rolling weighted mean by group with zoo and dplyr

I need to calculate the moving, weighted average by group in R.

Below is a sample of my code:

df %>% arrange(Type, Year)group_by(Type) %>% mutate("weighted.rolling.mean" = rollapplyr(    df %>% select(Value, Area),    width = 50,    function(z){      return(        weighted_mean = weighted.mean(z[,"Value"],z[,"Area"], partial = TRUE)      )    },    by.column = FALSE,    align = "right",    fill=NA  ))

Without the group_by argument, the code works fine.

If I group_by inside the rollapplyr function, I get the error below:

Error in `mutate()`:ℹ In argument: `weighted.rolling.mean = rollapplyr(...)`.ℹ In group 1: `Type = "Etageadskillelse"`.Caused by error in `x * w`:! non-numeric argument to binary operatorBacktrace:  1. ... %>% ...  9. zoo::rollapplyr(...) 11. zoo:::rollapply.default(..., align = align) 14. zoo:::rollapply.zoo(zoo(data), ...) 15. base::mapply(...) 16. zoo (local) `<fn>`(dots[[1L]][[50L]], dots[[2L]][[50L]], data = `<chr[,4]>`) 17. FUN(data[posns, ], ...) 19. stats:::weighted.mean.default(z[, "Value"], z[, "Area"], partial = TRUE)

Many thanks in advance!