Create multiple columns based on the content of another column [duplicate]

Question

In a dataset i have a column containing letters, as follows:

d = data.frame(col1 = c("ABC", "CDE","ACE","BDF"))
d

  col1
1  ABC
2  CDE
3  ACE
4  BDF

I would like to create a column for each different letter that is contained in col1 and those column would be TRUE/FALSE, as follows:

  col1     A
1  ABC  TRUE
2  CDE FALSE
3  ACE  TRUE
4  BDF FALSE

But the thing is that i have 25 different ones. So to identify each different characters that is contained in the column i already have the function needed :

find.characters <- function(v1){
  x1 <- unique(unlist(strsplit(v1, '')))
  indx <- grepl('[A-Z]', x1)
  c(sort(x1[indx]), sort(x1[!indx]))
}
find.characters(d$col1)

[1] "A" "B" "C" "D" "E" "F"

But i struggle to create a list of columns based on this list of characters

Answer 1

You can take advantage of the LETTERS built-in character vector to create the column names and apply grepl on each of its elements:

d[LETTERS] <- sapply(LETTERS, \(l) grepl(l, d$col1))

output

#   col1     A     B     C     D     E     F     G     H     I     J     K     L     M     N     O     P     Q     R
# 1  ABC  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 2  CDE FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 3  ACE  TRUE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 4  BDF FALSE  TRUE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#       S     T     U     V     W     X     Y     Z
# 1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 2 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 3 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 4 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE