Hi
the source of your problem is most probably that aggregate uses conversion of
group variable to factor and therefore empty level is lost.
From aggregate help page:
by a list of grouping elements, each as long as the variables in the data frame
x. The elements are coerced to factors before use.
The only option I can come with is
> sapply(split(dados[,c(1,3)], dados$var), g1)
A B C D E
0.02589377 0.37123239 -0.57820359 NaN 0.39584514
but maybe there is some trick I did not find.
Cheers
Petr
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Leandro
> Marino
> Sent: Monday, March 09, 2015 2:48 PM
> To: r-help at r-project.org
> Subject: [R] Show all elements
>
> Hi,
>
> Look to the following code:
>
> set.seed(1)
> dados >
data.frame(valor=rnorm(100),var=sample(LETTERS[c(1,2,3,5)],100,replace>
T),peso=rpois(100,2))
> dados[1:10,]
> dados$var <- factor(dados$var,levels=LETTERS[1:5])
> table(dados$var)
> A B C D E
> 31 31 19 0 19
>
> When I try to use summarize, Hmisc package it shows me the result
> without D category.
>
> g1 <- function(y) wtd.mean(y[,1],y[,2])
> summarize(dados[,c(1,3)], llist(var=dados$var), g1,stat.name =
'med')
> var med
> 1 A 0.02589377
> 2 B 0.37123239
> 3 C -0.57820359
> 4 E 0.39584514
>
> How do I get med = NA or something else with summarize?
>
> I realy need to the function to return all factors in the var even it
> they are an empty set.
>
> thanks in advance.
>
> leandro
>
> [[alternative HTML version deleted]]
>
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