   Age    Steatosis       Mallory Lille_dico Lille_3 Bili.AHHS2cat
68 HA-09   16   NA          NA       NA       5             NA
69 HA-09   16   <33% no/occasional     NA      NA             1")