group by - use user defined function after grouped data in R -

i have function checking 0 numbers in each column in large dataframe. want check 0 numbers in each col after grouped category. here example:

   zero_rate <- function(df) {      z_rate_list <- sapply(df, function(x) {       data.frame(       n_zero=length(which(x==0)),        n=length(x),        z_rate=length(which(x==0))/length(x))  })        d <- data.frame(z_rate_list)       d <- sapply(d, unlist)       d <- as.data.frame(d)        return(d)}     df = data.frame(var1=c(1,0,na,4,na,6,7,0,0,10),var2=c(11,na,na,0,na,16,0,na,19,na))    df1= data.frame(cat = c(1,1,1,1,1,2,2,2,2,2),df)      zero_rate_df =  df1 %>% group_by(cat) %>% do( zero_rate(.)) 

here zero_rate(df) works expected. when group data cat , calculate in each category zero_rate each column, result not expected. expect this:

   cat         va1  var2     1   n_zero  1   1             n   5   5         z_rate  0.2 0.2     2   n_zero  2   1             n   5   5        z_rate   0.4 0.2 

any suggestion? thank you.

i came following code. .[-1] used remove grouping col:

zero_rate <- function(df){     res <- lapply(df, function(x){         y <- c(sum(x == 0, na.rm = t), length(x))         c(y, y[1]/y[2])     })     res <- do.call(cbind.data.frame, res)     res$vars <- c('n_zero', 'n', 'z_rate')     res }  df1 %>% group_by(cat) %>% do( zero_rate(.[-1]))  #     cat  var1  var2   vars #   <dbl> <dbl> <dbl>  <chr> # 1     1   1.0   1.0 n_zero # 2     1   5.0   5.0      n # 3     1   0.2   0.2 z_rate # 4     2   2.0   1.0 n_zero # 5     2   5.0   5.0      n # 6     2   0.4   0.2 z_rate