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.
Installation
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.
Using
addr vectors in R
The addr package provides the addr R object, which stores standardized address tags, but acts like a usual vector in R:
addr(c("3333 Burnet Ave Cincinnati OH 45229", "202 Riva Ridge Ct Cincinnati OH 45140"))
#> 3333 Burnet Avenue Cincinnati OH 45229 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"addr matching
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()$cagis_addr)
#> 3333 Burnet Avenue Cincinnati OH 45229 5130 Rapid Run Road Delhi Township OH 45238 NA NA NA NA NA NAUse the matched addr vector to merge in address-specific data in the included cagis_addr object.
addr(c("3333 Burnet Ave Cincinnati OH 45229", "5130 RAPID RUN RD CINCINNATI OHIO 45238")) |>
addr_match(cagis_addr()$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 = voter_addresses()[1040:1100],
ref_addr = cagis_addr()$cagis_addr,
ref_s2 = cagis_s2,
county = "39061",
year = "2022")
#> # A tibble: 61 × 3
#> addr s2 match_method
#> <addr> <s2cell> <fct>
#> 1 9822 Tollgate Lane Cincinnati OH 45242 8840538796e0aca3 ref_addr
#> 2 3840 Applegate Avenue Cincinnati OH 45211 8841ca63599fc325 ref_addr
#> 3 2819 Hocking Drive Cincinnati OH 45233 8841cb8ea9f6c543 ref_addr
#> 4 8311 Wetherfield Lane Cincinnati OH 45236 8840536907b7ccc5 ref_addr
#> 5 529 13th E St Cincinnati OH 45202 NA none
#> 6 996 Wittshire Lane Cincinnati OH 45255 8841a91704d8f5a5 tiger_range
#> 7 5110 Herringbone Drive Cincinnati OH 45227 8841ad10999e2617 ref_addr
#> 8 7081 Jeannie Avenue Cincinnati OH 45230 8841aed03759a5c5 ref_addr
#> 9 6924 Miami Bluff Drive Cincinnati OH 45227 8841ac605740b499 ref_addr
#> 10 433 Mcdowell Street Cincinnati OH 45226 8841adf7a4bb9c83 ref_addr
#> # ℹ 51 more rows