Dogs of New York — nyc_license • nycdogs

Dog licenses active in New York City, from annual extracts of the Department of Health and Mental Hygiene (DOHMH) Dog Licensing System. Covers extract years 2016–2018, 2022–2024, and 2026.

Usage

nyc_license

Format

`nyc_license`

A tibble with 819,323 rows and 12 columns:

animal_name: Name of dog, as provided by the owner. Sentence case.
animal_gender: Sex of dog, as provided by the owner: "M" or "F".
animal_birth_year: Year dog was born, as provided by the owner. NA where the source has a spreadsheet error in place of a value.
breed_name: Dog breed, as provided by the owner. Whitespace and capitalization are standardized. "Unknown" is a reported category.
breed_rc: Recoded breed. Variant, abbreviated, and misspelled names are standardized, and varieties are collapsed to their breed. See Details.
zip_code: Owner zip code. Same as zip.
zip: Owner zip code.
license_issued_date: Date license issued.
license_expired_date: Date license expires.
extract_year: Year the record was extracted.
borough: Borough of owner, based on zip code. Some zip codes are in more than one borough but here are counted only once. NA for zip codes not in nycmaps::nyc_zip_sf.
city: Nominal city (USPS designation), based on zip code.

Source

NYC Open Data https://data.cityofnewyork.us/Health/NYC-Dog-Licensing-Dataset/nu7n-tubp, retrieved October 5th 2026.

Details

The data is sourced from the DOHMH Dog Licensing System (https://a816-healthpsi.nyc.gov/DogLicense), where owners can apply for and renew dog licenses. Each record represents a unique dog license that was active during the year, but not necessarily a unique record per dog, since a license that is renewed during the year results in a separate record of an active license period. Licenses are valid for one to five years.

breed_rc is a recoded version of breed_name:

Inverted names are put in their usual order, e.g. "Bull Dog, French" becomes "French Bulldog".
Varieties are collapsed to their breed, e.g. "Dachshund Smooth Coat" and "Dachshund, Long Haired Miniature" become "Dachshund"; "Poodle, Toy" and "Poodle, Standard" become "Poodle"; and "Collie, Rough Coat" becomes "Collie". Breeds that are distinct, such as Miniature, Standard, and Giant Schnauzers or Pembroke and Cardigan Welsh Corgis, are kept apart.
Long, abbreviated, and misspelled names are standardized, e.g. "American Pit Bull Terrier/Pit Bull" becomes "Pit Bull" and "Cav Kc" becomes "Cavalier King Charles Spaniel".
Crossbreeds are kept distinct from their breed and are labeled consistently, so that e.g. "Terrier Mix", "Terrier X", and "Terrier Crossbreed" are all "Terrier Crossbreed".
Free-text descriptions of two or more breeds, e.g. "Beagle/Boxer", are left as they are.

The lookup table used is in data-raw/breed_recodes.csv in the package source. breed_rc in nyc_bites is coded in the same way.

Other than this the data is deliberately lightly cleaned. Owner-provided values are kept as reported, including placeholder names (e.g. "Unknown", "Name not provided"), implausible birth years, and malformed zip codes.

Licenses, dogs, and duplicate records

Two features of the data matter for any analysis.

First, dog licenses expire. Each row is a record of a time-limited license that was issued, not necessarily the record of a unique individual dog. A dog whose license is renewed appears once for each license period.

Second, the table contains several extracts of the licensing data, marked by the extract_year column. A license that was active in more than one extract year appears in each of them, so there are a substantial number of duplicated rows. About 155,000 of the 819,323 rows repeat an earlier record.

Any analysis of the table should try to de-duplicate the records. For example, arrange the data by extract year, find distinct records based on a number of the identifying columns, and keep only one of them (here, the earliest):

nyc_license |>
  dplyr::arrange(extract_year) |>
  dplyr::distinct(
    animal_name,
    animal_gender,
    animal_birth_year,
    breed_name,
    zip,
    license_issued_date,
    license_expired_date,
    .keep_all = TRUE
  )

This leaves one row per license. To count dogs and not licenses, drop the two license date columns from the call to distinct(). There is no dog identifier in the data, so this is approximate: two dogs with the same name, sex, birth year, and breed in the same zip code cannot be told apart.

Author

Kieran Healy