I have data like this:
library(data.table)
id <- c(\"1232\",\"1232\",\"1232\",\"4211\",\"4211\",\"4211\")
conversion <- c(0,0,0,1,1,1)
DT <- data.ta
Timings for reference:
library(data.table)
#data.table 1.12.3 IN DEVELOPMENT built 2019-05-12 17:04:48 UTC; root using 4 threads (see ?getDTthreads). Latest news: r-datatable.com
set.seed(0L)
nid <- 3e6L
DT <- data.table(id=rep(1L:nid, each=3L))[,
conversion := sample(c(0L,1L), 1L, replace=TRUE), by=.(id)]
DT0 <- copy(DT)
DT1 <- copy(DT)
DT2 <- copy(DT)
DT3 <- copy(DT)
mtd0 <- function() {
DT0[DT0[, .I[.N], by=id]$V1, lastconv := conversion]
DT0[is.na(lastconv), lastconv := 0L]
}
mtd1 <- function() {
DT1[DT1[, .I[.N], by=id]$V1, lastconv := conversion]
setnafill(DT1, cols = "lastconv", fill = 0L)
}
mtd2 <- function() {
DT2[, v := 0]
DT2[.(DT2[conversion == 1, unique(id)]), on=.(id), mult="last", v := 1]
#or also
#DT2[, v := 0L][
# DT2[,.(cv=last(conversion)), id], on=.(id), mult="last", v := cv]
}
mtd3 <- function() {
DT3[ , lastconv := as.integer(.I == .I[.N] & conversion == 1), by = id]
}
library(microbenchmark)
microbenchmark(mtd0(), mtd1(), mtd2(), mtd3(), times=1L)
timings:
Unit: milliseconds
expr min lq mean median uq max neval cld
mtd0() 1363.1783 1416.1867 1468.9256 1469.1952 1521.7992 1574.4033 3 b
mtd1() 1349.5333 1365.4653 1378.9350 1381.3974 1393.6358 1405.8743 3 b
mtd2() 511.5615 515.4728 552.9133 519.3841 573.5892 627.7944 3 a
mtd3() 3966.8867 4009.1128 4048.9607 4051.3389 4089.9977 4128.6564 3 c