IPUMS visualization in ggplot2

Code for tasks:

library(dplyr);library(ggplot2)
ipums <- read.csv('C:/Users/rt1875bv/Dropbox/DataViz/Data/IPUMS-Sex-EdAttain.csv')
usa <- ipums %>% filter(Country=='United States')
#head(usa)
ggplot(data = usa) + geom_line(aes(x = Sex, y = Count, group = EdAttain, color=EdAttain), size = 2) +
  geom_point(aes(x = Sex, y = Count, shape = Sex),size=2) +
  facet_grid(.~Year) + 
  scale_color_discrete(name='Highest education attained') + 
  theme(axis.text.x = element_text(angle=90)) + 
  scale_y_continuous(name='Count (in millions)', labels = function(x) paste(x / 1000000,'M')) 

With percents instead of counts:

usa2 <- usa%>%group_by(Year,Sex)%>%mutate(pct = 100*Count/sum(Count))
#head(usa2)
ggplot(data = usa2) + 
  geom_line(aes(x = Sex, y = pct, group = EdAttain, color=EdAttain), size = 2) +
  geom_point(aes(x = Sex, y = pct, shape = Sex,color=EdAttain),size=4) +
  facet_grid(.~Year) + 
  scale_color_discrete(name='Highest education attained') +
  ylab('Percent of population') + 
    theme(axis.text.x = element_text(angle=90))