[R] Using a 'for' loop : there should be a better way in R

[Gabor Grothendieck]

Use cbind to create a two column matrix, mat,
and multiply that by the appropriate inflation factors.
Then use rowsum to sum the rows according to the
id grouping factor.

inf.fac <- list(year1 = 1, year2 = 5, year3 = 10)
mat <- cbind(s1 = df1$cat1 + df1$cat2, s2 = df1$cat3 + df1$cat4)
rowsum(mat * unlist(inf.fac[df1$year]), df1$id)


On 8/24/06, John Kane <jrkrideau at yahoo.ca> wrote:
> I need to apply a yearly inflation factor to some
> wages and supply some simple sums by work category.  I
> have gone at it with a brute force "for" loop approach
>  which seems okay as it is a small dataset.  It looks
> a bit inelegant and given all the warnings in the
> Intro to R, etc, about using loops I wondered  if
> anyone could suggest something a bit simpler or more
> efficent?
>
> Example:
>
> cat1 <- c( 1,1,6,1,1,5)
> cat2 <- c( 1,2,3,4,5,6)
> cat3 <- c( 5,4,6,7,8,8)
> cat4 <- c( 1,2,1,2,1,2)
> years <- c( 'year1', 'year2', 'year3', 'year3',
> 'year1', 'year1')
> id <-  c('a','a','b','c','c','a')
> df1 <- data.frame(id,years,cat1,cat2, cat3, cat4)
>
> nn <- levels(df1$id)    # levels for outer loop
> hh <- levels(df1$years) # levels for inter loop
>
>
> mp <- c(1, 5, 10)   # inflation factor
>
> tt <- data.frame(matrix(NA, length(nn), 2))
> names(tt) <- c("s1","s2")
> rownames(tt) <- nn
>
> for (i in 1:length(nn)){
> scat <- data.frame(matrix(NA, length(hh),2))
> dd1 <- subset(df1, id==nn[i])
> for (j in 1:length(hh)){
> dd2 <- subset(dd1, dd1$years==hh[j])
> s1 <- sum(dd2$cat1,dd2$cat2, na.rm=T)
> s2 <- sum(dd2$cat3,dd2$cat4,na.rm=T)
> scat[j,] <- c(s1,s2) *mp[j]    # multiply by the
> inflation factor
> }
> crush <- apply(scat, 2, sum)
> tt[i,] <- crush
> }
> tt
>
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