Aggregate R sum

Question

I'm writting my first program in R and as a newbie I'm having some troubles, hope you can help me.

I've got a data frame like this:

> v1<-c(1,1,2,3,3,3,4)
> v2<-c(13,5,15,1,2,7,4)
> v3<-c(0,3,6,13,8,23,5)
> v4<-c(26,25,11,2,8,1,0)
> datos<-data.frame(v1,v2,v3,v4)
> names(datos)<-c("Position","a1","a2","a3")

> datos
  posicion a1 a2 a3
1        1 13  0 26
2        1  5  3 25
3        2 15  6 11
4        3  1 13  2
5        3  2  8  8
6        3  7 23  1
7        4  4  5  0

What I need is to sum the data in a1, a2 and a3 (in my real case from a1 to a51) grouped by Position. I'm trying with the function aggregate() but it only works for means, not for sums and I don't know why.

Thanks in advance

Solution 1

This is fairly straightforward with the plyr library.

library("plyr")
ddply(datos, .(Position), colwise(sum))

If you have additional non-numeric columns that shouldn't be averaged, you can use

ddply(datos, .(Position), numcolwise(sum))

Solution 2

You need to tell the aggregate function to use sum, as the default is for it to get the mean of each category. For example:

aggregate(datos[,c("a1","a2","a3")], by=list(datos$Position), "sum")

Comments

[Nerea Valcárcel]

Hi Brian, I've made a proof and it seems to be what I need. However I need to check some things with my real data. I'll let you know. Thank you for your help!

[Nerea Valcárcel]

I've checked it and it's just what I needed. Thank you so much!