I have a data frame with thousands of rows but a sample is given below:
userid event
1 123 view
2 123 view
3 123 order
4 345 view
5 345 view
6 345 view
7 345 order
8 111 view
9 111 order
10 111 view
11 111 view
12 111 view
13 333 view
14 333 view
15 333 view
dput(data)
structure(list(userid = c(123, 123, 123, 345, 345, 345, 345,
111, 111, 111, 111, 111, 333, 333, 333), eventaction = structure(c(2L,
2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("order",
"view"), class = "factor")), .Names = c("userid", "event"
), row.names = c(NA, -15L), class = "data.frame")
What I am looking at doing is to extract all the rows of userid's that contains the word "order" under event. The result will contain all the rows for userid's excluding userid = 333 as the eventaction does not contain an order entry.
The second task is to count the number of occurences for "view" before the order entry. I will appreciate help and pointers.
Thanks.
We can try with data.table. Convert the 'data.frame' to 'data.table' (setDT(data)), grouped by 'userid', if there are any 'event' that is an 'order' in the 'userid', return the Subset of Data.table' (.SD)
library(data.table)
setDT(data)[,if(any(event=="order")) .SD , by = userid]
Or using dplyr, we filter for any 'order' in the 'event' after grouping by 'userid'.
library(dplyr)
data %>%
group_by(userid) %>%
filter(any(event == "order"))