It looks like it works right out of the box. (The documentation for
merge() in R1.5.1 pretty clearly mentions the possibility of merging on
multiple columns .)
> m1 <- read.table("tmp1.txt", header=T, row.names=NULL)
> m2 <- read.table("tmp2.txt", header=T, row.names=NULL)
> m1
SUBID TARGID ITEM RATING
1 1 1 1 4
2 1 1 2 5
3 1 1 3 3
4 1 1 4 2
5 1 1 5 5
TARGID ITEM TARGET
1 1 1 5
2 1 2 4
3 1 3 6
4 1 4 2
5 1 5 3
TARGID ITEM SUBID RATING TARGET
1 1 1 1 4 5
2 1 2 1 5 4
3 1 3 1 3 6
4 1 4 1 2 2
5 1 5 1 5 3
At 11:17 AM 10/8/2002 -0700, you wrote:
Greetings,
Is it possible to match several columns in a merge statement? Here is
my problem:
data1 looks like this...
SUBID TARGID ITEM RATING
1 1 1 4
1 1 2 5
1 1 3 3
1 1 4 2
1 1 5 5
......
SUBID is the ID for the raters, TARGID is the ID for the targets being
rated, ITEM ranges from 1 to 64 crossed by TARGID (i.e., all targets
were rated on 64 items), and RATING is the rating given by SUBID for
each TARGID and ITEM.
My second dataset looks like this data2:
TARGID ITEM TARGET
1 1 5
1 2 4
1 3 6
1 4 2
1 5 3
.......
TARGID again is the target's ID, ITEM ranges from 1 to 64, and TARGET
is the rating provided by the target.
I would like to merge these two data.frames by TARGID and ITEM to yield
the following structure:
SUBID TARGID ITEM RATING TARGET
1 1 1 4 5
1 1 2 5 4
1 1 3 3 6
1 1 4 2 2
1 1 5 5 3
........
I realize that merge appears to be the proper tool but there is no
documentation for how to merge by multiple columns. Is this possible?
Thanks in advance for any assistance with the problem.
--
Cheers,
Patrick
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