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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

if (FALSE) { # \dontrun{
# 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 = EJAM:::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)
} # }