I have a large data frame (6 million rows) with one row for entry times and next one for exit times of the same unit (id). I need to put them together.
Original data looks something like the following (please bear in mind that some "id" may entry and exit twice like in case of id=1):
df <- read.table(header=T, text='id time
1 "15/12/2014 06:30"
1 "15/12/2014 06:31"
1 "15/12/2014 06:34"
1 "15/12/2014 06:35"
2 "15/12/2014 06:36"
2 "15/12/2014 06:37"
3 "15/12/2014 06:38"
3 "15/12/2014 06:39"')
Output that I need:
id entry exit
1 15/12/2014 06:30 15/12/2014 06:31
2 15/12/2014 06:34 15/12/2014 06:35
3 15/12/2014 06:36 15/12/2014 06:37
4 15/12/2014 06:38 15/12/2014 06:39
Right now I tried a for loop which picks the id and entry time from row 1 and the exit time from time from row2, and puts them together:
for (i in 1:nrow(df)){
outputdf[i,1] <- df[i+i-1,1]
outputdf[i,2] <- df[i+i-1,2]
outputdf[i,3] <- df[i+i-1+1,2]
}
The problem is that it is very inefficient (works for 10k subsets but not for my 6million data frame). I need something that takes less than a minute at least. I have 6 million rows in the df
. Do you know any alternative faster than this loop to match rows?
You could try
library(data.table)
dcast.data.table(setDT(df)[ ,c('.id', 'Seq'):=
list(c('entry', 'exit'), gl(.N,2, .N))], id+Seq~.id, value.var='time')
# id Seq entry exit
#1: 1 1 15/12/2014 06:30 15/12/2014 06:31
#2: 1 2 15/12/2014 06:34 15/12/2014 06:35
#3: 2 3 15/12/2014 06:36 15/12/2014 06:37
#4: 3 4 15/12/2014 06:38 15/12/2014 06:39
df <- structure(list(id = c(1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L), time =
structure(1:8, .Label = c("15/12/2014 06:30",
"15/12/2014 06:31", "15/12/2014 06:34", "15/12/2014 06:35", "15/12/2014 06:36",
"15/12/2014 06:37", "15/12/2014 06:38", "15/12/2014 06:39"), class
= "factor")),.Names = c("id", "time"), class = "data.frame", row.names
= c(NA, -8L))
Maybe I'm missing something, but how about this??
indx <- seq(1,nrow(df)-1,2)
result <- with(df,data.frame(seq=seq(indx),id=id[indx],entry=time[indx],exit=time[indx+1]))
result
# seq id entry exit
# 1 1 1 15/12/2014 06:30 15/12/2014 06:31
# 2 2 1 15/12/2014 06:34 15/12/2014 06:35
# 3 3 2 15/12/2014 06:36 15/12/2014 06:37
# 4 4 3 15/12/2014 06:38 15/12/2014 06:39
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