R data.table podzbiór

Question

Mam zestaw danych, który składa się z danych transakcji klienta. Ma znaczniki czasu, kiedy zdarzały się pewne wydarzenia. Chciałbym otrzymywać tylko wydarzenia, które miały miejsce przed określonym wydarzeniem, ale dla każdego klienta, a nie tylko jednego punktu w czasie.

Oto migawka:

 custId   date_time_recorded    event   dateTime1 
1 280512544 2012-11-13 15:25:37.947-08   shipped 2012-11-13 15:25:37 
2 280512544 2012-11-13 15:22:42.614-08  statusCheck 2012-11-13 15:22:42 
3 280512544 2012-11-13 15:03:16.62-08  statusCheck 2012-11-13 15:03:16 
4 280512544 2012-11-13 15:01:35.149-08  statusCheck 2012-11-13 15:01:35 
5 280512544 2012-11-13 14:45:41.964-08  status-picked 2012-11-13 14:45:41 
6 280512544 2012-11-13 14:44:57.664-08 warehouse_notified 2012-11-13 14:44:57 
7 280512544 2012-11-13 14:44:57.644-08  statusCheck 2012-11-13 14:44:57 
8 280512544 2012-11-13 13:05:15.725-08  recordCreated 2012-11-13 13:05:15 
9 280510610 2012-11-13 09:22:36.427-08   shipped 2012-11-13 09:22:36 
10 280510610 2012-11-13 09:20:07.202-08  statusCheck 2012-11-13 09:20:07 
11 280510610 2012-11-13 09:14:56.182-08  statusCheck 2012-11-13 09:14:56 

Chciałbym dostać tylko zdarzenia, które miały miejsce przed „Wysłane” zdarzenia. Obecnie używam ddply, aby to osiągnąć, ale zajmuje to dużo czasu.

keepPreShip <- function(x){ 
shipTime <- fastPOSIXct(x[grep("shipped", x$event, ignore.case = T), "date_time_recorded"],tz = "UTC") 
#shipTime <- fastPOSIXct(x[x$event =="shipped", "date_time_recorded"],tz = "UTC") 
x <- x[x$dateTime1 < shipTime,] 
} 

system.time(eventsMain1 <- ddply(ss1, .(custId), keepPreShip)) 

Czy jest to szybszy sposób? Może z data.table?

Oto dput danych:

> dput(ss1) 
structure(list(custId = c(280512544L, 280512544L, 280512544L, 
280512544L, 280512544L, 280512544L, 280512544L, 280512544L, 280510610L, 
280510610L, 280510610L, 280510610L, 280510610L, 280510610L, 280510610L, 
280510610L, 280511123L, 280511123L, 280511123L, 280511123L), 
    date_time_recorded = c("2012-11-13 15:25:37.947-08", "2012-11-13 15:22:42.614-08", 
    "2012-11-13 15:03:16.62-08", "2012-11-13 15:01:35.149-08", 
    "2012-11-13 14:45:41.964-08", "2012-11-13 14:44:57.664-08", 
    "2012-11-13 14:44:57.644-08", "2012-11-13 13:05:15.725-08", 
    "2012-11-13 09:22:36.427-08", "2012-11-13 09:20:07.202-08", 
    "2012-11-13 09:14:56.182-08", "2012-11-13 09:11:40.438-08", 
    "2012-11-13 09:03:51.571-08", "2012-11-13 09:03:51.461-08", 
    "2012-11-13 09:03:49.174-08", "2012-11-13 06:42:10.208-08", 
    "2012-11-13 13:51:05.039-08", "2012-11-13 13:13:16.452-08", 
    "2012-11-13 12:42:08.917-08", "2012-11-13 12:28:51.541-08" 
    ), event = c("shipped", "statusCheck", "statusCheck", "statusCheck", 
    "status-picked", "warehouse_notified", "statusCheck", "recordCreated", 
    "shipped", "statusCheck", "statusCheck", "statusCheck", "status-picked", 
    "warehouse_notified", "statusCheck", "recordCreated", "shipped", 
    "statusCheck", "statusCheck", "statusCheck"), dateTime1 = structure(c(1352820337.947, 
    1352820162.614, 1352818996.62, 1352818895.149, 1352817941.964, 
    1352817897.664, 1352817897.644, 1352811915.725, 1352798556.427, 
    1352798407.202, 1352798096.182, 1352797900.438, 1352797431.571, 
    1352797431.461, 1352797429.174, 1352788930.208, 1352814665.039, 
    1352812396.452, 1352810528.917, 1352809731.541), class = c("POSIXct", 
    "POSIXt"), tzone = "UTC")), .Names = c("custId", "date_time_recorded", 
"event", "dateTime1"), row.names = c(NA, 20L), class = "data.frame") 

Answer 1

To działa. Mam nadzieję, że to szybciej.

require(data.table) 
# convert this column to date format first 
ss1$date_time_recorded <- as.POSIXct(ss1$date_time_recorded) 
dt <- data.table(ss1, key="custId") 
dt[, .SD[dateTime1 < date_time_recorded[event == "shipped"]], by=custId] 

#  custId date_time_recorded   event   dateTime1 
# 1: 280510610 2012-11-13 06:42:10 recordCreated 2012-11-13 06:42:10 
# 2: 280511123 2012-11-13 12:42:08 statusCheck 2012-11-13 12:42:08 
# 3: 280511123 2012-11-13 12:28:51 statusCheck 2012-11-13 12:28:51 
# 4: 280512544 2012-11-13 13:05:15 recordCreated 2012-11-13 13:05:15