Addresses that were not validated at the time of collection are often heterogenously formatted, making them difficult to directly compare. The goal of addr is to clean, parse, standardize, and match messy, real-world addresses in R to use for data linkages.
You can install the development version of addr from GitHub with:
# install.packages("pak")
pak::pak("cole-brokamp/addr")addr requires a working Rust toolchain; install one using rustup.
The addr package provides the addr R object, which stores
standardized address tags, but acts like a usual vector in R:
library(addr)addr(c("3333 Burnet Ave Cincinnati OH 45229", "202 Riva Ridge Ct Cincinnati OH 45140"))
#> <addr[2]>
#> [1] 3333 Burnet Avenue Cincinnati OH 45229
#> [2] 202 Riva Ridge Court Cincinnati OH 45140Under the hood, an addr vector keeps a record of the tagged and
standardized address components so that they can be used with other
functions. To inspect or use them directly:
addr(c("3333 Burnet Ave Cincinnati OH 45229", "202 Riva Ridge Ct Cincinnati OH 45140")) |>
as.data.frame()
#> street_number street_name street_type city state zip_code
#> 1 3333 burnet avenue cincinnati oh 45229
#> 2 202 riva ridge court cincinnati oh 45140or
addr(c("3333 Burnet Ave Cincinnati OH 45229", "202 Riva Ridge Ct Cincinnati OH 45140")) |>
as.character()
#> [1] "3333 Burnet Avenue Cincinnati OH 45229"
#> [2] "202 Riva Ridge Court Cincinnati OH 45140"List all of the potentially matching addrs in a reference set of
addrs with addr_match(). The code below matches input addresses to
the reference set of all addresses in Hamilton County, OH included in
the package:
addr(c("3333 Burnet Ave Cincinnati OH 45229",
"5130 RAPID RUN RD CINCINNATI OHIO 45238",
"5131 RAPID RUN RD CINCINNATI OHIO 45238"
)) |>
addr_match(cagis_addr()$cagis_addr)
#> <addr[3]>
#> [1] 3333 Burnet Avenue Cincinnati OH 45229
#> [2] 5130 Rapid Run Road Delhi Township OH 45238
#> [3] NAUse the matched addr vector to merge in address-specific data in the
included cagis_addr object.
addr(c("3333 Burnet Ave Cincinnati OH 45229", "5130 RAPID RUN RD CINCINNATI OHIO 45238")) |>
addr_match(cagis_addr()$cagis_addr) |>
tibble::enframe(name = "input_addr", value = "ca") |>
dplyr::left_join(cagis_addr(), by = c("ca" = "cagis_addr"))
#> # A tibble: 2 × 3
#> input_addr ca cagis_addr_data
#> <int> <addr> <list<tibble[,6]>>
#> 1 1 3333 Burnet Avenue Cincinnati OH 45229 [1 × 6]
#> 2 2 5130 Rapid Run Road Delhi Township OH 45238 [1 × 6]If exact matching fails, use matching to TIGER street range files from the US census:
addr(c("3333 Burnet Ave Cincinnati OH 45229", "5130 RAPID RUN RD CINCINNATI OHIO 45238")) |>
addr_match_tiger_street_ranges()
#> $`3333 Burnet Avenue Cincinnati OH 45229`
#> # A tibble: 2 × 4
#> TLID s2_geography from to
#> <chr> <s2_geography> <dbl> <dbl>
#> 1 103925697 LINESTRING (-84.500403 39.14089, -84.500289 39.141892) 3301 3399
#> 2 103925699 LINESTRING (-84.500525 39.139737, -84.500403 39.14089) 3247 3398
#>
#> $`5130 Rapid Run Road Cincinnati OHIO 45238`
#> # A tibble: 1 × 4
#> TLID s2_geography from to
#> <chr> <s2_geography> <dbl> <dbl>
#> 1 650346231 LINESTRING (-84.608444 39.110496, -84.6087 39.110523, -… 5094 5199Because the addresses are possibly located on more than one street range
geography, use the summarize argument to return the centroid of each
set of matched street ranges and then add TIGER/Line census block group
identifers via geospatial intersection:
addr(c("3333 Burnet Ave Cincinnati OH 45229", "5130 RAPID RUN RD CINCINNATI OHIO 45238")) |>
addr_match_tiger_street_ranges(county = "39061", summarize = "centroid") |>
dplyr::bind_rows() |>
dplyr::mutate(census_bg_id = s2_join_tiger_bg(s2::as_s2_cell(s2_geography)))
#> # A tibble: 2 × 5
#> TLID s2_geography from to census_bg_id
#> <chr> <s2_geography> <dbl> <dbl> <chr>
#> 1 103925697-103925699 POINT (-84.5004091 39.1408146) 3247 3399 390610270002
#> 2 650346231 POINT (-84.6103702 39.1110311) 5094 5199 390610214011The above process is conducted, with default matching arguments, in the
function addr_match_geocode, which requires a vector of reference s2
cell locations: As of now, this process only works with the cagis_s2
available as below and for matching within Hamilton County, OH (36061)
using 2022 TIGER street range files
# select one s2 cell at random from addresses with more than one parcel identifier and coordinates
cagis_s2 <-
cagis_addr()$cagis_addr_data |>
purrr::modify_if(\(.) length(.) > 0 && nrow(.) > 1, dplyr::slice_sample, n = 1) |>
purrr::map_vec(purrr::pluck, "cagis_s2", .default = NA, .ptype = s2::s2_cell())
addr_match_geocode(x = sample(voter_addresses(), 100),
ref_addr = cagis_addr()$cagis_addr,
ref_s2 = cagis_s2,
county = "39061",
year = "2022")
#> # A tibble: 100 × 3
#> addr s2 match_method
#> <addr> <s2cell> <fct>
#> 1 411 Pedretti Avenue Cincinnati OH 45238 8841b6192539a2e5 ref_addr
#> 2 7432 Bayswater Drive Cincinnati OH 45255 8841af3264f87405 tiger_range
#> 3 5366 Dickens Drive Cincinnati OH 45241 884051140ea170a7 ref_addr
#> 4 245 Mcguire Lane Cincinnati OH 45215 88405286586bc095 ref_addr
#> 5 3909 Dickson Avenue Cincinnati OH 45229 8841b30e55fab54d ref_addr
#> 6 4025 Egbert Avenue Cincinnati OH 45220 8841b37c962f5a3b ref_addr
#> 7 11451 Folkstone Drive Cincinnati OH 45240 88404ebd7161497d ref_addr
#> 8 1860 Queen City Avenue Cincinnati OH 45214 8841b43472fe3997 ref_addr
#> 9 9797 Cooper Woods Court Cincinnati OH 45241 88405251fbc59f91 ref_addr
#> 10 3815 Lincoln Road Cincinnati OH 45247 88403554febe6d93 ref_addr
#> # ℹ 90 more rows