One of the many challenges that social science researchers and practitioners face is the difficulty of relating data between census tracts which are re-delineated with each decennial census. While some methods of harmonizing or crosswalking data between census tracts exist, to provide additional avenues for merging these data, PD&R has released the HUD-USPS Census Tract Crosswalk Files. These unique files are derived from the USPS Vacancy Data which are regularly updated by the USPS which makes them uniquely positioned to describe human settlements patterns between census tract delineations. These data use the locations of ZIP+4 centroids, an extremely granular level of geography, the number of addresses of various types (residential, business, other, and total), and do not rely on ancillary data to map where population or households might be located.There are twelve types of crosswalk files available for download. The first six crosswalk files are used to allocate ZIP codes to Census Bureau geographies such as census tracts, counties, county subdivisions, Core Based Statistical Areas (CBSAs), CBSA Divisions, and Congressional Districts. The last six are used to allocate from those same Census Bureau geographies to ZIP Codes. It is important to note that the relationship between the two types of crosswalk files is not perfectly inverse. That is to say, the ZIP to Tract crosswalk file cannot be used to allocate data from census tract geographies to ZIP codes. Instead, the Tract to ZIP crosswalk file must be used in that specific scenario.In addition to the crosswalk files, this dataset also includes screenshots of HUDs documentation and FAQ pages.

HUD’s Office of Policy Development and Research (PD&R) announced that HUD-USPS ZIP Code Crosswalk data are now available via an application programming interface (API). With this API, developers can easily access and customize crosswalk data for use in existing applications or to create new applications. To create an account and get an access token, please visit the API page here: https://www.huduser.gov/portal/dataset/uspszip-api.html.

One of the many challenges that social science researchers and practitioners face is the difficulty of relating United States Postal Service (USPS) ZIP codes to Census Bureau geographies. There are valuable data available only at the ZIP code level that, when combined with demographic data tabulated at various Census geography levels, could open up new avenues of exploration.While some acceptable methods of combining ZIP codes and Census geography exist, they have limitations. To provide additional avenues for merging these data, PD&R has released the HUD-USPS Crosswalk Files. These unique files are derived from data in the quarterly USPS Vacancy Data. They originate directly from the USPS; are updated quarterly, making them highly responsive to changes in ZIP code configurations; and reflect the locations of both business and residential addresses. The latter feature is of particular interest to housing researchers because many of the phenomena that they study are based on housing unit or address. By using an allocation method based on residential addresses rather than by area or by population, analysts can take into account not only the spatial distribution of population, but also the spatial distribution of residences. This enables a slightly more nuanced approach to allocating data between disparate geographies. Please note that the USPS Vacancy Data is constructed from ZIP+4 data that contains records of addresses, it does not contain ZIP+4 data that are associated with ZIP codes that exclusively serve Postal Office Boxes (PO Boxes). As a result, ZIP codes that only serve PO Boxes will not appear in the files.In addition to the crosswalk files, this dataset also includes screenshots of HUDs documentation and FAQ pages.Understanding ZIP Code Crosswalk FilesThough often used for mapping, spatial analysis, and data aggregation careful attention is required when interpreting ZIP Code data relative to other administrative geographies. The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdfUsing a GIS to Geoprocess ZIP Code Crosswalk FilesThis article demonstrates how to use a GIS to process ZIP Code Crosswalk Files. In this article, calls for service from New York City's Open Data Portal are estimated at the county-level and census tract-level. This article also includes an accuracy analysis.Din, Alexander and Wilson, Ron, 2020. "Crosswalking ZIP Codes to Census Geographies: Geoprocessing the U.S. Department of Housing & Urban Development’s ZIP Code Crosswalk Files," Cityscape: A Journal of Policy Development and Research, Volume 22, Number 1, https://www.huduser.gov/portal/periodicals/cityscpe/vol22num1/ch12.pdf

Abstract

A crosswalk dataset matching US ZIP codes to corresponding county codes

Documentation

The denominators used to calculate the address ratios are the ZIP code totals. When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file.

**Example: **ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record.

So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code.

https://redivis.com/fileUploads/4ecb405e-f533-4a5b-8286-11e56bb93368%3E" alt="">(Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.)

County definition

In the United States, a county is an administrative or political subdivision of a state that consists of a geographic region with specific boundaries and usually some level of governmental authority. The term "county" is used in 48 U.S. states, while Louisiana and Alaska have functionally equivalent subdivisions called parishes and boroughs, respectively.

Further reading

The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.

Wilson, Ron and Din, Alexander, 2018. “Understanding and Enhancing the U.S. Department of Housing and Urban Development’s ZIP Code Crosswalk Files,” Cityscape: A Journal of Policy Development and Research, Volume 20 Number 2, 277 – 294. URL: https://www.huduser.gov/portal/periodicals/cityscpe/vol20num2/ch16.pdf

Contact information

Questions regarding these crosswalk files can be directed to Alex Din with the subject line HUD-Crosswalks.

Acknowledgement

This dataset is taken from the U.S. Department of Housing and Urban Development (HUD) office: https://www.huduser.gov/portal/datasets/usps_crosswalk.html#codebook

Context

Dataset created to link between County - State Name, State-County FIPS, and ZIP Code.

Acknowledgements

Data Sources

• US HUD

https://www.huduser.gov/portal/datasets/usps.html

• Census Bureau

https://www2.census.gov/geo/docs/reference/codes/files/national_county.txt https://www.census.gov/geo/reference/codes/cou.html

Data cleaned by Data4Democracy and hosted originally on Data.World: https://github.com/Data4Democracy/zip-code-to-county https://data.world/niccolley/us-zipcode-to-county-state

ZCTA data from USPS 6.2017 release.

