I am having trouble figuring out the most elegant and flexible way to switch data from long format to wide format when I have more than one measure variable I want to bring along.
For example, here's a simple data frame in long format. ID
is the subject, TIME
is a time variable, and X
and Y
are measurements made of ID
at TIME
:
> my.df <- data.frame(ID=rep(c("A","B","C"), 5), TIME=rep(1:5, each=3), X=1:15, Y=16:30)
> my.df
ID TIME X Y
1 A 1 1 16
2 B 1 2 17
3 C 1 3 18
4 A 2 4 19
5 B 2 5 20
6 C 2 6 21
7 A 3 7 22
8 B 3 8 23
9 C 3 9 24
10 A 4 10 25
11 B 4 11 26
12 C 4 12 27
13 A 5 13 28
14 B 5 14 29
15 C 5 15 30
If I just wanted to turn the values of TIME
into column headers containing the include X
, I know I can use cast()
from the reshape
package (or dcast()
from reshape2
):
> cast(my.df, ID ~ TIME, value="X")
ID 1 2 3 4 5
1 A 1 4 7 10 13
2 B 2 5 8 11 14
3 C 3 6 9 12 15
But what I really want to do is also bring along Y
as another measure variable, and have the column names reflect both the measure variable name and the time value:
ID X_1 X_2 X_3 X_4 X_5 Y_1 Y_2 Y_3 Y_4 Y_5
1 A 1 4 7 10 13 16 19 22 25 28
2 B 2 5 8 11 14 17 20 23 26 29
3 C 3 6 9 12 15 18 21 24 27 30
(FWIW, I don't really care if all the X
's are first followed by the Y
's, or if they are interleaved as X_1
, Y_1
, X_2
, Y_2
, etc.)
I can get close to this by cast-ing the long data twice and merging the results, though the column names need some work, and I would need to tweak it if I needed to add a 3rd or 4th variable in addition to X
and Y
:
merge(
cast(my.df, ID ~ TIME, value="X"),
cast(my.df, ID ~ TIME, value="Y"),
by="ID", suffixes=c("_X","_Y")
)
Seems like some combination of functions in reshape2
and/or plyr
should be able to do this more elegantly that my attempt, as well as handling multiple measure variables more cleanly. Something like cast(my.df, ID ~ TIME, value=c("X","Y"))
, which isn't valid. But I haven't been able to figure it out.
reshape(my.df,
idvar = "ID",
timevar = "TIME",
direction = "wide")
gives
ID X.1 Y.1 X.2 Y.2 X.3 Y.3 X.4 Y.4 X.5 Y.5
1 A 1 16 4 19 7 22 10 25 13 28
2 B 2 17 5 20 8 23 11 26 14 29
3 C 3 18 6 21 9 24 12 27 15 30