r - Finding percentage in a sub-group using group_by and summarise -

i new dplyr , trying following transformation without luck. i've searched across internet , have found examples same in ddply i'd use dplyr.

i have following data:

   month   type  count 1  feb-14  bbb   341 2  feb-14  ccc   527 3  feb-14  aaa  2674 4  mar-14  bbb   811 5  mar-14  ccc  1045 6  mar-14  aaa  4417 7  apr-14  bbb  1178 8  apr-14  ccc  1192 9  apr-14  aaa  4793 10 may-14  bbb   916 ..    ...  ...   ... 

i want use dplyr calculate percentage of each type (aaa, bbb, ccc) @ month level i.e.

   month   type  count  per 1  feb-14  bbb   341    9.6% 2  feb-14  ccc   527    14.87% 3  feb-14  aaa  2674    .. ..    ...  ...   ... 

i've tried

data %>%   group_by(month, type) %>%   summarise(count / sum(count)) 

this gives 1 each value. how make sum(count) sum across types in month?

try

library(dplyr) data %>%     group_by(month) %>%     mutate(countt= sum(count)) %>%     group_by(type, add=true) %>%     mutate(per=paste0(round(100*count/countt,2),'%')) 

we use left_join after summarising sum(count) 'month'

or option using data.table.

 library(data.table)  setkey(setdt(data), month)[data[, list(count=sum(count)), month],                 per:= paste0(round(100*count/i.count,2), '%')][]