R/us_counties_gazetteer.R
us_county_geo_details.RdUnited States county-level geographic details
us_county_geo_details()a data frame with county names, FIPS codes, areas, and lat/long
https://www.census.gov/geographies/reference-files/time-series/geo/gazetteer-files.html
Other data-import:
acaps_government_measures_data(),
acaps_secondary_impact_data(),
apple_mobility_data(),
beoutbreakprepared_data(),
cci_us_vaccine_data(),
cdc_aggregated_projections(),
cdc_excess_deaths(),
cdc_social_vulnerability_index(),
coronadatascraper_data(),
coronanet_government_response_data(),
cov_glue_lineage_data(),
cov_glue_newick_data(),
cov_glue_snp_lineage(),
covidtracker_data(),
descartes_mobility_data(),
ecdc_data(),
econ_tracker_consumer_spending,
econ_tracker_employment,
econ_tracker_unemp_data,
economist_excess_deaths(),
financial_times_excess_deaths(),
google_mobility_data(),
government_policy_timeline(),
jhu_data(),
jhu_us_data(),
kff_icu_beds(),
nytimes_county_data(),
oecd_unemployment_data(),
owid_data(),
param_estimates_published(),
test_and_trace_data(),
us_county_health_rankings(),
us_healthcare_capacity(),
us_hospital_details(),
us_state_distancing_policy(),
usa_facts_data(),
who_cases()
usc = us_county_geo_details()
dplyr::glimpse(usc)
#> Rows: 3,220
#> Columns: 9
#> $ state <chr> "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", …
#> $ fips <chr> "01001", "01003", "01005", "01007", "01009", "01011", …
#> $ ansicode <chr> "00161526", "00161527", "00161528", "00161529", "00161…
#> $ county <chr> "Autauga County", "Baldwin County", "Barbour County", …
#> $ area_land <dbl> 1539602137, 4117621645, 2292160139, 1612167476, 167010…
#> $ area_water <dbl> 25706961, 1132980868, 50523213, 9602089, 15015467, 603…
#> $ area_land_sqmi <dbl> 594.444, 1589.823, 885.008, 622.461, 644.831, 622.812,…
#> $ area_water_sqmi <dbl> 9.926, 437.446, 19.507, 3.707, 5.798, 2.331, 1.043, 6.…
#> $ geometry <POINT> POINT (-86.64644 32.53224), POINT (-87.74607 30.6592…
usc
#> Simple feature collection with 3220 features and 8 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -164.1889 ymin: 17.94805 xmax: 179.6212 ymax: 69.44934
#> CRS: NA
#> # A tibble: 3,220 × 9
#> state fips ansicode county area_land area_water area_land_sqmi
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 AL 01001 00161526 Autauga County 1539602137 25706961 594.
#> 2 AL 01003 00161527 Baldwin County 4117621645 1132980868 1590.
#> 3 AL 01005 00161528 Barbour County 2292160139 50523213 885.
#> 4 AL 01007 00161529 Bibb County 1612167476 9602089 622.
#> 5 AL 01009 00161530 Blount County 1670103866 15015467 645.
#> 6 AL 01011 00161531 Bullock County 1613076054 6038093 623.
#> 7 AL 01013 00161532 Butler County 2012002531 2701198 777.
#> 8 AL 01015 00161533 Calhoun County 1569195268 16587192 606.
#> 9 AL 01017 00161534 Chambers County 1545085607 16971700 597.
#> 10 AL 01019 00161535 Cherokee County 1433623319 120308342 554.
#> # … with 3,210 more rows, and 2 more variables: area_water_sqmi <dbl>,
#> # geometry <POINT>
summary(usc)
#> state fips ansicode county
#> Length:3220 Length:3220 Length:3220 Length:3220
#> Class :character Class :character Class :character Class :character
#> Mode :character Mode :character Mode :character Mode :character
#>
#>
#>
#> area_land area_water area_land_sqmi
#> Min. :5.300e+06 Min. :0.000e+00 Min. : 2.05
#> 1st Qu.:1.085e+09 1st Qu.:7.005e+06 1st Qu.: 419.02
#> Median :1.566e+09 Median :1.930e+07 Median : 604.52
#> Mean :2.845e+09 Mean :2.140e+08 Mean : 1098.28
#> 3rd Qu.:2.369e+09 3rd Qu.:6.022e+07 3rd Qu.: 914.64
#> Max. :3.770e+11 Max. :2.597e+10 Max. :145575.52
#> area_water_sqmi geometry
#> Min. : 0.000 POINT :3220
#> 1st Qu.: 2.705 epsg:NA: 0
#> Median : 7.452
#> Mean : 82.617
#> 3rd Qu.: 23.252
#> Max. :10028.348