Counting non-empty levels of a factor

Hi everyone,

I'm struggling with a little problem for a while, and I'm wondering if
anyone could help...

I have a dataset (from retailing industry) that indicates which brands
are present in a panel of 500 stores,

store , brand
1 , B1
1 , B2
1 , B3
2 , B1
2 , B3
3 , B2
3 , B3
3 , B4

I would like to know how many brands are present in each store,

I tried:
result <- aggregate(MyData$brand , by=list(MyData$store) , nlevels)

but I got:
Group.1 x
1 , 4
2 , 4
3 , 4

which is not exactly the result I expected
I would like to get sthg like:
Group.1 x
1 , 3
2 , 2
3 , 3
Try:

result <- aggregate(MyData$brand , by=list(MyData$store) , length)

Quick, easy and generalizes to other situations. The factor levels got  
carried along identically, but length counts the number of elements in  
the list returned by tapply.
Looking around, I found I can delete empty levels of factor using:
problem.factor <- problem.factor[,drop=TRUE]
If you reapply the function, factor, you get the same result. So you  
could have done this:

 > result <- aggregate(MyData$brand , by=list(MyData$store) ,  
function(x) nlevels(factor(x)))
 > result
   Group.1 x
1       1 3
2       2 2
3       3 3
But this solution isn't handy for me as I have many stores and should
make a subset of my data for each store before dropping empty factor

I can't either counting the line for each store (N), because the same
brand can appear several times in each store (several products for the
same brand, and/or several weeks of observation)

I used to do this calculation using SAS with:
proc freq data = MyData noprint ; by store ;
tables  brand / out = result ;
run ;
(the cool thing was I got a database I can merge with MyData)

any idea for doing that in R ?

Thanks in advance,

King Regards,

Sylvain Willart,
PhD Marketing,
IAE Lille, France

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Counting non-empty levels of a factor

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