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FIPS - Analyze US Counties as if they were sites, to get summary indicators summary for each county

Source: R/FIPS_FUNCTIONS.R
counties_as_sites.Rd

FIPS - Analyze US Counties as if they were sites, to get summary indicators summary for each county

Usage

counties_as_sites(fips)

Arguments

fips

County FIPS vector, like fips_counties_from_state_abbrev("DE")

Value

provides table similar to the output of getblocksnearby(), data.table with one row per blockgroup in these counties, or all pairs of county fips - bgid, and ejam_uniq_id (1 through N) assigned to each county but missing blockid and distance so not ready for doaggregate().

Details

This function provides one row per blockgroup. getblocksnearby_from_fips() provides one row per block. See more below under "Value"

See also

getblocksnearby_from_fips()

Examples

 
 # compare counties within a state:
 fipsRI = fips_counties_from_state_abbrev("RI")
 x = counties_as_sites(fipsRI)
 out = doaggregate(x) # similar to ejamit()
 ejam2barplot_sites(out, "pop", names.arg = fipsRI)
 
 # compare two specific counties:
 counties_as_sites(c('01001','72153'))
 
 # Largest US Counties by ACS Population Totals:
 topcounties = blockgroupstats[ , .(ST = ST[1], countypop = sum(pop)),
  by = .(FIPS = substr(bgfips,1,5))][order(-countypop),][1:20, .(
    CountyPopulation = prettyNum(countypop, big.mark = ","), FIPS, ST)]
 
 myfips = topcounties$FIPS
 
 # simplest map of top counties
 map_shapes_leaflet(shapes = shapes_counties_from_countyfips(myfips))
 
 # simplest way to get and map results county by county
 out_c1 = ejamit(fips = myfips)
 mapfastej_counties(out_c1$results_bysite)
   
 # another way to get and map results county by county
 s2b = counties_as_sites(myfips)
 out_c2 = doaggregate(s2b) 
 # but without URLs/links to reports
 bysite = out_c2$results_bysite
 bysite$ejam_uniq_id <- myfips
 mapfastej_counties(bysite)