Suppose I have this R data frame:
ts year month day
1 1295234818000 2011 1 17
2 1295234834000 2011 1 17
3 1295248650000 2011 1 17
4 1295775095000 2011 1 23
5 1296014022000 2011 1 26
6 1296098704000 2011 1 27
7 1296528979000 2011 2 1
8 1296528987000 2011 2 1
9 1297037448000 2011 2 7
10 1297037463000 2011 2 7
dput(a)
structure(list(ts = c(1295234818000, 1295234834000, 1295248650000,
1295775095000, 1296014022000, 1296098704000, 1296528979000, 1296528987000,
1297037448000, 1297037463000), year = c(2011, 2011, 2011, 2011,
2011, 2011, 2011, 2011, 2011, 2011), month = c(1, 1, 1, 1, 1,
1, 2, 2, 2, 2), day = c(17, 17, 17, 23, 26, 27, 1, 1, 7, 7)), .Names = c("ts",
"year", "month", "day"), row.names = c(NA, 10L), class = "data.frame")
Is there a way to create a vector of data frames, where each one is a subset of the original with unique group-by combinations of year, month, and day? Ideally, I would like to get back data frames DF1, DF2, DF3, DF4, DF5, and DF6, in that order, where:
DF1:
ts year month day
1 1295234818000 2011 1 17
2 1295234834000 2011 1 17
3 1295248650000 2011 1 17
DF2:
4 1295775095000 2011 1 23
DF3:
5 1296014022000 2011 1 26
DF4:
6 1296098704000 2011 1 27
DF5:
7 1296528979000 2011 2 1
8 1296528987000 2011 2 1
DF6:
9 1297037448000 2011 2 7
10 1297037463000 2011 2 7
Any help would be appreciated.
interactionmight be useful if I understand what you want correctly. Something likesplit(a, interaction(a$year, a$month, a$day, drop = T)). - alexis_lazdrop=TRUEcan also be passed as an argument directly tosplit, so this will also work:with(a, split(a, list(year,month,day), drop=TRUE))- thelatemail