Reputation: 351
I'm having trouble stacking columns in a data.frame into one column. Now my data looks something like this:
id time black white red
a 1 b1 w1 r1
a 2 b2 w2 r2
a 3 b3 w3 r3
b 1 b4 w4 r4
b 2 b5 w5 r5
b 3 b6 w6 r6
I'm trying to transform the data.frame so that it looks like this:
id time colour
a 1 b1
a 2 b2
a 3 b3
b 1 b4
b 2 b5
b 3 b6
a 1 w1
a 2 w2
a 3 w3
b 1 w4
b 2 w5
b 3 w6
a 1 r1
a 2 r2
. . .
. . .
. . .
I'm guessing that this problem requires using the reshape package, but I'm not exactly sure how to use it to stack multiple columns under one column. Can anyone provide help on this?
Upvotes: 14
Views: 26437
Reputation: 193687
Since you mention "stacking" in your title, you can also look at the stack
function in base R:
cbind(mydf[1:2], stack(mydf[3:5]))
# id time values ind
# 1 a 1 b1 black
# 2 a 2 b2 black
# 3 a 3 b3 black
# 4 b 1 b4 black
# 5 b 2 b5 black
# 6 b 3 b6 black
# 7 a 1 w1 white
# 8 a 2 w2 white
# 9 a 3 w3 white
# 10 b 1 w4 white
# 11 b 2 w5 white
# 12 b 3 w6 white
# 13 a 1 r1 red
# 14 a 2 r2 red
# 15 a 3 r3 red
# 16 b 1 r4 red
# 17 b 2 r5 red
# 18 b 3 r6 red
If the values in the "black", "white", and "red" columns are factor
s, you'll need to convert them to character
values first.
cbind(mydf[1:2], stack(lapply(mydf[3:5], as.character)))
Upvotes: 10
Reputation: 42689
Here's melt from reshape:
library(reshape)
melt(x, id.vars=c('id', 'time'),var='color')
And using reshape2
(an up-to-date, faster version of reshape
) the syntax is almost identical.
The help files have useful examples (see ?melt
and the link to melt.data.frame
).
In your case, something like the following will work (assuming your data.frame is called DF
)
library(reshape2)
melt(DF, id.var = c('id','time'), variable.name = 'colour')
Upvotes: 13