R help - Aug 2006 - Using a 'for' loop : there should be a better way in R

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

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
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>