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 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. 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