merging with aggregating

Dear List,

I have two data.frame of the following form:

A:

n  V1 V2
1  12  0 
2  10  8
3   3  8 
4   8  4
6   7  3  
7  12  0 
8   1  0 
9  18  0 
10  1  0
13  2  0

B:

n  V1 V2
1   0  2
2   0  3
3   1  9
4  12  8 
5   2  9
6   2  9
8   2  0
10  4  1
11  7  1
12  0  1


Now I want to merge those frame to one data.frame with summing up the
columns V1 and V2 but not the column n. So the result in this example
would be:

AB:

n  V1 V2
1  12  2
2  10 11 
3   4 17
4  20 12
5   2  9
6   9 12
7  12  0
8   3  0
9  18  0
10  5  1
11  7  1
12  0  1
13  2  0 


So Columns V1 and V2 are the sum of A und B while n has its old value.
Notice that there are different rows in n of A and B.

I don't have a clue how to start here. Any hint is welcome.

Thanks

There might be a somewhat easier way, but here is one approach:

# Use merge() to join A and B on 'n'
# Set all = TRUE to include non-matched rows

C <- merge(A, B, by = "n", all = TRUE)

C

n V1.x V2.x V1.y V2.y
1   1   12    0    0    2
2   2   10    8    0    3
3   3    3    8    1    9
4   4    8    4   12    8
5   5   NA   NA    2    9
6   6    7    3    2    9
7   7   12    0   NA   NA
8   8    1    0    2    0
9   9   18    0   NA   NA
10 10    1    0    4    1
11 11   NA   NA    7    1
12 12   NA   NA    0    1
13 13    2    0   NA   NA


# Now get the rowSums() for the V1/V2 column pairs
# and create a new dataframe from the 
# results

AB <- data.frame(n = C$n, 

V1 = rowSums(C[, c(2, 4)], na.rm = TRUE), 
                   V2 = rowSums(C[, c(3, 5)], na.rm = TRUE))

AB

n V1 V2
1   1 12  2
2   2 10 11
3   3  4 17
4   4 20 12
5   5  2  9
6   6  9 12
7   7 12  0
8   8  3  0
9   9 18  0
10 10  5  1
11 11  7  1
12 12  0  1
13 13  2  0


See ?merge and ?rowSums for more information.

HTH,

Marc Schwartz