FP - Percent Degrees

Percent Degrees

#p divorced
#final project data analysis 

library(dplyr)

library(readr)

library(ggplot2)

library(RColorBrewer)

library(ggmap)

library(maptools)

library(gtools)





# read csv

ipumsdata_figure3 <- read_csv("~/Desktop/usa_00028.csv")

#women only older than 22
women_only <- ipumsdata_figure3 %>% filter(SEX==2 & AGE>=22)

#total num women
numwomen <- women_only %>% group_by(YEAR) %>% summarise(tnum=sum(PERWT))

#only women with degrees
women_educ <- women_only %>% filter(EDUCD>=101 & EDUCD<=116)

#num women with degrees

numwomen_educ <- women_educ %>% group_by(YEAR) %>% summarise(num=sum(PERWT))

#join
joined <- left_join(numwomen,numwomen_educ,by=c('YEAR'='YEAR'))

#calc percent
percentages <- joined %>% mutate(pct=num/tnum*100)






ggplot(data=percentages,aes(x=YEAR, y=pct)) + 
  geom_bar(stat='identity', position='dodge') +
  labs(x='Year',y='Percent', title='Percent of Women Holding College Degrees in the United States, 1940-2000') +
  scale_y_continuous() +
  theme_bw(base_size=22) +
  scale_x_continuous(breaks=c(1940,1960,1980,2000)) +
  scale_fill_brewer('blues')