gg-data-gender.R

data_gender <- years_of_education[,-5] %>% 
  left_join(., gender_equality_education[,-5], by = c("ccode", "country.name", "year")) %>% 
  rename(., education_years = value.x, gender_equality_education = value.y)
data_gender <- data_gender[complete.cases(data_gender$gender_equality_education),]

lm_data_gender1 <- glance(lm(gender_equality_education ~ education_years, data = data_gender))
lm_data_gender2 <- glance(lm(gender_equality_education ~ education_years, 
                             data = filter(data_gender, education_years >= 5)))

# And now for a scatterplot
ggplot(data = data_gender, aes(x = education_years, 
                                  y = gender_equality_education)) +
  geom_point() +
  geom_smooth(colour = "blue", method = "lm") +
  geom_smooth(data = filter(data_gender, education_years >= 5), colour = "red", method = "lm") +
  geom_label(aes(x = 8.5, y = 0.5, label = paste0("blue line\nR^2 = ", 
                                                  round(lm_data_gender1$adj.r.squared,3), 
                                                  "\nred line\nR^2 = ", 
                                                  round(lm_data_gender2$adj.r.squared,3))))