Image from Reddit.

Unlock the power of geographical precision with this comprehensive ZIP to FIPS dataset. Seamlessly map ZIP codes to Federal Information Processing Standards (FIPS) codes, enabling accurate location-based analyses. Ideal for geospatial applications, demographic research, and data integration. Explore the seamless fusion of ZIP and FIPS codes for enhanced spatial insights.

A. SUMMARY This dataset contains the list of intersecting Analysis Neighborhoods and ZIP Codes for the City and County of San Francisco. It can be used to identify which ZIP codes overlap with Analysis Neighborhoods and vice verse. B. HOW THE DATASET IS CREATED The dataset was created with a spatial join between the Analysis Neighborhoods and ZIP codes. C. UPDATE PROCESS This is a static dataset D. HOW TO USE THIS DATASET This dataset is a many-to-many relationship between analysis neighborhoods and ZIP codes. A single neighborhood can contain or intersect with multiple ZIP codes and similarly, a single ZIP code can be in multiple neighborhoods. This dataset does not contain geographic boundary data (i.e. shapefiles/ GEOMs). The datasets below containing geographic boundary data should be used for analysis of data with geographic coordinates. E. RELATED DATASETS Analysis Neighborhoods San Francisco ZIP Codes Supervisor District (2022) to ZIP Code Crosswalk Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods

A. SUMMARY This dataset contains the list of intersecting 2022 Supervisor Districts and ZIP Codes for the City and County of San Francisco. It can be used to identify which ZIP codes overlap with Supervisor Districts (2022) and vice verse. B. HOW THE DATASET IS CREATED The dataset was created with a spatial join between the 2022 Supervisor districts and ZIP codes. C. UPDATE PROCESS This is a static dataset D. HOW TO USE THIS DATASET This dataset is a many-to-many relationship between supervisor districts and ZIP codes. A single supervisor district can contain or intersect with multiple ZIP codes and similarly, a single ZIP code can be in multiple supervisor districts. This dataset does not contain geographic boundary data (i.e. shapefiles/ GEOMs). The datasets below containing geographic boundary data should be used for analysis of data with geographic coordinates. E. RELATED DATASETS Supervisor Districts (2022) San Francisco ZIP Codes Supervisor District (2012) to ZIP Code Crosswalk Analysis Neighborhoods - 2020 census tracts assigned to neighborhoods

View the 2022 Zip Code to Supervisor District Crosswalk: https://data.sfgov.org/Geographic-Locations-and-Boundaries/Supervisor-District-2022-to-ZIP-Code-Crosswalk/2x22-z5j6 Lists intersecting Supervisor Districts and ZIP Codes for City and County of San Francisco.

This dataset contains many files; use the Tree view below to get a condensed overview of what is available. This dataset provides harmonized geographic boundary shapefiles and crosswalks sourced from the U.S. Census Bureau and accessed via the pygris Python library. It includes: ZCTA (ZIP Code Tabulation Area) shapefiles County shapefiles ZCTA-to-county crosswalk files Unique lists of ZCTAs and counties by year Shapefiles: The column names and column types are harmonized for consistency across years. The cartographic boundaries are selected across years enabling longitudinal spatial analysis and integration with external datasets such as demographic or health data. Crosswalks are fetched directly from U.S. Census sources and processed to ensure compatibility and ease of use. All files are structured to support reproducible, year-over-year spatial analyses.

Content

Lists intersecting Supervisor Districts and ZIP Codes for City and County of San Francisco.

Context

This is a dataset hosted by the city of San Francisco. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore San Francisco's Data using Kaggle and all of the data sources available through the San Francisco organization page!

• Update Frequency: This dataset is updated quarterly.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Tomas Sobek on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

US County & Zipcode Historical Demographics

Easily lookup US historical demographics by county FIPS or zipcode in seconds with this file containing over 5,901 different columns including:

*Lat/Long *Boundaries *State FIPS *Population from 2010-2019 *Death Rate from 2010-2019 *Unemployment from 2001-2020 *Education from 1970-2019 *Gender and Age Population

Provided by bitrook.com to help Data Scientists clean data faster.

Data Sources

All Data Combined Source:

https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/

Population Source:

https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/

Unemployment Source:

https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/

Zip FIPS Crosswalk Source:

https://data.world/niccolley/us-zipcode-to-county-state

County Boundaries Source:

https://public.opendatasoft.com/explore/dataset/us-county-boundaries/table/?disjunctive.statefp&disjunctive.countyfp&disjunctive.name&disjunctive.namelsad&disjunctive.stusab&disjunctive.state_name

Age Sex Source:

https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/asrh/cc-est2019-agesex-**.csv https://www2.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2010-2019/cc-est2019-agesex.pdf

Races Source:

https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/asrh/cc-est2019-alldata.csv https://www2.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2010-2019/cc-est2019-alldata.pdf

March 2024

The Plan ID Crosswalk PUF (CW-PUF) is one of the files that make up the Marketplace PUF. The purpose of the CW-PUF is to map QHPs and SADPs offered through the Marketplaces in 2018 to plans that will be offered through the Marketplaces in 2019. These data either originate from the Plan Crosswalk template (i.e., template field), an Excel-based form used by issuers to describe their plans in the QHP application process, or were generated by CCIIO for use in data processing (i.e., system-generated).This data dictionary describes the variables contained in the CW-PUF. Each record relates to a mapping between a plan offered in 2018 and a plan offered in 2019 at the county or county-zip code level.