How to run a loop creating new columns?

I have a dataset with columns that contain information of a code + name, which I would like to separate into 2 columns. So, just an example:

Column E5000_A contain values like `0080002. ALB - Democratic Party' in one cell, I would like two columns one containing the code 0080002, and the other containing the other info.

I have 8 more columns with values very similar (E5000_A until E5000_H). This is the code that I am writing.

cols2 <- c("E5000_A" , "E5000_B" , "E5000_C" , "E5000_D" , 
           "E5000_E" , "E5000_F" , "E5000_G" , "E5000_H" )

for(i in cols2){
  cses_imd_m <- cses_imd_m %>% mutate(substr(i, 1L, 7L))  
}

But for some reason it is only generating a new column for the E5000_A and the loop does not go to the other variables. What am I doing wrong? Let me know if you need more details about the code or data frame.

Solution

data.frame approach

# to extract codes
df %>% 
mutate_at(.vars = vars(c("E5000_A", "E5000_B", "E5000_C", "E5000_D", "E5000_E", 
                          "E5000_F", "E5000_G", "E5000_H")), 
          .funs = function(x) str_extract("^\\d+", x))

You can also use across() inside of mutate().

If you want to use for loop

col_names <- c("E5000_A", "E5000_B", "E5000_C", "E5000_D", "E5000_E", "E5000_F", "E5000_G", "E5000_H")

for (i in col_names) {
  
  df[,sprintf("code_%s", i)] <- str_extract("^\\d+", df[,i])
  df[,sprintf("party_%s", i)] <- gsub(".*\\.", "", df[,i]) %>% str_trim() # remove all before dot (.)
  
}