Assuming I have a melted data.frame
that looks like this:
variable value
1 A -0.19933093
2 A -1.19043346
3 A -1.
Alright, begin with a data frame in wide form, containing an id. melt()
it to give the long form, then dcast()
it to get back to the original data frame.
library(reshape2)
df = read.table(text = "id A B
1 1 -0.19933093 -0.10074686
2 2 -1.19043346 0.72451483
3 3 -1.32248172 -0.40914044
4 4 -1.98644507 0.02913376
5 5 -0.07930953 0.16062491", sep = "", header = TRUE)
df
df.melt = melt(df, "id")
df.melt
df.original = dcast(df.melt, id~variable)
df.original
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.
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)