Hi,
I have a grouped data set and would like to calculate weighted proportions for
a large number of factor variables within each group member. Rather than using
dplyr::count() on each of these factors individually, the idea would be to do
it for all factors at once. Does anyone know how this would work? Here is a
reproducible example:
############################################################
# reproducible example
df1 <- data.frame(wt=rnorm(90),
group=paste0('reg', 1:5),
var1=rep(c('male','female'), times=45),
var2=rep(c('low','med','high'), each=30)) %>% tbl_df()
# instead of doing this separately for each factor ...
df2 <- df1 %>%
group_by(group) %>%
dplyr::count(var1, wt=wt) %>%
mutate(prop1=n/sum(n))
df3 <- df1 %>%
group_by(group) %>%
dplyr::count(var2, wt=wt) %>%
mutate(prop2=n/sum(n)) %>%
left_join(df2, by='group')
# I would like to do something like the following (which does of course not
work):
my_fun <- function(x,wt){
freq1 <- dplyr::count(x, wt=wt)
prop1 <- freq1 / sum(freq1)
return(prop)
}
df1 %>%
group_by(group) %>%
summarise_all(.funs=my_fun(.), .vars=c('var1', 'var2'))
############################################################
Best regards,
Erich
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