Ok, gracias!! > From: [email protected] > To: [email protected] > Date: Wed, 28 Oct 2015 10:00:02 +0100 > Subject: Re: [R-es] pregunta > > Hola Jesús, > > Usando la función by, prueba con > > by(datos$Gain, datos$Diet, mean, na.rm=T) > > para obviar los NA y con > > by(datos$Gain, datos$Diet, function(x) sum(is.na(x))) > > para contar los missings en cada categoría. > > Puedes sustituir la función by también por la función tapply. > > Klaus. > > > On 28/10/2015 9:07, Jesús Para Fernández wrote: > > > > > > > > Me gusta la respuesta uqe has dado, pero si por ejemplo, alguno de los > > datos tiene datos faltantes, entonces devuelve NA. > > > > He probado con: > > sapply(split(datos$uno, as.factor(datos$dos)), mean(na.rm=TRUE)) > > > > pero da fallo. > > > > ¿Cómo se podría hacer para que devolviera además la media obviando los NA y > > que contara el numero de NA por categoria? > > > >> Date: Wed, 28 Oct 2015 00:13:45 +0100 > >> From: [email protected] > >> To: [email protected] > >> CC: [email protected] > >> Subject: Re: [R-es] pregunta > >> > >> Otras variantes con y sin paquetes adicionales... > >> > >>> sapply(split(datIn$Gain, as.factor(datIn$Diet)), mean) > >> d1 d2 d3 > >> 280 278 312 > >>> by(datIn$Gain, datIn$Diet, mean) > >> datIn$Diet: d1 > >> [1] 280 > >> -------------------------------------------------------------- > >> datIn$Diet: d2 > >> [1] 278 > >> -------------------------------------------------------------- > >> datIn$Diet: d3 > >> [1] 312 > >>> library(dplyr) > >>> summarise(group_by(datIn, Diet), mean(Gain)) > >> Source: local data frame [3 x 2] > >> > >> Diet mean(Gain) > >> (chr) (dbl) > >> 1 d1 280 > >> 2 d2 278 > >> 3 d3 312 > >>> library(sqldf) > >>> sqldf("select Diet,avg(Gain) from datIn group by Diet") > >> Diet avg(Gain) > >> 1 d1 280 > >> 2 d2 278 > >> 3 d3 312 > >> > >> > >> Saludos, > >> Carlos Ortega > >> www.qualityexcellence.es > >> > >> 2015-10-27 22:45 GMT+01:00 eric <[email protected]>: > >> > >>> tambien te sirve la funcion data.table ... si no tienes instalado el > >>> paquete: > >>> > >>> install.packages("data.table") > >>> library(data.table) > >>> jbe <- as.data.table(read.table("tusdatos.txt")) > >>> jbe.ave <- jbe[, .("ave"=mean(Gain)), by=.(Diet)] > >>> > >>>> jbe.ave > >>> Diet ave > >>> 1: d1 280 > >>> 2: d2 278 > >>> 3: d3 312 > >>> > >>> > >>> Saludos. > >>> > >>> Eric. > >>> > >>> > >>> On 10/27/2015 05:16 PM, jbetancourt wrote: > >>> > >>>> Estimados > >>>> > >>>> Cuando existia epicalc, hab�a una manera muy f�cil de determinar la > >>>> media de una variable (en esta caso Gain) por grupos, en este caso > >>>> (Diet). > >>>> ?Como se puede hacer ahora? > >>>> > >>>> Diet Gain > >>>> 1 d1 270 > >>>> 2 d1 300 > >>>> 3 d1 280 > >>>> 4 d1 280 > >>>> 5 d1 270 > >>>> 6 d2 290 > >>>> 7 d2 250 > >>>> 8 d2 280 > >>>> 9 d2 290 > >>>> 10 d2 280 > >>>> 11 d3 290 > >>>> 12 d3 340 > >>>> 13 d3 330 > >>>> 14 d3 300 > >>>> 15 d3 300 > >>>> > >>>> Saludos > >>>> Jos� > >>>> > >>>> [[alternative HTML version deleted]] > >>>> > >>>> > >>>> > >>>> _______________________________________________ > >>>> R-help-es mailing list > >>>> [email protected] > >>>> https://stat.ethz.ch/mailman/listinfo/r-help-es > >>>> > >>>> > >>> -- > >>> Forest Engineer > >>> Master in Environmental and Natural Resource Economics > >>> Ph.D. student in Sciences of Natural Resources at La Frontera University > >>> Member in AguaDeTemu2030, citizen movement for Temuco with green city > >>> standards for living > >>> > >>> Nota: Las tildes se han omitido para asegurar compatibilidad con algunos > >>> lectores de correo. > >>> > >>> > >>> _______________________________________________ > >>> R-help-es mailing list > >>> [email protected] > >>> https://stat.ethz.ch/mailman/listinfo/r-help-es > >>> > >> > >> > >> -- > >> Saludos, > >> Carlos Ortega > >> www.qualityexcellence.es > >> > >> [[alternative HTML version deleted]] > >> > >> _______________________________________________ > >> R-help-es mailing list > >> [email protected] > >> https://stat.ethz.ch/mailman/listinfo/r-help-es > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > R-help-es mailing list > > [email protected] > > https://stat.ethz.ch/mailman/listinfo/r-help-es > > _______________________________________________ > R-help-es mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-help-es [[alternative HTML version deleted]]
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