initial.R

#Load libraries.
library(ggplot2)
library(dplyr)
library(RColorBrewer)

#Get data.
census <- read.csv("census-income.csv", stringsAsFactors = T, strip.white = T)

#Subset census data by race and sex.
ratio_race_of_worker = group_by(census, race, sex) %>% 
  summarise(., 
            count_geq50 = sum(instance.weight[X == "50000+." & age >= 18]), 
            count_l50 = sum(instance.weight[X == "-50000" & age >= 18]),
            pct_geq50 = (count_geq50 / (count_l50 + count_geq50)) * 100)

#Graph by race and sex.
racePlot_sex = ggplot(ratio_race_of_worker, aes(x = race, y = pct_geq50)) + 
  geom_bar(stat = "identity", aes(fill = race)) + 
  scale_fill_brewer(name = "Race", palette = "Set1") +
  ggtitle("Income by Race 94' - 95'") + 
  xlab("") + 
  ylab("Percent of Race with Income >50k") + 
  theme(axis.ticks = element_blank(), axis.text.x = element_blank()) + 
  facet_wrap( ~ sex)
racePlot_sex