有没有办法在R中划分group_by汇总统计的答案？

Question

I'm trying to subset data from three vectors and then apply arithmetic to the summary statistics but I'm having issues with count(). Below is the summary using (summarise, dplyr), but I want it to return as the percentage of unfiltered (X_age65yr).
For example, filtered count results for Alabama is 1667, total count is 2411. I'd like Alabama, and all subsequent states, to return the filtered count by total, or 1667/2411 = .6914 or 69.14%

cthigh <- brfss2013 %>% filter(bphigh4 == "Yes", !is.na(X_age65yr),X_age65yr == "Age 65 or older") %>%
   group_by(X_state) %>% summarise(count = n())

cthigh
# A tibble: 53 x 2
   X_state              count
   <fct>                <int>
 1 Alabama               1667
 2 Alaska                 507
 3 Arizona                930
 4 Arkansas              1352
 5 California            1817
 6 Colorado              2302
 7 Connecticut           1488
 8 Delaware              1123
 9 District of Columbia  1032
10 Florida               8924
# ... with 43 more rows

ctall <- brfss2013 %>% filter(!is.na(X_age65yr),X_age65yr == "Age 65 or older") %>% 
    group_by(X_state) %>% summarise(count= n())

ctall
# A tibble: 53 x 2
   X_state              count
   <fct>                <int>
 1 Alabama               2411
 2 Alaska                 864
 3 Arizona               1578
 4 Arkansas              2069
 5 California            3111
 6 Colorado              4067
 7 Connecticut           2362
 8 Delaware              1786
 9 District of Columbia  1683
10 Florida              14245
# ... with 43 more rows

Answer 1

You can count the number of bphigh4 == "Yes" and divide it by number of rows in each X_state to get the ratio.

library(dplyr)

brfss2013 %>% 
  filter(!is.na(X_age65yr) & !is.na(bphigh4),X_age65yr == "Age 65 or older") %>%
  group_by(X_state) %>% 
  summarise(count = sum(bphigh4 == "Yes")/n() * 100)