educationPlot.R

#Tally the totals for each level of education.
education_totals = summarise(education_numbers, 
                             Both = sum(instance.weight),
                             Males = sum(instance.weight[sex == "Male"]),
                             Females = sum(instance.weight[sex == "Female"]))

education_numbers_both = group_by(education_numbers, education) %>%
  summarise(.,
            Both = (sum(instance.weight) / education_totals$Both) * 100)

education_numbers_males = group_by(education_numbers, education, sex) %>%
  summarise(.,
            pct = (sum(instance.weight[sex == "Male"]) / education_totals$Males) * 100)

education_numbers_females = group_by(education_numbers, education, sex) %>%
  summarise(.,
            pct = (sum(instance.weight[sex == "Female"]) / education_totals$Females) * 100)

education_numbers_males$pct = education_numbers_males$pct + education_numbers_females$pct

#Getting education by income
education_income = group_by(education_numbers, education, sex) %>%
  summarise(., 
            count_geq50 = sum(instance.weight[X == "50000+." & age >= 18]), 
            count_l50 = sum(instance.weight[X == "-50000" & age >= 18]),
            pct = (count_geq50 / (count_l50 + count_geq50)) * 100) %>%
  select(., education, sex, pct)

#Stack data for ggplot2
population.ident = rep("Percent of Total Population", NROW(education_numbers_males))
income.ident = rep("Percent with Certain Education with Income >$50,000", NROW(education_income))

education_numbers_males$Identifier = population.ident
education_income$Identifier = income.ident

education_stacked = rbind(education_numbers_males, education_income)

#Male/female side by side education/income vertically
educationPlot_mf = ggplot(education_stacked, aes(x = education, y = pct)) + 
  geom_bar(stat = "identity", aes(fill = education)) + 
  theme_bw() + 
  scale_fill_discrete(name = "Education") + 
  ggtitle("Education Grid 94' - 95'") + 
  xlab("") + 
  ylab("") + 
  theme(axis.ticks = element_blank(), axis.text.x = element_blank()) + 
  facet_grid(Identifier ~ sex)
educationPlot_mf