beeswarm_us2020.R

library(tidyverse)
library(ggbeeswarm)
library(ggthemes)
library(glue)

elex <- read_csv("https://raw.githubusercontent.com/favstats/USElection2020-NYT-Results/master/data/latest/presidential.csv")

elex %>% 
  mutate(votes_perc = votes/sum(votes)) %>% 
  mutate(abs_margin2020 = abs(margin2020)) %>% 
  mutate(vote_size = ifelse(votes >= 100000, "Counties with more than 100k votes", "Counties with less than 100k votes")) %>% 
  mutate(vote_size = fct_relevel(vote_size, c("Counties with more than 100k votes", "Counties with less than 100k votes"))) %>% 
  ggplot(aes(y = margin2020, x= 1, color = margin2020, size = votes_perc, alpha = abs_margin2020)) + 
  geom_quasirandom(method = "tukeyDense", groupOnX=T) +
  scale_color_gradient2("Margins",
                        low = "#0000ff",
                        mid = "purple",
                        high = "#ff0803") +
  scale_y_continuous(labels = c("+50% Biden", "0%", "+50% Trump"),
                     breaks = c(-50, 0, 50)) +
  scale_alpha(range = c(0.4, 1)) +
  scale_size(range = c(0.65, 12)) +
  coord_flip() +
  ggthemes::theme_fivethirtyeight() +
  geom_hline(yintercept = 0, linetype = "dashed") +
  labs(y = "\nCounty Margins in the 2020 US Election", caption = glue("\n\nColor reflects by which margin the county was won: blue = greater Biden margin; red = greater Trump margin. The size of the bubble reflects the county share of votes of the national total vote count.\n\nSource: New York Times. Last updated: {as.character(elex$retrieved_time)[1]}. Visualization created by Fabio Votta (@favstats)\n"), title = "US 2020 Presidential Election - Results by County") +
  facet_wrap(~vote_size, ncol = 1) +
  theme(legend.position = "none",
        panel.grid = element_blank(),
        axis.title.y = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        panel.background = element_blank(), plot.caption = element_text(hjust = 0))