Helping out Casey Wichman

casey-sex-ratio.r

library(gender)
library(genderdata)
library(ggplot2)
library(dplyr)  # so we can pipe with %>%
library(purrr)  # gives us the map function
library(tidyr)  # lets us unnest the output from purrr::map


graph_sex_ratio <- function(name, years = c(1950:2010)){
  tibble(year = years) %>%
    mutate(gender = map(year, ~gender(name, ., "ssa"))) %>%
    unnest() %>%
    ggplot(aes(x = year, y = proportion_male)) +
    geom_point() +
    geom_line() +
    geom_hline(yintercept = 0.5, linetype = "dashed") +
    labs(x = "Birth year", 
         y = "Proportion male", 
         title = paste("Sex ratio for people named", name, "at birth", sep = " ")) +
    theme_minimal()
}

graph_sex_ratio("Casey")
graph_sex_ratio("Aubrey")