search for: provinciales

...variable puntual veo que las etiquetas de las variables "están" pero la clase del vector no me cierra y los resultados no los usan. Trato de mostrarlo: > na.omit(datos[, .(FORM, Region, Dependencia = B2a, Criterios = D4_Otros.1)]) FORM Region Dependencia Criterios 1: 44 NEA Provinciales 8 2: 47 NEA Provinciales 8 3: 51 NEA Provinciales 8 4: 52 NEA Provinciales 8 5: 58 NEA Provinciales 8 6: 222 NOA Municipales 11 7: 231 NOA Provinciales 12 8: 232 NOA Religiosos 11 9: 235 NOA...

...pero, no puedo hacer que las tablas se llamen como quisiera porque el factor "etiqueta" que debería indicar el primer nombre de la variable no es consdierado, como podrán ver. ?Si correo el código para la variable, resulta algo como: > tabla Sexo N Porc PorcAc NEA NOA Nacionales Provinciales Municipales Comunitarios Religiosos Privados 1 Mujer 270 86.8 86.8 92.7 84.2 77.8 89.6 83.8 78.9 90 100 2 Varon 40 12.9 99.7 7.3 15.3 22.2 10.4 16.2 19.3 10 NA 3 <NA> 1 0.3 100.0 NA 0.5 NA...

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

Dear Massimo, It seems straightforward to use weighted.mean() in a dplyr context library(dplyr) mydf %>% group_by(date_time, type) %>% summarise(vel = weighted.mean(speed, n_vehicles)) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team

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 =

hi thierry thanks for your reply yes, you are right, your solution is more straightforward best Da: "Thierry Onkelinx" <thierry.onkelinx at inbo.be> A: "Massimo Bressan" <massimo.bressan at arpa.veneto.it> Cc: "r-help" <r-help at r-project.org> Inviato: Gioved?, 9 novembre 2017 15:17:31 Oggetto: Re: [R] weighted average grouped by

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...pero, no puedo hacer que las tablas se llamen como quisiera porque el factor "etiqueta" que debería indicar el primer nombre de la variable no es consdierado, como podrán ver. ?Si correo el código para la variable, resulta algo como: > tabla    Sexo   N Porc PorcAc  NEA  NOA Nacionales Provinciales Municipales Comunitarios Religiosos Privados 1 Mujer 270 86.8   86.8 92.7 84.2       77.8         89.6        83.8         78.9         90      100 2 Varon  40 12.9   99.7  7.3 15.3       22.2         10.4        16.2         19.3         10       NA 3  <NA>   1  0.3  100.0   NA  0.5        ...

Hello, Try the following. icol <- which(grepl("flag", names(mydf))) mydf[icol] <- lapply(mydf[icol], function(x){ is.na(x) <- x == 0 x }) mydf # A A_flag B B_flag #1 8 10 5 12 #2 7 NA 6 9 #3 10 1 2 NA #4 1 NA 1 5 #5 5 2 0 NA Hope this helps, Rui Barradas On 11/22/2017 10:34 AM, Massimo Bressan

...well, I don't think this is exactly the expected result (see my post) to be noted that the columns affected should be "A" and "B" thanks for the help max ----- Messaggio originale ----- Da: "Rui Barradas" <ruipbarradas at sapo.pt> A: "Massimo Bressan" <massimo.bressan at arpa.veneto.it>, "r-help" <r-help at

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

> 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

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De aqui: http://resultadosgenerales2015.interior.es/congreso/#/ES201512-CON-ES/ES o en json: http://resultadosgenerales2015.interior.es/#/herramienta-analisis?siteLanguage=es_ES dentro del linux estan los archivos El 28 de diciembre de 2015, 16:30, Javier Marcuzzi < javier.ruben.marcuzzi en gmail.com> escribió: > Estimado Ivan Aguilar > > Desconozco desde donde toma los datos,

Given this data frame (a simplified, essential reproducible example) A<-c(8,7,10,1,5) A_flag<-c(10,0,1,0,2) B<-c(5,6,2,1,0) B_flag<-c(12,9,0,5,0) mydf<-data.frame(A, A_flag, B, B_flag) # this is my initial df mydf I want to get to this final situation i<-which(mydf$A_flag==0) mydf$A[i]<-NA ii<-which(mydf$B_flag==0) mydf$B[ii]<-NA

Hi, I really did my best to understand how I can help improving Wine, but I did not succed. Well, everything started when I installed a win application on my Debian 3.1, Wine 2004.07.16 deb (clean install, no dlls). The application is ALOHA (http://www.epa.gov/ceppo/cameo/aloha.htm) It's a free application from US-Environment Protection Agency used for chemical emergency planning (I am an

Hello, this is a problem: We have a debian server 2.2 with kernel 2.4.18 and samba 2.2.4 works as Domain Controler. After joing a Domain we read at property administrator of the local group Administrators of win2000 this: Administrator \"Domain"\unix_group.2147483404 rather than Administrator \"Domain"\Domain Admins If we tryng to adding the global group Domain Admins we