[R] avoiding too many loops - reshaping data

[Erik Iverson]

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!
> 
>