[R-SIG-Finance] Aggregating tick-by-tick data to seconds

[G See]

You can use `period.apply` (along with `endpoints()`) to apply any
function you like over non-overlapping time periods.

In this case, you want to sum columns 2 and 3 separately, so use
`period.apply()` with `FUN=colSums` on just the 2nd and 3rd columns.

    period.apply(test[, 2:3], endpoints(test, 'secs'), FUN=colSums)

Then you can merge that with the results of `to.period`

    > cbind(to.period(test[, 1], name="test"), period.apply(test[,
-1], endpoints(test, 'secs'), FUN=colSums))
                                test.Open test.High test.Low
test.Close   up down
    2012-09-12 16:30:00    144.39    144.39   144.38     144.38 5903  100

You could also use `period.sum()` on each column separately.

HTH,
Garrett

On Sat, Sep 15, 2012 at 10:57 AM, Costas Vorlow <costas.vorlow at gmail.com> wrote:
> Hello,
>
> I have the following data (xts) (last two columns refer to up and down
> volumes).
>
>> head(test,20)
>                       [,1] [,2] [,3]
> 2012-09-12 16:30:00 144.39  300    0
> 2012-09-12 16:30:00 144.39  500    0
> 2012-09-12 16:30:00 144.39  300    0
> 2012-09-12 16:30:00 144.39  400    0
> 2012-09-12 16:30:00 144.39  300    0
> 2012-09-12 16:30:00 144.39  300    0
> 2012-09-12 16:30:00 144.39  100    0
> 2012-09-12 16:30:00 144.39  900    0
> 2012-09-12 16:30:00 144.39  200    0
> 2012-09-12 16:30:00 144.39  103    0
> 2012-09-12 16:30:00 144.39  197    0
> 2012-09-12 16:30:00 144.39  200    0
> 2012-09-12 16:30:00 144.39  500    0
> 2012-09-12 16:30:00 144.39  400    0
> 2012-09-12 16:30:00 144.39  100    0
> 2012-09-12 16:30:00 144.39  500    0
> 2012-09-12 16:30:00 144.39  300    0
> 2012-09-12 16:30:00 144.39  200    0
> 2012-09-12 16:30:00 144.39  103    0
> 2012-09-12 16:30:00 144.38    0  100
>
>
> I can use the to.period to aggregate the above data to seconds
>
>                     test.Open test.High test.Low test.Close
> 2012-09-12 16:30:00    144.39    144.47   144.37     144.38
> 2012-09-12 16:31:00    144.39    144.40   144.33     144.37
> 2012-09-12 16:32:00    144.37    144.45   144.37     144.45
> 2012-09-12 16:33:00    144.45    144.47   144.42     144.47
>
>
>  but I am not sure how to do this for the volume columns. I would need to
> retrieve the volume sums per second.
>
> Is this functionality built into the xts package? Is there any other
> function that could be used to do something like that?
>
> Thanks & best regards,
> Costas
> _______________
>
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