pop-estimates-2024.R

library(tidycensus)
library(ggplot2)
library(dplyr)

state_mig <- get_estimates(
  geography = "state", 
  variables = c("RDOMESTICMIG", "RINTERNATIONALMIG"),
  vintage = 2024,
  output = "wide"
)

ggplot(state_mig, aes(y = reorder(NAME, RDOMESTICMIG))) +
  geom_segment(aes(x = RDOMESTICMIG, xend = RINTERNATIONALMIG, yend = NAME),
               color = "#959595", size = 1.5) +
  geom_point(aes(x = RDOMESTICMIG), color = "red", size = 3) +
  geom_point(aes(x = RINTERNATIONALMIG), color = "blue", size = 3) +
  geom_vline(xintercept = 0, color = "black", size = 1) +
  theme_minimal() +
  theme(
    panel.grid.minor.y = element_blank(),
    axis.text.y = element_text(size = 8)
  ) +
  labs(
    title = "Comparison of International vs. Domestic Migration Rates by State",
    subtitle = "Red: Domestic Migration Rate | Blue: International Migration Rate",
    x = "Migration Rate (per 1000 people)",
    y = "State"
  ) +
  scale_x_continuous(breaks = c(-5, 0, 15))