Hi
I'm trying to manipulate a data frame (that has about 10 million rows) rows
by "grouping" it with multiple columns. For example, say the data set looks
like:
Area
Sex
Year
y
Bob
F
2011
1
Bob
F
2011
2
Bob
F
2012
3
Bob
M
2012
3
Bob
M
2012
2
Fred
F
2011
1
Fred
F
2011
1
Fred
F
2012
2
Fred
M
2012
3
Fred
M
2012
1
And I want it to look like
Area
Sex
Year
Sum of y
Bob
F
2011
3
Bob
F
2012
3
Bob
M
2012
5
Fred
F
2011
2
Fred
F
2012
2
Fred
M
2012
4
I think I can use something like:
tmp <- aggregate (y ~ ., sum)
But due to the size it's really taking a strain on the computer (even with
64-bit R on a, yes unfortunately Windows, machine with 16GB RAM :(). The
reason for me wanting the data set to get into this form is I want to then
apply the population information and get the "rate" on the "sum of y" column
then fit a Poisson regression model.
I'm wondering (and would appreciate comments) whether there is a more
efficient way to the process I described?
Cheers
Michael
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