Popular Vote Presidential Elections [USA]

chart_usa_popular_vote.r

library(ggplot2)
library(scales)
library(dplyr)

# https://decisiondeskhq.com/results/2024/General/President/
# https://election.lab.ufl.edu/2024-general-election-turnout/
# https://www.google.com/search?q=us+elections

# Scale factor and plot dimensions
sf <- 2
width <- 600 * sf
height <- 335 * sf
options(vsc.dev.args = list(width = width, height = height, res = 72 * sf))

# Define party colors
party_colors <- c(
  "Democrat" = "#1f78b4", # blue
  "Republican" = "#e31a1c" # red
)

# Define variables
total_ballots <- 156252813
harris_votes <- 74969829
trump_votes <- 77258241
other_votes <- 782243 + 755131 + 640903 + 388712
outstanding <- total_ballots - harris_votes - trump_votes - other_votes

# Calculate reported and projected votes
harris_reported <- harris_votes
trump_reported <- trump_votes
ratio <- harris_votes / (harris_votes + trump_votes)
harris_projected <- outstanding * ratio
trump_projected <- outstanding * (1 - ratio)
reporting <- 1 - (outstanding / total_ballots)

(trump_reported + trump_projected) / total_ballots
(harris_projected + harris_reported) / total_ballots
# Create main dataset
election_data <- data.frame(
  Year = c(
    2012, 2012, 2016, 2016, 2020, 2020, 2024, 2024, 2024, 2024
  ),
  Candidate = c(
    "Obama", "Romney", "Clinton", "Trump", "Biden", "Trump",
    "Harris (reported)", "Trump (reported)", "Harris (projected)", "Trump (projected)"
  ),
  Party = c(
    "Democrat", "Republican", "Democrat", "Republican",
    "Democrat", "Republican", "Democrat", "Republican", "Democrat", "Republican"
  ),
  Votes = c(
    65915795, 60933504, 65853514, 62984828, 81283501, 74223975,
    harris_reported, trump_reported, harris_projected, trump_projected
  ),
  Type = c(
    "reported", "reported", "reported", "reported", "reported", "reported",
    "reported", "reported", "projected", "projected"
  )
)

# Order factor levels and data for stacking
election_data$Type <- factor(election_data$Type, levels = c("reported", "projected"))
election_data <- election_data[order(election_data$Year, election_data$Type), ]

# Summing up 2024 votes by Party
totals_2024 <- election_data %>%
  filter(Year == 2024) %>%
  group_by(Party) %>%
  summarise(TotalVotes = sum(Votes)) %>%
  mutate(total_text = paste0(comma(TotalVotes), "\n", percent(TotalVotes / total_ballots, accuracy = 0.01), "%"))

# Add `total_text` column to the main dataset for 2024 "projected" rows
election_data$total_text <- NA
election_data$total_text[election_data$Year == 2024 & election_data$Type == "projected"] <-
  totals_2024$total_text

# Generate plot
chart <- ggplot(election_data, aes(x = Party, y = Votes, fill = Party)) +
  geom_bar(
    stat = "identity",
    position = position_stack(reverse = TRUE),
    aes(alpha = Type)
  ) +
  geom_text(
    aes(label = comma(round(Votes))),
    position = position_stack(vjust = -1),
    size = 3,
    color = "white",
    fontface = "bold"
  ) +
  geom_text(
    aes(label = total_text),
    inherit.aes = TRUE,
    na.rm = TRUE,
    position = position_stack(vjust = 6.5),
    size = 3.5,
    color = "black",
    fontface = "bold"
  ) +
  scale_fill_manual(values = party_colors) +
  scale_alpha_manual(
    values = c("reported" = 1, "projected" = 0.6),
    name = "Vote Type",
    labels = c("Reported", "Projected")
  ) +
  facet_wrap(~Year, nrow = 1) +
  labs(
    title = "Popular Vote US Presidential Elections (Updated: 12/6/24 9:40pm)",
    subtitle = paste0(
      sprintf("%.1f%% reporting", reporting * 100),
      " · Outstanding: ", comma(outstanding), " · @USMortality"
    ),
    caption = paste0(
      "Source: decisiondeskhq.com, election.lab.ufl.edu,",
      " wikipedia.org, google.com"
    ),
    x = "Party",
    y = "Votes",
    fill = "Party"
  ) +
  scale_y_continuous(labels = comma, limits = c(0, 85000000)) +
  theme_bw() +
  theme(
    legend.position = "top",
    axis.text.x = element_blank(),
    axis.ticks.x = element_line(color = "black")
  )

# Save the plot
ggsave(
  filename = "chart1.png", plot = chart, width = width, height = height,
  units = "px", dpi = 72 * sf, device = grDevices::png, type = "cairo"
)