# [R] how to make aggregation in R ?

Gabor Grothendieck ggrothendieck at gmail.com
Fri Mar 20 02:37:14 CET 2009

```Here are two solutions:

> aggregate(testDF[c("n1", "n2")], testDF[c("v1", "v2")], sum)
v1 v2 n1 n2
1   a a1  6 66
2   a a2  4 24
3   a a3  5 25
4   b b1 13 53
5   b b2 27 87
6   c c1 11 31
7   c c2 39 99
8   c c3 15 35
9   d d1 16 36
10  d d2 17 37
11  d d3 18 38
12  d d4 39 79

> library(sqldf)
> sqldf("select v1, v2, sum(n1), sum(n2) from testDF group by v1, v2")
v1 v2 sum(n1) sum(n2)
1   a a1       6      66
2   a a2       4      24
3   a a3       5      25
4   b b1      13      53
5   b b2      27      87
6   c c1      11      31
7   c c2      39      99
8   c c3      15      35
9   d d1      16      36
10  d d2      17      37
11  d d3      18      38
12  d d4      39      79

On Thu, Mar 19, 2009 at 9:18 PM, Ferry <fmi.mlist at gmail.com> wrote:
> Hi,
>
> I think I found the solution.
> Using doBy library, I got:
>
> testDF.result2 <- summaryBy(n1+n2 ~ v1+v2, data = testDF, FUN=sum)
>
>> testDF.result2
>   v1 v2 n1.sum n2.sum
> 1   a a1      6     66
> 2   a a2      4     24
> 3   a a3      5     25
> 4   b b1     13     53
> 5   b b2     27     87
> 6   c c1     11     31
> 7   c c2     39     99
> 8   c c3     15     35
> 9   d d1     16     36
> 10  d d2     17     37
> 11  d d3     18     38
> 12  d d4     39     79
>
> In any case, did I do something wrong using the aggregate function?
>
> Thanks,
>
> Ferry
>
> On Thu, Mar 19, 2009 at 6:09 PM, Ferry <fmi.mlist at gmail.com> wrote:
>
>> Hi,
>>
>> I am trying to aggregate the sum of my test data.frame as follow:
>>
>> testDF <- data.frame(v1 = c("a", "a", "a", "a", "a", "b", "b", "b", "b",
>> "b", "c", "c", "c", "c", "c", "d", "d", "d", "d", "d"),
>>                      v2 = c("a1", "a1", "a1", "a2", "a3", "b1", "b1", "b2",
>> "b2", "b2", "c1", "c2", "c2", "c2", "c3", "d1", "d2", "d3", "d4", "d4"),
>>                      n1 = 1:20,
>>                      n2 = 21:40 )
>>
>> testDF <- orderBy( ~ v1+v2, data = testDF)
>> rownames(testDF) <- NULL
>>
>> > testDF
>>    v1 v2 n1 n2
>> 1   a a1  1 21
>> 2   a a1  2 22
>> 3   a a1  3 23
>> 4   a a2  4 24
>> 5   a a3  5 25
>> 6   b b1  6 26
>> 7   b b1  7 27
>> 8   b b2  8 28
>> 9   b b2  9 29
>> 10  b b2 10 30
>> 11  c c1 11 31
>> 12  c c2 12 32
>> 13  c c2 13 33
>> 14  c c2 14 34
>> 15  c c3 15 35
>> 16  d d1 16 36
>> 17  d d2 17 37
>> 18  d d3 18 38
>> 19  d d4 19 39
>> 20  d d4 20 40
>> >
>>
>> testDF.result <- aggregate(list(testDF\$n1, testDF\$n2), by = list(testDF\$v1,
>> testDF\$v2), FUN = sum)
>>
>> > testDF.result
>>    Group.1 Group.2 X1.20 X21.40
>> 1        a      a1     6     66
>> 2        a      a2     4     24
>> 3        a      a3     5     25
>> 4        b      b1    13     53
>> 5        b      b2    27     87
>> 6        c      c1    11     31
>> 7        c      c2    39     99
>> 8        c      c3    15     35
>> 9        d      d1    16     36
>> 10       d      d2    17     37
>> 11       d      d3    18     38
>> 12       d      d4    39     79
>> >
>>
>>
>> However, when I applied it to my real data, it failed. It seems that
>> aggregate require more memory that I have currently (I am using WinXP,
>> R2.8.0, 2GB RAM).
>>
>> Basically I want to perform aggregate sum on my numeric fields (in the
>> above case, n1 and n2) based on condition of v1 and v2.
>>
>> Problem is, I have a lot more of than just two numerics and conditioning
>> fields.
>>
>> In SQL, I would do:
>> select v1, v2, sum(n1), sum(n2) from myData
>> group by v1, v2;
>>
>> Am I using a wrong function / library (or even wrong approach)? If so, can
>> you suggest which one?
>>
>> Any pointer is really appreciated.
>>
>> Thanks,
>>
>> Ferry
>>
>
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