find last row with to multiple groups

Question

| id | msgid | source | value |
|----|-------|--------|-------|
| 1  | 1     | B      | 0     |
| 1  | 2     | A      | 1     |
| 1  | 3     | B      | 0     |
| 2  | 1     | B      | 0     |
| 2  | 2     | A      | 0     |
| 2  | 3     | A      | 1     |
| 2  | 4     | B      | 0     |

In the above snippet, I want to create column value from the other columns. id is a conversation and msgId is the message in each conversation.

I wish to identify the row number for the last message that came from source=A.

I made an attempt to solve it. However, I was able to identify only the last row within a conversation.

last_values <- dat %>% group_by(id) %>% 
   slice(which.max(msgid)) %>%
   ungroup %>%
   mutate(value = cumsum(msgid))

dat$final_val <- 0    
dat[last_values$value,5] <- 1

Answer 1

We can create the column 'value' by

dat %>% 
  group_by(id) %>% 
  mutate(value1 = as.integer(source == "A" & !duplicated(source == "A", fromLast = TRUE)))
# A tibble: 7 x 5
# Groups: id [2]
#     id msgid source value value1
#  <int> <int> <chr>  <int>  <int>
#1     1     1 B          0      0
#2     1     2 A          1      1
#3     1     3 B          0      0
#4     2     1 B          0      0
#5     2     2 A          0      0
#6     2     3 A          1      1
#7     2     4 B          0      0