这就是我在data.table 包中的as.ITime() 函数的帮助下要做的事情:
times <- c("04:30:00", "01.09:55:00")
library(data.table)
cols <- c("days", "hms")
as.data.table(times)[
times %like% "[.]", (cols) := tstrsplit(times, "[.]")][
is.na(days), (cols) := .( "0", times)][
, as.integer(days) * 60 * 24 + as.integer(as.ITime(hms, "%H:%M:%S")) / 60][]
[1] 270 2035
基准测试
# create benchmark data
times0 <- CJ(c("", sprintf("%02i.", 1:99)), 1:24, 1:60)[, sprintf("%s%02i:%02i:00", V1, V2, V3)]
# run benchmarks
microbenchmark::microbenchmark(
apitsch = {
times <- copy(times0)
for (i in 1:length(times)){
# for format without days:
if (nchar(times[i]) == 8){
tmp <- as.numeric(unlist(strsplit(times[i], split = ":")))
times[i] <- tmp[1] * 60 + tmp[2] + tmp[3] * 1/60
} else { # for format including days:
tmp <- c(unlist(strsplit(times[i], split = "[.]")))
tmp <- c(tmp[1], unlist(strsplit(tmp[2], split = ":")))
tmp <- as.numeric(tmp)
times[i] <- tmp[1] * 24 * 60 + tmp[2] * 60 + tmp[3] + tmp[4] * 1/60
}
}
times
},
uwe = {
times <- copy(times0)
cols <- c("days", "hms")
as.data.table(times)[
times %like% "[.]", (cols) := tstrsplit(times, "[.]")][
is.na(days), (cols) := .( "0", times)][
, as.integer(days) * 60 * 24 + as.integer(as.ITime(hms, "%H:%M:%S")) / 60][]
},
times = 11L
)
Unit: milliseconds
expr min lq mean median uq max neval cld
apitsch 3485.6488 3561.5639 3708.8017 3631.2264 3747.1996 4288.368 11 b
uwe 493.0976 497.6782 582.6732 540.5967 643.0875 773.587 11 a