K-12 Enrollment Plot

k12_enrollment_plot.R

# Enrollment Demographics Stacked Bar Plot

# Libraries ---------------------------------------------------------------

library(tidyverse)
library(geofacet)
library(showtext)
library(cowplot)

font_add_google("Noto Sans", "noto-sans")
font_add_google("Noto Serif", "noto-serif")

showtext_auto()
quartz()

# Function ----------------------------------------------------------------

plot_theme <- function(dat){
  dat %>% 
    ggplot(aes(state, value, fill = variable)) +
    geom_col(aes(fill = variable),
             position = position_stack(),
             color = "white",
             size = 0.3,
             width = 0.4) +
    coord_flip() +
    theme_minimal() +
    theme(text = element_text(size = 9,
                              family = "noto-sans"),
          plot.subtitle = element_text(size = 14,
                                       family = "noto-serif"),
          legend.position = "bottom",
          plot.title = element_text(size = 18,
                                    face = "bold",
                                    family = "noto-serif"),
          plot.caption = element_text(family = "noto-sans"),
          legend.title = element_blank(),
          axis.title.x = element_blank(),
          axis.title.y = element_blank()) +
    guides(fill = guide_legend(nrow = 1)) +
    scale_y_continuous(labels = scales::percent) +
    scale_fill_manual(labels = c("american_indian_alaska_native_percent_2018" = "Am. Indian/Alaska Native", 
                                 "asian_percent_2018" = "Asian", 
                                 "black_percent_2018" = "Black", 
                                 "latino_percent_2018" = "Latino", 
                                 "pacific_islander_percent_2018" = "Pacific Is.", 
                                 "two_or_more_races_percent_2018" = "Two or More Races",
                                 "white_percent_2018" = "White"),
                      values = c("american_indian_alaska_native_percent_2018" = "#e96c3e", 
                                 "asian_percent_2018" = "#69a89d", 
                                 "black_percent_2018" = "#afdbf6", 
                                 "latino_percent_2018" = "#c3e3d4", 
                                 "pacific_islander_percent_2018" = "#355759", 
                                 "two_or_more_races_percent_2018" = "#631c48",
                                 "white_percent_2018" = "#14256b"))
}

# Data --------------------------------------------------------------------

dat <-
  read_csv(here::here("data", "processed", "state_enroll_long_2018.csv"))

# Plots -------------------------------------------------------------------

p1 <-
  dat %>% 
  filter(str_detect(variable, "percent_2018"),
         state != "United States") %>% 
  arrange(fct_relevel(variable, "white_percent_2018"), value) %>%
  mutate(state = fct_inorder(state)) %>% 
  plot_theme() +
  labs(caption = "Source: National Center for Education Statistics")

p2 <-
  dat %>% 
  filter(str_detect(variable, "percent_2018"),
         state == "United States") %>% 
  arrange(fct_relevel(variable, "white_percent_2018"), value) %>%
  mutate(state = fct_inorder(state)) %>% 
  plot_theme() +
  theme(legend.position = "none",
        plot.margin = unit(c(0,0.2,0,1), "cm"),
        axis.text.x = element_blank()) +
  labs(title = "Percentage distribution of enrollment in public elementary and secondary schools",
       subtitle = "By race/ethnicity and state 2018") +
  geom_text(data = dat %>% 
              filter(variable %in% c("white_percent_2018"),
                     state == "United States"), 
            aes(label = paste0("White: ",
                               scales::percent(round(value, 2)))),
            position = position_stack(vjust = 0.5),
            color = "white",
            size = 4) +
  geom_text(data = dat %>% 
              filter(variable %in% c("black_percent_2018"),
                     state == "United States"), 
            aes(label = paste0("Black: ",
                               scales::percent(round(value, 2)))),
            position = position_stack(vjust = 5.75),
            color = "black",
            size = 4) +
  geom_text(data = dat %>% 
              filter(variable %in% c("latino_percent_2018"),
                     state == "United States"), 
            aes(label = paste0("Latino: ",
                               scales::percent(round(value, 2)))),
            position = position_stack(vjust = 2.4),
            color = "black",
            size = 4)

plot_grid(p2, p1,
          rel_heights = c(1, 4),
          ncol = 1)

# Save Plots --------------------------------------------------------------

ggsave(here::here("plot1.png"), dpi = "retina", width = 16, height = 9, units = "in")