[R] weighted average grouped by variables

Mon Nov 13 07:51:12 CET 2017

Hi Berend

Yes you are correct. My fault, I did not test it before sending.

Cheers
Petr

> -----Original Message-----
> From: Berend Hasselman [mailto:bhh at xs4all.nl]
> Sent: Saturday, November 11, 2017 11:26 AM
> To: PIKAL Petr <petr.pikal at precheza.cz>
> Cc: Massimo Bressan <massimo.bressan at arpa.veneto.it>; r-help <r-help at r-
> project.org>
> Subject: Re: [R] weighted average grouped by variables
>
>
> > On 9 Nov 2017, at 14:58, PIKAL Petr <petr.pikal at precheza.cz> wrote:
> >
> > Hi
> >
> > Thanks for working example.
> >
> > you could use split/ lapply approach, however it is probably not much better
> than dplyr method.
> >
> > sapply(split(mydf, mydf$type), function(speed, n_vehicles)
> > sum(mydf$speed*mydf$n_vehicles)/sum(mydf$n_vehicles))
> > gives you averages
> >
>
> The result of this calculation is:
>
>      car light_duty heavy_duty motorcycle
>   36.54109   36.54109   36.54109   36.54109
>
> But this doesn't give the same result as the dplyr method which is:
>
>             date_time       type      vel
>                <dttm>     <fctr>    <dbl>
> 1 2017-10-17 13:00:00        car 36.39029
> 2 2017-10-17 13:00:00 light_duty 38.56522
> 3 2017-10-17 13:00:00 heavy_duty 37.53333
> 4 2017-10-17 13:00:00 motorcycle 36.08696
>
> The base R way of getting the result should be modified slightly into
>
> sapply(split(mydf, mydf$type), function(Z)
> sum(Z$speed*Z$n_vehicles)/sum(Z$n_vehicles))
>
> Calculations are done on the elements of the list provided by split.
> The result now is:
>
>       car light_duty heavy_duty motorcycle
>   36.39029   38.56522   37.53333   36.08696
>
> Obviously now the same as the dplyr method.
>
> Berend Hasselman
>
> > aggregate(mydf$n_vehicles, list(mydf$type), sum)$x gives you sums
> >
> > Cheers
> > Petr
> >
> >> -----Original Message-----
> >> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of
> >> Massimo Bressan
> >> Sent: Thursday, November 9, 2017 2:17 PM
> >> To: r-help <r-help at r-project.org>
> >> Subject: Re: [R] weighted average grouped by variables
> >>
> >> Hello
> >>
> >> an update about my question: I worked out the following solution
> >> (with the package "dplyr")
> >>
> >> library(dplyr)
> >>
> >> mydf%>%
> >> mutate(speed_vehicles=n_vehicles*mydf$speed) %>%
> >> group_by(date_time,type) %>%
> >> summarise(
> >> sum_n_times_speed=sum(speed_vehicles),
> >> n_vehicles=sum(n_vehicles),
> >> vel=sum(speed_vehicles)/sum(n_vehicles)
> >> )
> >>
> >>
> >> In fact I was hoping to manage everything in a "one-go": i.e. without
> >> the need to create the "intermediate" variable called
> >> "speed_vehicles" and with the use of the function weighted.mean()
> >>
> >> any hints for a different approach much appreciated
> >>
> >> thanks
> >>
> >>
> >>
> >> Da: "Massimo Bressan" <massimo.bressan at arpa.veneto.it>
> >> A: "r-help" <r-help at r-project.org>
> >> Inviato: Giovedì, 9 novembre 2017 12:20:52
> >> Oggetto: weighted average grouped by variables
> >>
> >> hi all
> >>
> >> I have this dataframe (created as a reproducible example)
> >>
> >> mydf<-structure(list(date_time = structure(c(1508238000, 1508238000,
> >> 1508238000, 1508238000, 1508238000, 1508238000, 1508238000), class =
> >> c("POSIXct", "POSIXt"), tzone = ""), direction = structure(c(1L, 1L,
> >> 1L, 1L, 2L, 2L, 2L), .Label = c("A", "B"), class = "factor"), type =
> >> structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L), .Label = c("car",
> >> "light_duty", "heavy_duty", "motorcycle"), class = "factor"),
> >> avg_speed = c(41.1029082774049, 40.3333333333333, 40.3157894736842,
> >> 36.0869565217391, 33.4065155807365, 37.6222222222222, 35.5),
> >> n_vehicles = c(447L, 24L, 19L, 23L, 706L, 45L, 26L)), .Names =
> >> c("date_time", "direction", "type", "speed", "n_vehicles"), row.names
> >> = c(NA, -7L), class = "data.frame")
> >>
> >> mydf
> >>
> >> and I need to get to this final result
> >>
> >> mydf_final<-structure(list(date_time = structure(c(1508238000,
> >> 1508238000, 1508238000, 1508238000), class = c("POSIXct", "POSIXt"),
> >> tzone = ""), type = structure(c(1L, 2L, 3L, 4L), .Label = c("car",
> >> "light_duty", "heavy_duty", "motorcycle"), class = "factor"),
> >> weighted_avg_speed = c(36.39029, 38.56521, 37.53333, 36.08696),
> >> n_vehicles = c(1153L,69L,45L,23L)), .Names = c("date_time", "type",
> >> "weighted_avg_speed", "n_vehicles"), row.names = c(NA, -4L), class =
> >> "data.frame")
> >>
> >> mydf_final
> >>
> >>
> >> my question:
> >> how to compute a weighted mean i.e. "weighted_avg_speed"
> >> from "speed" (the values whose weighted mean is to be computed) and
> >> "n_vehicles" (the weights) grouped by "date_time" and "type"?
> >>
> >> to be noted the complication of the case "motorcycle" (not present in
> >> both
> >> directions)
> >>
> >> any help for that?
> >>
> >> thank you
> >>
> >> max
> >>
> >>
> >>
> >> --
> >>
> >> ------------------------------------------------------------
> >> Massimo Bressan
> >>
> >> ARPAV
> >> Agenzia Regionale per la Prevenzione e Protezione Ambientale del
> >> Veneto
> >>
> >> Dipartimento Provinciale di Treviso
> >> Via Santa Barbara, 5/a
> >> 31100 Treviso, Italy
> >>
> >> tel: +39 0422 558545
> >> fax: +39 0422 558516
> >> e-mail: massimo.bressan at arpa.veneto.it
> >> ------------------------------------------------------------
> >>
> >>
> >>      [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> >> http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >
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- a obsahuje-li nabídku, je adresát oprávněn nabídku bezodkladně přijmout; Odesílatel tohoto e-mailu (nabídky) vylučuje přijetí nabídky ze strany příjemce s dodatkem či odchylkou.
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