Create new column in string partial match-based dataframe without repeats - r

Question

I have a dataframe with 2 columns GL and GLDESC and want to add a 3rd column called KIND based on some data that is inside of column GLDESC.
DF:
GL GLDESC
1 515100 Payroll-ISL
2 515900 Payroll-ICA
3 532300 Bulk Gas
4 551000 Supply AB
5 551000 Supply XPTO
6 551100 Supply AB
7 551300 Intern
For each row of the data table:
If GLDESC contains the word Payroll anywhere in the string then I want KIND to be Payroll.
If GLDESC contains the word Supply anywhere in the string then I want KIND to be Supply.
In all other cases I want KIND to be Other.
Then, I found this:
DF$KIND <- ifelse(grepl("supply", DF$GLDESC, ignore.case = T), "Supply",
ifelse(grepl("payroll", DF$GLDESC, ignore.case = T), "Payroll", "Other"))
But with that, I have everything that matches Supply, for example, classified. However, as in DF lines 4 and 5, the same GL has two Supply, which for me is unnecessary. In fact, I need only one type of GLDESC to be matched if for the same GL the string is repeated.
Edit: I can not delet any row. I want to have this as output:
GL GLDESC KIND
A Supply1 Supply
A Supply2 N/A
A Supply3 N/A
A Supply4 N/A
A Supply5 N/A
A Supply6 N/A
A Payroll1 Payroll
B Supply2 Supply
B Payroll Payroll

Answer 1

If we need the repeating element to be NA, use duplicated on 'GLDESC' to get a logical vector and assign those elements in 'KIND' created with ifelse to NA
DF$KIND[duplicated(DF$GLDESC)] <- NA_character_
If we need to change the values by a grouping variable
library(dplyr)
DF %>%
group_by(GL) %>%
mutate(KIND = replace(KIND, duplicated(KIND) & KIND == "Supply", NA_character_))
# A tibble: 9 x 3
# Groups: GL [2]
# GL GLDESC KIND
# <chr> <chr> <chr>
#1 A Supply1 Supply
#2 A Supply2 <NA>
#3 A Supply3 <NA>
#4 A Supply4 <NA>
#5 A Supply5 <NA>
#6 A Supply6 <NA>
#7 A Payroll1 Payroll
#8 B Supply2 Supply
#9 B Payroll Payroll
Or with the full changes
DF1 %>%
mutate(KIND = str_remove(GLDESC, "\\d+"),
KIND = replace(KIND, !KIND %in% c("Supply", "Payroll"), "Othere")) %>%
group_by(GL) %>%
mutate(KIND = replace(KIND, duplicated(KIND) & KIND == "Supply", NA_character_))
data
DF1 <- structure(list(GL = c("A", "A", "A", "A", "A", "A", "A", "B",
"B"), GLDESC = c("Supply1", "Supply2", "Supply3", "Supply4",
"Supply5", "Supply6", "Payroll1", "Supply2", "Payroll")), row.names = c(NA,
-9L), class = "data.frame")