[R-SIG-Finance] Aggregating Statistics By Time Interval

Gabor Grothendieck ggrothendieck at gmail.com
Wed Aug 1 15:16:24 CEST 2007

Something similar was just discussed this morning:

On 8/1/07, Rory Winston <rory.winston at gmail.com> wrote:
> Hi all
> I have a question about aggegating statistics by time intervals. I have a
> data set with 3 columns : time, bid, and ask. Time is specified as a
> millisecond timestamp since epoch. I would like to compute summary
> statistics for the data set on an hourly basis. Here is what I have tried so
> far:
> # Data is in pricedata
> t <- ISODatetime(1970, 1, 1, 0, 0, 0) + pricedata$time
> agg <- aggregate(pricedata$spread, list(byhour=format(t, "%Y-%m %H")), mean)
> This seems to do what I want - however, what really want to do is more
> specific: I would like to be able to extract a subset of the data frame
> pricedata, and not just the aggregated entries - for instance, instead of
> just extracting pricedata$spread by hour, I would like to extract a slice of
> columns, e.g. pricedata$spread and pricedata$time on an hourly basis, and
> pass these into a function that can compute a time-weighted average spread,
> for instance. Does anyone know an elegant way to do this? I have a feeling
> zoo may do what I want, but I'm new to zoo ...
> Cheers
> Rory
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