# [R] More flexible aggregate / eval

From: Patrick Hausmann <patrick.hausmann_at_uni-bremen.de>
Date: Sat, 30 Apr 2011 13:06:17 +0200

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)

```

## 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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