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I am trying to subset/ match data by groups from 2 data.tables and cannot figure out how do this is in R. I have the following data.table that has a City_ID and a time stamp (column name=Time).

Library(data.table)  
timetable <- data.table(City_ID=c("12","9"),
                        Time=c("12-29-2013-22:05:03","12-29-2013-11:59:00"))

I have a second data.table with several observation for cities and time stamps (plus additional data). The table looks like this:

DT = data.table(City_ID =c("12","12","12","9","9","9"),
                Time= c("12-29-2013-13:05:13","12-29-2013-22:05:03",
                        "12-28-2013-13:05:13","12-29-2013-11:59:00",
                        "01-30-2013-10:05:03","12-28-2013-13:05:13"), 
                Other=1:6)

Now I need to find the observations for each city in DT that have a Time >= Time in the other data.table "timetable" (which is basically the matchtable). Only those records should be kept (including the columns that are not used for the calculation; in the example column "other"). The result I want looks like this:

desiredresult = data.table(City_ID=c("12","9"),
                           Time= c("12-29-2013-22:05:03","12-29-2013-11:59:00"),
                           Other=c("2","4"))

I have tried the following: 

setkey(DT, City_ID, Time)  
setkey(timetable, City_ID)  
failedresult = DT[,Time >= timetable[Time], by=City_ID]  
failedresult2 = DT[,Time >= timetable, by=City_ID]

BTW: I know it may be better to additionally split date and time, but this may make the example even more complex (and when I tested finding a minimum in the time stamps through data.table, it seemed to work).

A5C1D2H2I1M1N2O1R2T1
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user3340145
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1 Answers1

3

Here's an approach for this task:

# 1) transform string to POSIXct object
DT[ , Time := as.POSIXct(strptime(Time, "%m-%d-%Y-%X"))]
timetable[ , Time := as.POSIXct(strptime(Time, "%m-%d-%Y-%X"))]

# 2) set key
setkey(DT, City_ID)
setkey(timetable, City_ID)

# 3) join tables
DT2 <- DT[timetable]

# 4) extract rows and columns
DT2[Time >= Time.1, .SD, .SDcols = names(DT)]

#    City_ID                Time Other
# 1:      12 2013-12-29 22:05:03     2
# 2:       9 2013-12-29 11:59:00     4
MichaelChirico
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Sven Hohenstein
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