how to find top N descending values in group in dplyr

Question

I have a 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 I want is 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 am 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 does not give me what is intended.

Answer 1

We can try with count/arrange/slice

df1 %>% 
   count(Service, Codes) %>%
   arrange(desc(n)) %>% 
   group_by(Service) %>% 
   slice(seq_len(3))
# A 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

---

In the OP's code, we need to arrange by 'Service' too. As @Marius said in the comments, the top_n will include more number of rows if there are ties. One option is to do a second grouping with 'Service' and slice (as showed above) or after the grouping, we 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)