r - dplyr summarise: Equivalent of ".drop=FALSE" to keep groups with zero length in output -

when using summarise plyr's ddply function, empty categories dropped default. can change behavior adding .drop = false. however, doesn't work when using summarise dplyr. there way keep empty categories in result?

here's example fake data.

library(dplyr)  df = data.frame(a=rep(1:3,4), b=rep(1:2,6))  # add level df$b has no corresponding value in df$a df$b = factor(df$b, levels=1:3)  # summarise plyr, keeping categories count of 0 plyr::ddply(df, "b", summarise, count_a=length(a), .drop=false)    b    count_a 1 1    6 2 2    6 3 3    0  # try dplyr df %.%   group_by(b) %.%   summarise(count_a=length(a), .drop=false)    b     count_a .drop 1 1     6       false 2 2     6       false 

not hoping for. there dplyr method achieving same result .drop=false in plyr?

the issue still open, in meantime, since data factored, can use complete "tidyr" might looking for:

library(tidyr) df %>%   group_by(b) %>%   summarise(count_a=length(a)) %>%   complete(b) # source: local data frame [3 x 2] #  #        b count_a #   (fctr)   (int) # 1      1       6 # 2      2       6 # 3      3      na 

if wanted replacement value zero, need specify fill:

df %>%   group_by(b) %>%   summarise(count_a=length(a)) %>%   complete(b, fill = list(count_a = 0)) # source: local data frame [3 x 2] #  #        b count_a #   (fctr)   (dbl) # 1      1       6 # 2      2       6 # 3      3       0