luffe - 1 month ago 11

R Question

I know

`reshape`

`A`

`B`

`wide = data.frame(A.2010 = c('a', 'b', 'c'),`

A.2011 = c('f', 'g', 'd'),

B.2010 = c('A', 'B', 'C'),

B.2011 = c('G', 'G', 'H'),

z = runif(3),

x = runif(3))

wide

# A.2010 A.2011 B.2010 B.2011 z x

#1 a f A G 0.3626823 0.67212468

#2 b g B G 0.3726911 0.09663248

#3 c d C H 0.9807237 0.31259394

Becomes:

`reshape(wide, direction = 'long', sep = '.',`

varying = c('A.2010', 'A.2011', 'B.2010', 'B.2011'))

# z x time A B id

#1.2010 0.3626823 0.67212468 2010 a A 1

#2.2010 0.3726911 0.09663248 2010 b B 2

#3.2010 0.9807237 0.31259394 2010 c C 3

#1.2011 0.3626823 0.67212468 2011 f G 1

#2.2011 0.3726911 0.09663248 2011 g G 2

#3.2011 0.9807237 0.31259394 2011 d H 3

Can I accomplish the same with

`reshape2::melt`

Answer

It seems like `reshape`

in base r is the best tool to do this, since there is no similar functionality in the `melt`

function from the `reshape`

package. You can however, achieve something similar with the `patterns`

function in `melt.data.table`

:

```
library(reshape2)
library(data.table)
wide = data.table(wide)
long = melt(wide, id.vars = c("z", "x"), measure = patterns("^A", "^B"),
value.name = c("A", "B"), variable.name = "time")
> long
z x time A B
1: 0.3421681 0.8432707 1 a A
2: 0.1243282 0.5096108 1 b B
3: 0.3650165 0.1441660 1 c C
4: 0.3421681 0.8432707 2 f G
5: 0.1243282 0.5096108 2 g G
6: 0.3650165 0.1441660 2 d H
```

Notice that `melt`

recognizes the varying "time", and groups them correctly, but does not use 2010 and 2011 as desired. A workaround is to recode the levels manually, which should be trivial.

```
levels(long$time) = c("2010", "2011")
> long
z x time A B
1: 0.3421681 0.8432707 2010 a A
2: 0.1243282 0.5096108 2010 b B
3: 0.3650165 0.1441660 2010 c C
4: 0.3421681 0.8432707 2011 f G
5: 0.1243282 0.5096108 2011 g G
6: 0.3650165 0.1441660 2011 d H
```

I hope this helps!