Combine column to remove NA's

Question

I have some columns in R and for each row there will only ever be a value in one of them, the rest will be NA's. I want to combine these into one column with the non-NA value. Does anyone know of an easy way of doing this. For example I could have as follows:

data <- data.frame('a' = c('A','B','C','D','E'),                    'x' = c(1,2,NA,NA,NA),                    'y' = c(NA,NA,3,NA,NA),                    'z' = c(NA,NA,NA,4,5)) 

So I would have

'a' 'x' 'y' 'z'    A   1   NA  NA    B   2   NA  NA    C  NA   3   NA    D  NA   NA  4    E  NA   NA  5 

And I would to get

 'a' 'mycol'     A   1     B   2     C   3     D   4     E   5   

The names of the columns containing NA changes depending on code earlier in the query so I won't be able to call the column names explicitly, but I have the column names of the columns which contains NA's stored as a vector e.g. in this example cols <- c('x','y','z'), so could call the columns using data[, cols].

Any help would be appreciated.

Thanks

Answer 1

A dplyr::coalesce based solution could be as:

data %>% mutate(mycol = coalesce(x,y,z)) %>%          select(a, mycol) #   a mycol # 1 A     1 # 2 B     2 # 3 C     3 # 4 D     4 # 5 E     5  

Data

data <- data.frame('a' = c('A','B','C','D','E'),                  'x' = c(1,2,NA,NA,NA),                  'y' = c(NA,NA,3,NA,NA),                  'z' = c(NA,NA,NA,4,5)) 

Answer 2

You can use unlist to turn the columns into one vector. Afterwards, na.omit can be used to remove the NAs.

cbind(data[1], mycol = na.omit(unlist(data[-1])))     a mycol x1 A     1 x2 B     2 y3 C     3 z4 D     4 z5 E     5