counting NAs across several columns of various types

[leoncio]

Hello,

when I want to identify complete cases across several columns using dplyr it will not work if columns are of different types. How to code to solve this error?
My code looks like this:

library(tidyverse)

dbase <- starwars |> rowwise() |> 
mutate(compcases = ifelse(complete.cases(c_across(c(name : mass,  birth_year)))==TRUE, 1, NA))

I get the message:
Caused by error in vec_c():
! Can't combine name and height .

I would like to code using pipe operator and cannot figure out how to overcome this. Help appreciated.
Cheers

[technocrat]

library(tidyverse)
dim(starwars)
#> [1] 87 14
pruned <- tidyr::drop_na(starwars)
dim(pruned)
#> [1] 29 14

[nirgrahamuk]

this works

res <- starwars |> mutate(compcases = 
                            select(starwars,name:mass,birth_year) |> complete.cases())

res$compcases

[leoncio]

Yeah, thought about drop_na() but could not come up with an idea how to use it on a subset of columns, that is, eliminate NAs based only on a subset of variables, while retaining all columns and all rows in the dataframe..

[leoncio]

Yes, thanks again

PS. I somehow cannot rely this to my data frame, the error message is "compcases must be size 1 not ..." but I guess it is something with my data frame, it works fine with starwars

however, this notation works:

res <- starwars
res$compcases  <- select(starwars,name:mass,birth_year) |> complete.cases()