pop-change-2024.R

library(tidycensus)
library(tidyverse)
library(scales)

state_pop <- get_estimates(
  geography = "state",
  variables = "POPESTIMATE",
  vintage = 2024,
  time_series = TRUE
)

ggplot(state_pop, aes(x = year, y = value, group = NAME)) +
  geom_line(aes(color = NAME)) +
  geom_point(aes(color = NAME)) +
  facet_wrap(~ NAME, scales = "free_y", ncol = 6) +
  theme_minimal() +
  theme(
    legend.position = "none",
    strip.text = element_text(size = 8, face = "bold"),
    axis.text.x = element_text(angle = 45, hjust = 1, size = 6),
    axis.text.y = element_text(size = 6),
    axis.line.x = element_blank(),
    panel.grid = element_blank(),
    axis.line = element_line(color = "gray80"),
    plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
    plot.subtitle = element_text(size = 10, hjust = 0.5),
    plot.caption = element_text(size = 8, hjust = 1),
    panel.spacing = unit(1, "lines"),  
    plot.margin = margin(10, 10, 10, 10)  
  ) +
  scale_color_viridis_d(option = "turbo") + 
  labs(
    title = "Population Estimates by State (2020-2024)",
    subtitle = "Showing individual trends for each state",
    x = "Year",
    y = "Population",
    caption = "Data source: 2024 US Census Population Estimates, tidycensus R package\nPlease note: y-axes are not consistent across states"
  ) +
  scale_x_continuous(breaks = 2020:2024) +
  coord_cartesian(expand = TRUE, clip = "off") +  
  scale_y_continuous(
    labels = label_number(scale = 1/1000000, suffix = "M", accuracy = 0.01),
    breaks = function(x) c(min(x), max(x)),
    expand = expansion(mult = c(0.1, 0.1))  
  )