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

A dplyr approach using summarise_all:

## using `na.strings` to identify NA entries in posted data
b <- read.table(text = "
      ID   Age    Steatosis       Mallory Lille_dico Lille_3 Bili.AHHS2cat
68 HA-09   16                           5             NA
69 HA-09   16   <33% no/occasional             NA             1", na.strings = c("NA", ""))

library(dplyr)
f <- function(x) {
  x <- na.omit(x)
  if (length(x) > 0) first(x) else NA
}
res <- b %>% group_by(ID,Age) %>% summarise_all(funs(f))
##Source: local data frame [1 x 7]
##Groups: ID [?]
##
##      ID   Age Steatosis       Mallory Lille_dico Lille_3 Bili.AHHS2cat
##                                 
##1  HA-09    16      <33% no/occasional         NA       5             1

The definition of the function is to handle the case where all values is NA.

---

As @jdobres suggests, if there are more than one non-NA values that you want to merge (per each column), you may want to flatten all of these to a string representation using:

library(dplyr)
f <- function(x) {
  x <- na.omit(x)
  if (length(x) > 0) paste(x,collapse='-') else NA
}
res <- b %>% group_by(ID,Age) %>% summarise_all(funs(f))

In your posted data, the result would be the same as above because all columns that are summarized has at most one non-NA value.