Combine column to remove NA's

r merge na

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

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))

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

Here's a more general (but even simpler) solution which extends to all column types (factors, characters etc.) with non-ordered NA's. The strategy is simply to merge the non-NA values of other columns into your merged column using is.na for indexing:

data$m = data$x  # your new merged column start with x
data$m[!is.na(data$y)] = data$y[!is.na(data$y)]  # merge with y
data$m[!is.na(data$z)] = data$z[!is.na(data$z)]  # merge with z

> data
  a  x  y  z m
1 A  1 NA NA 1
2 B  2 NA NA 2
3 C NA  3 NA 3
4 D NA NA  4 4
5 E NA NA  5 5

Note that this will overwrite existing values in m if there are several non-NA values in the same row. If you have a lot of columns you could automate this by looping over colnames(data).

Combine column to remove NA's

Related

Recent Posts