Hi Berend Yes you are correct. My fault, I did not test it before sending.
Cheers Petr > -----Original Message----- > From: Berend Hasselman [mailto:b...@xs4all.nl] > Sent: Saturday, November 11, 2017 11:26 AM > To: PIKAL Petr <petr.pi...@precheza.cz> > Cc: Massimo Bressan <massimo.bres...@arpa.veneto.it>; r-help <r-help@r- > project.org> > Subject: Re: [R] weighted average grouped by variables > > > > On 9 Nov 2017, at 14:58, PIKAL Petr <petr.pi...@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)$x gives you sums > > > > Cheers > > Petr > > > >> -----Original Message----- > >> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of > >> Massimo Bressan > >> Sent: Thursday, November 9, 2017 2:17 PM > >> To: r-help <r-help@r-project.org> > >> Subject: Re: [R] weighted average grouped by variables > >> > >> Hello > >> > >> an update about my question: I worked out the following solution > >> (with the package "dplyr") > >> > >> library(dplyr) > >> > >> mydf%>% > >> mutate(speed_vehicles=n_vehicles*mydf$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.bres...@arpa.veneto.it> > >> A: "r-help" <r-help@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.bres...@arpa.veneto.it > >> ------------------------------------------------------------ > >> > >> > >> [[alternative HTML version deleted]] > >> > >> ______________________________________________ > >> R-help@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. > > > > ________________________________ > > Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou > určeny pouze jeho adresátům. > > Jestliže jste obdržel(a) tento e-mail omylem, informujte laskavě neprodleně > jeho odesílatele. 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