Thanks a lot Achim!
This helped a lot. I do not have exactly what I want yet, but I now have
promising ideas to gather my data and find what I'm looking for (especially
as.numeric(x,
units = "hours")).
Regards,
Sartene Bel
> Message du 31/10/13 à 08h48
> De : "Achim Zeileis"
> A : sart...@voila.fr
> Copie à : r-help@r-project.org
> Objet : Re: [R] Irregular time series frequencies
>
> On Wed, 30 Oct 2013, sart...@voila.fr wrote:
>
> > Hi everyone,
> >
> > I have a data frame with email addresses in the first column and in the
> > second column a list of times (of different lengths) at which an email was
> > sent from
the
> > user in the first column.
> >
> > Here is an example of my data:
> >
> > Email Email_sent
> > j...@doe.com "2013-09-26 15:59:55" "2013-09-27 09:48:29" "2013-09-27
> > 10:00:02" "2013-09-27 10:12:54"
> > j...@shoe.com "2013-09-26 09:50:28" "2013-09-26 14:41:24" "2013-09-26
> > 14:51:36" "2013-09-26 17:50:10" "2013-09-27 13:34:02" "2013-09-27 14:41:10"
> > "2013-09-27 15:37:36"
> > ...
> >
> > I cannot find any way to calculate the frequencies between each email sent
> > for each user:
> > j...@doe.com 0.02 email / hour
> > j...@shoe.com 0.15 email / hour
> > ...
> >
> > Can anyone help me on this problem?
>
> You could do something like this:
>
> ## scan your data file
> d <- scan(, what = "character")
>
> ## here I use the data from above
> d <- scan(textConnection('j...@doe.com "2013-09-26 15:59:55"
> "2013-09-27 09:48:29" "2013-09-27 10:00:02" "2013-09-27 10:12:54"
> j...@shoe.com "2013-09-26 09:50:28" "2013-09-26 14:41:24"
> "2013-09-26 14:51:36" "2013-09-26 17:50:10" "2013-09-27 13:34:02"
> "2013-09-27 14:41:10" "2013-09-27 15:37:36"'), what = "character")
>
> ## find position of e-mail addresses
> n <- grep("@", dc, fixed = TRUE)
>
> ## extract list of dates
> n <- c(n, length(d) + 1)
> x <- lapply(1:(length(n) - 1),
> function(i) as.POSIXct(d[(n[i] + 1):(n[i+1] - 1)]))
>
> ## add e-mail addresses as names
> names(x) <- d[head(n, -1)]
>
> ## functions that could extract quantities of interest such as
> ## number of mails per hour or mean time difference etc.
> meantime <- function(timevec)
> mean(as.numeric(diff(timevec), units = "hours"))
> numperhour <- function(timevec)
> length(timevec) / as.numeric(diff(range(timevec)), units = "hours")
>
> ## apply to full list
> sapply(x, numperhour)
> sapply(x, meantime)
>
> ## apply to list by date
> sapply(x, function(timevec) tapply(timevec, as.Date(timevec), numperhour))
> sapply(x, function(timevec) tapply(timevec, as.Date(timevec), meantime))
>
> hth,
> Z
>
> > The ultimate goal (which seems amibitious at this time) is to calculate,
> > for each user, the frequencies between each mail per day, between the first
> > email sent
> > and the last email sent each day (to avoid taking nights into account),
> > i.e.:
> >
> > 2013-09-26 2013-09-27
> > j...@doe.com 1.32 emails / hour 0.56 emails / hour
> > j...@shoe.com 10.57 emails / hour 2.54 emails / hour
> > ...
> >
> > At this time it seems pretty impossible, but I guess I will eventually find
> > a way :-)
> >
> > Thanks a lot,
> >
> >
> > Sartene Bel
> > R learner
> > ___________________________________________________________
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> >
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