Using `tidycensus` to pull poverty rates by census tract and limit to high-poverty tracts (>= 35% poverty)

poverty_by_tract.R

## Load Packages
library(tidycensus)
library(purrr)

## Grab Data
# Set API key
census_api_key("your_api_key_here")

# Identify state FIPS codes
us <- unique(fips_codes$state)[1:51]

# Grab tract-level population
totalpop <- map_df(us, function(x) {
  get_acs(geography = "tract", 
          variables = "B01003_001", 
          state = x)
})

# Grab tract-level poverty populations
totalpov <- map_df(us, function(x) {
  get_acs(geography = "tract", 
          variables = "B17001_002", 
          state = x)
})

## Calculate Rate

# Merge totalpop with totalpov and calculate percent_poverty
total_data <- totalpop %>%
  rename(total_population = estimate) %>% 
  select(GEOID,
         NAME,
         total_population) %>% 
  left_join(totalpov %>% 
              rename(total_poverty = estimate) %>% 
              select(GEOID,
                     NAME,
                     total_poverty),
            by = c("GEOID",
                   "NAME")) %>% 
  mutate(percent_poverty = total_poverty / total_population) %>% 
  filter(percent_poverty >= 0.35)