r - how to find top N descending values in group in dplyr -

i have following dataframe in r

  serivce     codes    abs         rt    abs         rt    abs         ty    abs         dr    abs         dr    abs         dr    abs         dr    def         rt    def         rt    def         ty    def         dr    def         dr    def         dr    def         dr    def         ty    def         se    def         se 

what want service wise code count in descending order

  serivce     codes    count    abs         dr        4    abs         rt        2     abs         ty        1    def         dr        4    def         rt        2    def         ty        2   

i doing following in r

df%>%  group_by(service,codes) %>%  summarise(count = n()) %>% top_n(n=3,wt = count) %>%  arrange(desc(count)) %>%  as.data.frame()    

but,it not give me intended.

we can try count/arrange/slice

df1 %>%     count(service, codes) %>%    arrange(desc(n)) %>%     group_by(service) %>%     slice(seq_len(3)) # tibble: 6 x 3 # groups:   service [2] #  service codes     n #    <chr> <chr> <int> #1     abs    dr     4 #2     abs    rt     2 #3     abs    ty     1 #4     def    dr     4 #5     def    rt     2 #6     def    se     2 

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in op's code, need arrange 'service' too. @marius said in comments, top_n include more number of rows if there ties. 1 option second grouping 'service' , slice (as showed above) or after grouping, can filter

df1 %>%    group_by(service,codes) %>%   summarise(count = n()) %>%   top_n(n=3,wt = count)  %>%   arrange(service, desc(count)) %>%   group_by(service) %>%   filter(row_number() <=3)