I Used the Hispanic population and the totl population to get the % hispanic population in florida at the county level.

# Retrieve county-level data for Florida
florida_data <- get_acs(
  geography = "county",  # County-level data
  variables = c(total_pop = "B01003_001", hispanic_pop = "B03002_012"),
  state = "FL",          # Florida state code
  year = 2022,           # ACS 2022 data
  geometry = TRUE        # Include geographic data for mapping
)


# Reshape the data using pivot_wider and mutate into percent Hispanic 
florida_data_wide <- florida_data |>
  pivot_wider(names_from = variable, values_from = estimate) |>
  mutate(percent_hispanic = (hispanic_pop / total_pop) * 100) |>
  select(-moe)


# Check new data
head(florida_data_wide)


# Save CSV file
write.csv(florida_data_wide, "florida_hispanic_population.csv", row.names = FALSE)

# map of Hispanic population percentage
ggplot(data = florida_data_wide) +
  geom_sf(aes(fill = percent_hispanic), color = "white") +
  scale_fill_viridis_c(option = "plasma", name = "% Hispanic") +
  labs(
    title = "Percentage of Hispanic Population in Florida Counties (2022 ACS)",
    caption = "Source: U.S. Census Bureau, American Community Survey 2022"
  ) +
  theme_minimal()