Plot of the latest for the votecount for the 2020 US election in selected states

us-update.R

library(extrafont)
library(tidyverse)
library(scales)


myfont <- "Roboto"
main_font <- "Roboto"
heading_font <- "Sarala"


my_theme <- theme_light(base_family = main_font) + 
  theme(legend.position = "bottom") +
  theme(plot.caption = element_text(colour = "grey50"),
        strip.text = element_text(size = rel(1), face = "bold"),
        plot.title = element_text(family = heading_font))

theme_set(my_theme)          
update_geom_defaults("text", list(family = main_font))
update_geom_defaults("label", list(family = main_font))

nyt_data <- read_csv("https://raw.githubusercontent.com/alex/nyt-2020-election-scraper/master/battleground-state-changes.csv")

us_pal = c(Biden = "#1405bd", Trump = "#de0100")

p <- nyt_data %>%
  filter(
      grepl("Arizona", state) |
      grepl("Georgia", state) |
#      grepl("Nevada", state) |
      grepl("Pennsylvania", state)
    ) %>%
  ggplot(aes(x = timestamp, y = vote_differential, colour = leading_candidate_name)) +
  facet_wrap(~state, scales = "free_y", ncol = 2) +
  geom_smooth(method = "gam", fullrange = TRUE) +
  geom_point() +
  geom_hline(yintercept = 0) +
  scale_y_continuous(label = comma_format(accuracy = 1)) +
  scale_x_datetime(limits = as.POSIXct(c("2020/11/05", "2020/11/07")),
                   labels = date_format("%a-%d\n%H:%M", tz = "America/New_York" )) +
  scale_colour_manual(values = us_pal) +
  labs(x = "Time data published (US Eastern Standard Time)",
         y = "Number of votes leading by",
         colour = "Currently\nleading\ncandidate") +
  theme(legend.position = c(0.8, 0.2))

print(p)