Alternatives to stats::reshape

Question

The melt/cast functions in the reshape package are great, but I\'m not sure if there is a simple way to apply them when measured variables are of different types. For example,

Answer 1

I think the reshape function in the stats package is simplest. Here is a simple example, does this do what you want?

> tmp
  id val val2 cat
1  1   1   14   a
2  1   2   13   b
3  2   3   12   b
4  2   4   11   a
> tmp2 <- tmp
> tmp2$t <- ave(tmp2$val, tmp2$id, FUN=seq_along)
> tmp2
  id val val2 cat t
1  1   1   14   a 1
2  1   2   13   b 2
3  2   3   12   b 1
4  2   4   11   a 2
> reshape(tmp2, idvar='id', timevar='t', direction='wide')
  id val.1 val2.1 cat.1 val.2 val2.2 cat.2
1  1     1     14     a     2     13     b
3  2     3     12     b     4     11     a

Hopefully your patients sex is not changing each appointment, but there could be other categorical variables that change between visits

Answer 2

You can process each variable separately, and join the resulting two data.frames.

# Sample data
n <- 5
d <- data.frame(
  id = 1:n,
  pt1 = sample(c("M","F"),n,replace=TRUE),
  wt1 = round(runif(n,100,200)),
  pt2 = sample(c("M","F"),n,replace=TRUE),
  wt2 = round(runif(n,100,200)),
  pt3 = sample(c("M","F"),n,replace=TRUE),
  wt3 = round(runif(n,100,200))
)
# Reshape the data.frame, one variable at a time
library(reshape2)
d1 <- melt(d, 
  id.vars="id", measure.vars=c("pt1","pt2","pt3"), 
  variable.name="patient", value.name="gender"
)
d2 <- melt(d, 
  id.vars="id", measure.vars=c("wt1","wt2","wt3"), 
  variable.name="patient", value.name="weight"
)
d1$patient <- as.numeric(gsub("pt", "", d1$patient))
d2$patient <- as.numeric(gsub("wt", "", d1$patient))
# Join the two data.frames
merge(d1, d2, by=c("id","patient"), all=TRUE)