[R] aggregate function

[Gabor Grothendieck]

You can use rowsum like this:

R> rowsum(frame$Total * (frame[,3:5]>0), frame$Year)

Tus Whi Norw
1994 1 0.00 1
1995 1 1.00 1
1997 2 4.00 5
1998 0 0.00 1
1999 1 2.04 2

Note that only years that are actually present will be in the
resulting matrix. 1996 is not in frame so there is
no row for 1996. If that's not a problem or if your data
covers all the years anyways we are done.

If that *is* a problem then merge in some zero rows first. The first
two lines below do this and the third line is the same as the line
above:

R> frame <- merge(frame, 1994:1999, by = 1, all = TRUE)
R> frame[is.na(frame)] <- 0

R> sapply(frame[3:5], function(x) with(frame, tapply(Total*(x>0), Year, sum)))

Tus Whi Norw
1994 1 0.00 1
1995 1 1.00 1
1996 0 0.00 0 <-- now we have a row for 1996
1997 2 4.00 5
1998 0 0.00 1
1999 1 2.04 2


Luis Rideau Cruz <Luisr <at> frs.fo> writes:

:
: Hi all,
: I have the folowing frame(there are more columns than shown),
: 1 2 3 4 5
: Year Total Tus Whi Norw
: 1994 1.00 1830 0 355
: 1995 1.00 0 0 0
: 1995 1.00 0 0 0
: 1995 1.00 4910 4280 695
: 1997 1.00 0 0 110
: 1997 0.58 0 0 0
: 1997 1.00 0 0 0
: 1994 1.00 0 0 0
: 1997 1.00 0 40 70
: 1998 1.00 0 0 1252
: 1999 1.04 0 74 0
: 1999 1.00 0 0 0
: 1999 1.02 0 0 0
: 1999 1.00 0 0 0
: 1999 1.00 0 0 171
: 1999 1.00 1794 0 229
: 1999 1.00 0 3525 0
: 1997 1.00 1335 1185 147
: 1997 1.00 4925 1057 4801
: 1997 1.00 0 6275 1773
:
: I try to get sum("Total") by "Year" in which Tus>0, sum("Total") by "Year"
in which Whi>0,,,and so on.
:
: I have done something like this;
:
: a<-as.list(numeric(3))
: for (i in 3:5)
: {
: a[[i]]<-aggregate(frame[,"Total"],list(Year=frame$"Year",
: Tus=frame$"i">0),sum)
: }
:
: But I get
:
: "Error in FUN(X[[as.integer(1)]], ...) : arguments must have same length"
:
: Also by doing one by one
:
: aggregate(frame[,"Total"],list(Year=frame$"Year",
: Tus=frame$"Tus">0),sum)
:
: The result is something like;
:
: Year Tus x
: 1994 FALSE 49.69
: 1995 FALSE 49.35
: 1996 FALSE 56.95
: 1997 FALSE 57.00
: 1998 FALSE 57.00
: 1999 FALSE 58.09
: 2000 FALSE 56.97
: 2001 FALSE 57.95
: 2002 FALSE 57.10
: 2003 FALSE 56.16
: 2000 TRUE 1.00
: 2002 TRUE 1.00
: 2003 TRUE 2.01