Hadley's reshape package (google for it) can
do this. There's a nice intro on the site.
> library(reshape)
> cast(melt(mydf, measure.vars = "value"), city ~ brand,
fun.aggregate = sum)
city x y z
1 a 3 23 450
2 b 12 42 231
Although the numbers differ slightly?
I've heard of the reshape2 package, but have no idea
if that's replaced the reshape package yet.
--Erik
Dimitri Liakhovitski wrote:
Hello!
I have a data frame like this one:
mydf<-data.frame(city=c("a","a","a","a","a","a","a","a","b","b","b","b","b","b","b","b"),
brand=c("x","x","y","y","z","z","z","z","x","x","x","y","y","y","z","z"),
value=c(1,2,11,12,111,112,113,114,3,4,5,13,14,15,115,116))
(mydf)
What I need to get is a data frame like the one below - cities as
rows, brands as columns, and the sums of the "value" within each
city/brand combination in the body of the data frame:
city x y z
a 3 23 336
b 7 42 231
I have written a code that involves multiple loops and subindexing -
but it's taking too long.
I am sure there must be a more efficient way of doing it.
Thanks a lot for your hints!
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