Hello

Use something like this:

res.dat<-split(yourTable[,c(2,3)], group=yourTable$firstColum)

That will generate a list grouped by the firstColum.
To get means, or whatever you need you will have to use any of the list
functions "apply", "sapply", etc.

Regards,
Carlos.
P.S:
- yourTable: It is the name of your table or data.frame.
- firstColum: It is the name of the first column of your table, data.frame.



On 2/17/06, Prasanna BALAPRAKASH <prasannaprakash@gmail.com> wrote:
>
> Dear Rs
>
> I have a single table with three columns in the following form:
>
> 1       100     150
> 1       45      32
> 1       99      100
> 2       150     33
> 2       22      87
> 2       71      31
> ....
> ....
> 1000    64      32
> 1       100     150
> 1       45      32
> 1       99      100
> 2       22      89
> 2       31      44
> 2       88      11
> ....
> ....
> 1200    64      32
> 1       100     150
> 1       45      32
> 1       99      100
> 2       150     33
> 2       22      87
> 2       71      31
> ...
> ...
> 1100    31      34
>
> Totally 1000+1200+1100 rows.  Now, I need to group by first column
> and average then second and third column to get a table as follows as
> follows:
>
> 1       Avg. of all second col. values whose first col value is 1
> Avg. of
> all third col. values whose first col value is 1
> 2       Avg. of all second col. values whose first col value is 2
> Avg. of
> all third col. values whose first col value is 2
> ..
> ..
> 1200    Avg. of all second col. values whose first col value is 1200
> Avg. of all third col. values whose first col value is 1200
>
>
> Right now, I have a dirty implementation with a lot of "for" loops
> and "if" conditions. However, I am looking for some built in
> functions and lib. to make the code faster and easier.
>
>
> Thanks
> Prasanna
>
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