Welcome to RStudio Community @ECBN,
@nirgrahamuk provided some great hints above. Below I provide another approach to the problem you described, the R for Data Science book is a great resource to help you complete the visualisation task.
lapply(c("tidyverse","ggmice","mice"),
require,
character.only=TRUE) # Import Libraries
data("starwars") # Dataset
starwars <- split(starwars,starwars$species) #Separating per species into list
col_checker <- function(a_df){
value <- colSums(is.na(a_df))|>t() %>%
data.frame() %>%
select(c(height,mass))
return(value)} # Custom function to check NAs, dataframe results and select relevant columns
map(starwars,col_checker) %>%
do.call(rbind,.) %>%
rownames_to_column("species") #apply the function for all dataframes on the list and output na.value count.