Solidifying a melted data frame?

Question

Assuming I have a melted data.frame that looks like this:

  variable       value
1         A -0.19933093
2         A -1.19043346
3         A -1.32248172
4         A -1.98644507
5         A -0.07930953
6         B -0.10074686
7         B  0.72451483
8         B -0.40914044
9         B  0.02913376
10        B  0.16062491

How do I get it to:

  A       B
-0.19933093 -0.10074686
-1.19043346  0.72451483
-1.32248172 -0.40914044
-1.98644507  0.02913376
-0.07930953  0.16062491

Seems trivial but I am blanking on an answer. dcast and acast do not seem to do it. My goal is to do this on larger datasets and turn the end product into a matrix with the column names to be the variable names. I tried playing with daply and laply (before melting) without much luck.

Answer 1

Try unstack:

dat <- read.table(text = "variable       value
1         A -0.19933093
2         A -1.19043346
3         A -1.32248172
4         A -1.98644507
5         A -0.07930953
6         B -0.10074686
7         B  0.72451483
8         B -0.40914044
9         B  0.02913376
10        B  0.16062491",sep = "",header = TRUE)

> unstack(dat,value~variable)

            A           B
1 -0.19933093 -0.10074686
2 -1.19043346  0.72451483
3 -1.32248172 -0.40914044
4 -1.98644507  0.02913376
5 -0.07930953  0.16062491

But I should add that I would love to know how to do this using dcast, as I've also tried repeatedly and haven't been able to.

Answer 2

Using acast() to return a matrix. It needs an id variable.

library(reshape2)
dat <- read.table(text = "variable       value
1         A -0.19933093
2         A -1.19043346
3         A -1.32248172
4         A -1.98644507
5         A -0.07930953
6         B -0.10074686
7         B  0.72451483
8         B -0.40914044
9         B  0.02913376
10        B  0.16062491",sep = "",header = TRUE)

dat$id = rep(1:5, 2)
dat

acast(dat, id~variable)