Counting non-empty levels of a factor

On Nov 8, 2009, at 8:38 AM, sylvain willart wrote:

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.
Which may not have been what you asked for as this would demonstrate.  
You probably wnat the second solution:
mydata2 <- rbind(MyData, MyData)
 > result <- aggregate(mydata2$brand , by=list(mydata2$store) , length)
 > result
   Group.1 x
1       1 6
2       2 4
3       3 6

 > result <- aggregate(mydata2$brand , by=list(mydata2$store) ,  
function(x) nlevels(factor(x)))
 > result
   Group.1 x
1       1 3
2       2 2
3       3 3
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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