Count how many values in some cells of a row are not NA (in R)

Question

I\'ve got a data frame with lots of columns. For each row of the data frame, I\'d like to get a count of how many columns are NA. The problem is that I\'m only interested in

Answer 1

You can use is.na() over the selected columns, then rowSums() the result:

library(stringr)
df <- data_frame(
  id = 1:10
  , name = fruit[1:10]
  , word1 = c(words[1:5],NA,words[7:10])
  , word2 = words[11:20]
  , word3 = c(NA,NA,NA,words[25],NA,NA,words[32],NA,NA,words[65]))

df$word_count <- rowSums( !is.na( df [,3:5]))

df
      id         name    word1     word2   word3 n_words
                          
1      1        apple        a    actual           2
2      2      apricot     able       add           2
3      3      avocado    about   address           2
4      4       banana absolute     admit   agree       3
5      5  bell pepper   accept advertise           2
6      6     bilberry         affect           1
7      7   blackberry  achieve    afford alright       3
8      8 blackcurrant   across     after           2
9      9 blood orange      act afternoon           2
10    10    blueberry   active     again   awful       3

Edit

Using dplyr you could do this:

df %>% 
    select(3:5) %>% 
    is.na %>% 
    `!` %>% 
    rowSums