How to update variable value to current value (current value * 100/ colsums())

I have a df like below.:

I would like to do following two steps:

1. if first letter of col name matched the value in Grade and current value is NA, then replace it as 0.
2. update the value from A1:B2 as current value, (current value * 100/ colsums()).

How can I make this happen?

df <- structure(list(Grade = c("A", "A", "B", "B"), Pass = c("Y", "N", 
"Y", "N"), A1 = c(7, 8, NA, NA), A2 = c(4, 5, NA, NA), A3 = c(9, 
NA, NA, NA), B1 = c(NA, NA, 8, NA), B2 = c(NA, NA, 3, 4)), row.names = c(NA, 
-4L), class = c("tbl_df", "tbl", "data.frame"))

>Solution :

With the dplyr package, we can use two across, the first one sets relevant missing values to zero and the second one calculates and displays the percentage.

library(dplyr)

df %>% 
  mutate(across(A1:B2, ~ifelse(str_extract(cur_column(), "^.") == Grade & is.na(.x), 0, .x)), 
         across(A1:B2, ~ifelse(is.na(.x), NA, paste0(.x, " (", round(.x * 100/(sum(.x, na.rm = T)), digits = 2), "%)"))))

# A tibble: 4 × 7
  Grade Pass  A1         A2         A3       B1       B2        
  <chr> <chr> <chr>      <chr>      <chr>    <chr>    <chr>     
1 A     Y     7 (46.67%) 4 (44.44%) 9 (100%) NA       NA        
2 A     N     8 (53.33%) 5 (55.56%) 0 (0%)   NA       NA        
3 B     Y     NA         NA         NA       8 (100%) 3 (42.86%)
4 B     N     NA         NA         NA       0 (0%)   4 (57.14%)