Dear list,

I would like to do some calculation using different grouping variables. My 'df' looks like this:

# Some data
set.seed(345)
id <- seq(200,400, by=10)
ids <- sample(substr(id,1,1))
group1 <- rep(1:3, each=7)
group2 <- rep(1:2, c(10,11))
group3 <- rep(1:4, c(5,5,5,6))
df <- data.frame(id, ids, group1, group2, group3)
df <- rbind(df, df, df)
df$time <- seq(2009, 2011, each=3)
df$x1 <- sample(0:100, 63)
df$x2 <- sample(44:234, 63)

head(df)

## For group1
d1 <- aggregate(cbind(x1, x2) ~
                      group1 + ids + time, data = df, sum)

d1$l_pct <- with(d1, ave(x1, list(group1, time),
                 FUN = function(x) round(prop.table(x) * 100, 1) ) )

op1 <- xtabs(l_pct ~ group1 + ids + time, data = d1)
ftable(op1, row.vars=c(1,3))

## For group2
d2 <- aggregate(cbind(x1, x2) ~
                      group2 + ids + time, data = df, sum)

d2$l_pct <- with(d2, ave(x1, list(group2, time),
                 FUN = function(x) round(prop.table(x) * 100, 1) ) )

op2 <- xtabs(l_pct ~ group2 + ids + time, data = d2)
ftable(op2, row.vars=c(1,3))

## and for group3...
## To have a more flexible solution I wrote this function:

myfun <- function(xdf, xvar) {

 fo1 <- "cbind(x1, x2) ~ "
 fo2 <- paste(fo1, xvar, "+ ids + time", sep="")
 formular <- as.formula(fo2)

 d2 <- do.call(aggregate, list(formular, data = xdf, FUN = sum))

 d2$l_pct <- with(d2, ave(x1, list(eval(as.name(xvar)), time),
                  FUN = function(x) round(prop.table(x) * 100, 1) ) )
 op2 <- xtabs(l_pct ~ eval(as.name(xvar)) + ids + time, data = d2)
 fop2 <- ftable(op2, row.vars=c(1,3))
 out <- list(d2, fop2)
 return(out)

}

( out_gr1 <- myfun(df, "group1") )
( out_gr2 <- myfun(df, "group2") )
( out_gr3 <- myfun(df, "group3") )

This seems to work ok, but I am not really familiar with 'as.formula', 'eval' and 'as.name'. So I would like to know, if my solution is ok or if there are maybe better ways to solve this task.

Thanks for any help!!
Patrick

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