Count the number of observations across multiple columns and create new categories

I have data like these:

ID      color_1    color_2   color_3    color_4
1       blue        NA        NA         NA
5       green       blue      yellow     NA
9       None        NA        NA         NA 
2       blue        pink      NA         NA 
11      green       NA        NA         NA 

I want to add a new column that counts the number of colors (None, 1, or 2 or more):

ID      color_1    color_2   color_3    color_4    colors
1       blue        NA        NA         NA          1
5       green       blue      yellow     NA          2 or more
9       None        NA        NA         NA          None 
2       blue        pink      NA         NA          2 or more 
11      green       NA        NA         NA          1

I am thinking I can do something like this:

library(tidyverse)
data2 <- data %>%
 mutate(colors = case_when(
         color_1 == "None" ~ "None",
         

But I can’t figure out how to do the counting part. Any help is appreciated!

>Solution :

You can count using c_across and rowwise:

library(tidyverse)
df %>% 
  na_if("None") %>% 
  rowwise() %>% 
  mutate(count = sum(!is.na(c_across(color_1:color_4))),
         colors = case_when(count >= 2 ~ "2 or more",
                            count == 0 ~ "None",
                            T ~ as.character(count))) %>% 
  select(-count)

Output

     ID color_1 color_2 color_3 color_4 colors   
  <int> <chr>   <chr>   <chr>   <lgl>   <chr>    
1     1 blue    NA      NA      NA      1        
2     5 green   blue    yellow  NA      2 or more
3     9 NA      NA      NA      NA      None     
4     2 blue    pink    NA      NA      2 or more
5    11 green   NA      NA      NA      1