Hi
It seems to me that it is work for aggregate. Your code is not reproducible so
we cannot test it.
> temp<-read.table("clipboard", header=T)
> temp
Country Product Brand Year_Month DisplaySize OperationSystem
1 AE 1 20 201204 1 1
2 AE 5 20 201204 1 1
3 AE 2 28 201204 3 2
4 AE 3 27 201204 1 1
5 AE 1 20 201205 1 1
6 AE 2 28 201205 3 2
7 AE 4 20 201205 1
2> aggregate(temp$DisplaySize, list(temp$Brand), sum)
Group.1 x
1 20 4
2 27 1
3 28 6
> aggregate(temp$DisplaySize, list(temp$Brand, temp$Year_Month), sum)
Group.1 Group.2 x
1 20 201204 2
2 27 201204 1
3 28 201204 3
4 20 201205 2
5 28 201205 3
More flexible but more complicated is plyr package, which could probably be used
too.
Cheers
Petr
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of conglan
> Sent: Wednesday, February 25, 2015 10:09 AM
> To: r-help at r-project.org
> Subject: [R] How to avoid two for loops?
>
> HI,
>
> I have the following large data set:
> the sample is as the following:
> Country Product Brand Year_Month DisplaySize OperationSystem
> AE 1 20 201204 1
> 1
> AE 5 20 201204 1
> 1
> AE 2 28 201204 3
> 2
> AE 3 27 201204 1
> 1
> AE 1 20 201205 1
> 1
> AE 2 28 201205 3
> 2
> AE 4 20 201205 1
> 2
>
> I want to calculate the extra three columns as the following:
> Let's say "20" is own brand
> #The sums of display size produced by competing brand
> #The sums of display size of other products produced by own brand
> #The sums of display size of products of competing firm in the same
> operating system
>
> I build up the following codes, apprently two loop takes too long time:
>
> dd<-unique(cl$Year_Month)
>
> fldata<-data.frame(NULL)
>
> for ( i in 1:length(dd)){
>
> cls<-cl[cl$Year_Month==dd[i],]
> ws<-numeric(0) #The sums of characteristics of products produced by
> competing firms
> ws1<-numeric(0) #The sums of characteristics of other products
> produced
> by firm
> ws2<-numeric(0) #The sums of characteristics of products of competing
> firm in the same operating system
>
>
> for (j in 1:dim(cls)[1]){
>
> wd<-sum(cls[cls$Brand!=cls$Brand[j],]$DISPLAY_SIZE_INCH)
> ws[j]<-wd
> wc<-sum(cls[cls$Brand==cls$Brand[j] & cls$Item_Id!=cls$Item_Id[j]
> ,]$DISPLAY_SIZE_INCH)
> ws1[j]<-wc
> wf<-sum(cls[cls$Brand!=cls$Brand[j] &
> cls$OPERATING_SYST==cls$OPERATING_SYST[j]
> ,]$DISPLAY_SIZE_INCH)
> ws2[j]<-wf
> }
>
> cls<-cbind(cls,SumPCf=ws,SumOPf=ws1,SumPCfOp=ws2)
> fldata<-rbind(fldata,cls)
>
> }
>
>
> how can I avoid two loops and improve the speed of my code??????? any
> other
> solution?
>
>
> Thanks.
>
> Tammy
>
>
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/How-to-
> avoid-two-for-loops-tp4703799.html
> Sent from the R help mailing list archive at Nabble.com.
> [[alternative HTML version deleted]]
>
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> and provide commented, minimal, self-contained, reproducible code.
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