Getting Data
There are two methods for getting data from countyfipsR
.
First, countyfipsR
contains a tibble
data
frame, countyfips
, for easily accessing unfiltered county
data.
library(countyfipsR)
head(countyfips)
#> # A tibble: 6 × 7
#> fips county_name state_name state_abb state_fips county_fips county_ns
#> <chr> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 01001 Autauga County Alabama AL 01 001 161526
#> 2 01003 Baldwin County Alabama AL 01 003 161527
#> 3 01005 Barbour County Alabama AL 01 005 161528
#> 4 01007 Bibb County Alabama AL 01 007 161529
#> 5 01009 Blount County Alabama AL 01 009 161530
#> 6 01011 Bullock County Alabama AL 01 011 161531
The second method, get_countyfips
allows for easy
filtering of data by state. Simply, specify the state or territory you
would like, and get_countyfips
returns a
tibble
of the requested data.
dataIL <- get_countyfips(state = "illinois")
head(dataIL)
#> # A tibble: 6 × 7
#> fips county_name state_name state_abb state_fips county_fips county_ns
#> <chr> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 17001 Adams County Illinois IL 17 001 424202
#> 2 17003 Alexander County Illinois IL 17 003 424203
#> 3 17005 Bond County Illinois IL 17 005 424204
#> 4 17007 Boone County Illinois IL 17 007 424205
#> 5 17009 Brown County Illinois IL 17 009 424206
#> 6 17011 Bureau County Illinois IL 17 011 424207
Merging Data
Since the resultant data are a tibble
, merging is
relatively straightforward.
GNIS https://www.usgs.gov/us-board-on-geographic-names/download-gnis-data