Here is one way to do it using data.table package:
> x <- read.table(textConnection("NAME TICKER SHARES PERFORMANCE
+ John ABC 100 0.05
+ John ABC 1000 1.5
+ Alice EFG 20 0.3
+ Paul HIJ 50 1.0
+ Paul JKL 60 2.0
+ Paul MNO 12 3.0"), header = TRUE, as.is = TRUE)
> closeAllConnections()
> require(data.table)
> x <- data.table(x) # convert to data.table
> x[
+ , list(SHARES = sum(SHARES)
+ , PERFORMANCE = sum(SHARES * PERFORMANCE) / sum(SHARES)
+ )
+ , by = list(NAME, TICKER)
+ ]
NAME TICKER SHARES PERFORMANCE
[1,] John ABC 1100 1.368182
[2,] Alice EFG 20 0.300000
[3,] Paul HIJ 50 1.000000
[4,] Paul JKL 60 2.000000
[5,] Paul MNO 12 3.000000
>
On Fri, Oct 7, 2011 at 8:53 AM, PHILIP GLADWIN, BLOOMBERG TRADEBOOK:
<pgladw...@bloomberg.net> wrote:
> Hello,
> Could anybody help me with this question?
>
> Example data frame
> NAME TICKER SHARES PERFORMANCE
> John ABC 100 0.05
> John ABC 1000 1.5
> Alice EFG 20 0.3
> Paul HIJ 50 1.0
> Paul JKL 60 2.0
> Paul MNO 12 3.0
>
>
> I would like to aggregate this dataframe by NAME, TICKER, and SHARES and to
> perform a weighted mean. I expect the output to be
> NAME TICKER SHARES PERFORMANCE
> John ABC 1000+100 ( (100 * 0.05) + (1000 * 1.5) ) / (100 + 1000)
> Alice EFG 20 0.3
> Paul HIJ 50 1.0
> Paul JKL 60 2.0
> Paul MNO 12 3.0
>
> and I would like the output to be in a data frame.
>
> Can anybody help?
> Thank you,
> Phil,
>
> -------------------------------------------------------------------------------
> This e-mail is communicated by Bloomberg Tradebook Europe Limited a company
> registered in England & Wales No. 3556095 whose regis...{{dropped:23}}
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