How to use dplyr to generate a frequency table
library(dplyr)df %>% count(Color, Gender) %>% group_by(Color) %>% # now required with changes to dplyr::count() mutate(prop = prop.table(n))# Source: local data frame [4 x 4]# Groups: Color [3]# # Color Gender n prop# (fctr) (fctr) (int) (dbl)# 1 Blue M 1 1.0000000# 2 Red F 2 0.6666667# 3 Red NA 1 0.3333333# 4 NA M 1 1.0000000Updating per comment -- if you want to look at each variable separately, you will need to rearrange the dataframe first. You can accomplish this with tidyr:
library(tidyr)library(dplyr)gather(df, "var", "value", -RespondentID) %>% count(var, value) %>% group_by(var) %>% # now required with changes to dplyr::count() mutate(prop = prop.table(n))# Source: local data frame [6 x 4]# Groups: var [2]# # var value n prop# (fctr) (chr) (int) (dbl)# 1 Color Blue 1 0.2# 2 Color Red 3 0.6# 3 Color NA 1 0.2# 4 Gender F 2 0.4# 5 Gender M 2 0.4# 6 Gender NA 1 0.2