Hi, folks,

I am sorry that I did not state the problem correctly yesterday.

Please let me address the problem by the following codes:

first=c('u','b','e','k','j','c','u','f','c','e')
second=c('usa','Brazil','England','Korea','Japan','China','usa','France','China','England')
third=1:10
data=data.frame(first,second,third)

## You may understand values in the first column are the unique codes for
those in the second column.
####So 'u' is only for usa. Replicate values appear the same rows for the
first and second columns.
### Now I want to delete replicate rows with the same values in first
(sceond) rows
####and sum up values in the third column for the same values.

mm=melt(data,id='first')
sum=cast(mm,first~variable,sum) ### This does not work.

###I tried another way to do this
mm= melt(data, id='first',measure='third')
sum=cast(mm,first~variable,sum)

## But then the problem is how to 'merge' the result with the second column
in the dataset.


The expected dataframe is like this:

(I showed a wrong expected dataframe yesterday.)

     first   second  third
1      u     usa      8
2      b   Brazil     2
3      e  England   13
4      k   Korea     4
5      j   Japan      5
6      c   China     15
8      f  France     8

Thanks in advance.

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