I have a data frame in the following format:
Site Year Month Count1 Count2 Count3 Patch
1 1 May 15 12 10 1
1 1 May 8 0 5 2
1 1 May 3 1 2 3
1 1 May 4 4 1 4
1 1 June 6 5 1 1
1 1 June 9 1 3 2
1 1 June 3 0 0 3
1 1 June 5 5 2 4
1 1 July 4 0 3 1
..........
And I wish to collapse the data frame across the levels of patch such that the three count variables are summed. i.e.
Site Year Month Count1 Count2 Count3
1 1 May 30 17 18
1 1 June 23 11 6
1 1 July 4 0 3
.........
I've looked at the aggregate and tapply commands, but they do not seem to sum across patch as required.
Can somebody please advise on a command that will convert the data accordingly.
Thank you.
With aggregate:
> ( a <- aggregate(.~Site+Year+Month, dat[-length(dat)], sum) )
# Site Year Month Count1 Count2 Count3
# 1 1 1 July 4 0 3
# 2 1 1 June 23 11 6
# 3 1 1 May 30 17 18
Where dat is your data.
Note that your July results in the post are seem to be incorrect.
For the result in the order of the original data, you can use
> a[order(as.character(unique(dat$Month))), ]
# Site Year Month Count1 Count2 Count3
# 3 1 1 May 30 17 18
# 2 1 1 June 23 11 6
# 1 1 1 July 4 0 3