Find the 'RARE' user based on occurrence in two columns - r

Question

This is what my data frame looks like :
its the data of a song portal(like itunes or raaga)
datf <- read.csv(text =
"albumid,date_transaction,listened_time_secs,userid,songid
6263,3/28/2017,59,3747,6263
3691,4/24/2017,53,2417,3691
2222,3/24/2017,34,2417,9856
1924,3/16/2017,19,8514,1924
6691,1/1/2017,50,2186,6691
5195,1/1/2017,64,2186,5195
2179,1/1/2017,37,2186,2179
6652,1/11/2017,33,1145,6652")
My aim is to pick out the rare user. A 'rare' user is the one which visits the portal not more than once in each calendar month.
for e.g : 2186 is not rare. 2417 is rare because it occurred only once in 2 diff months, so are 3747,1145 and 8514.
I've been trying something like this :
DuplicateUsers <- duplicated(songsdata[,2:4])
DuplicateUsers <- songsdata[DuplicateUsers,]
DistinctSongs <- songsdata %>%
distinct(sessionid, date_transaction, .keep_all = TRUE)
RareUsers <- anti_join(DistinctSongs, DuplicateUsers, by='sessionid')
but doesn't seem to work.

Answer 1

Using library(dplyr) you could do this:
# make a new monthid variable to group_by() with
songdata$month_id <- gsub("\\/.*", "", songdata$date_transaction)
RareUsers <- group_by(songdata, userid, month_id) %>%
filter(n() == 1)
RareUsers
# A tibble: 5 x 6
# Groups: userid, month_id [5]
albumid date_transaction listened_time_secs userid songid month_id
<int> <chr> <int> <int> <int> <chr>
1 6263 3/28/2017 59 3747 6263 3
2 3691 4/24/2017 53 2417 3691 4
3 2222 3/24/2017 34 2417 9856 3
4 1924 3/16/2017 19 8514 1924 3
5 6652 1/11/2017 33 1145 6652 1

Answer 2

You can try something like:
df %>%
mutate(mth = lubridate::month(mdy(date_transaction))) %>%
group_by(mth, userid) %>%
filter(n() == 1)
which gives:
albumid date_transaction listened_time_secs userid songid mth
<int> <fctr> <int> <int> <int> <dbl>
1 6263 3/28/2017 59 3747 6263 3
2 3691 4/24/2017 53 2417 3691 4
3 2222 3/24/2017 34 2417 9856 3
4 1924 3/16/2017 19 8514 1924 3
5 6652 1/11/2017 33 1145 6652 1

Answer 3

You can do it with base R:
# parse date and extract month
datf$date_transaction <- as.Date(datf$date_transaction, "%m/%d/%Y")
datf$month <- format(datf$date_transaction, "%m")
# find non-duplicated pairs of userid and month
aux <- datf[, c("userid", "month")]
RareUsers <- setdiff(aux, aux[duplicated(aux), ])
RareUsers
# userid month
# 1 3747 03
# 2 2417 04
# 3 2417 03
# 4 8514 03
# 5 1145 01
If you need the other columns:
merge(RareUsers, datf)
# userid month albumid date_transaction listened_time_secs songid
# 1 1145 01 6652 2017-01-11 33 6652
# 2 2417 03 2222 2017-03-24 34 9856
# 3 2417 04 3691 2017-04-24 53 3691
# 4 3747 03 6263 2017-03-28 59 6263
# 5 8514 03 1924 2017-03-16 19 1924