Create a loop with mutate() in order to get percentage values by column

Question

In order to do an ACP I just need to "percentize" the data below (dummy data).

A <- c(1,3,4,5,2,3,4,1,3)
B <- c(1,3,7,3,7,3,7,3,6)

df <- data.frame(A, B)

df_2 <- mutate(df, A_perc = A/sum(df$A)) %>% 
  mutate(df, B_PERC = B/sum(df$B))

I dont want to normalize data with scale function. Because I have mutiples columns, I have tried to code a loop, which doesn't work. If you have any advice, thank you in advance

for(i in 1:length(samples)) {                              
  df_2 <- mutate(df, samples[[i]]/sum(samples[[i]]))
  
  
}

Answer 1

mutate(df, across(everything(), ~.x/sum(.x)))

Btw, when you use mutate, you don't need to refer to the column using $, it's enough to provide column name.