Includes Maryland Zip Codes and their corresponding cities/towns, and counties.

Abstract

A crosswalk dataset matching US ZIP codes to corresponding census tracts

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.)

Census tract definition

A census tract, census area, census district or meshblock is a geographic region defined for the purpose of taking a census. Sometimes these coincide with the limits of cities, towns or other administrative areas and several tracts commonly exist within a county. In unincorporated areas of the United States these are often arbitrary, except for coinciding with political lines.

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

This dataset is part of the Geographical repository maintained by Opendatasoft. It's been built from the ground up using authoritative sources including the U.S. Postal Service™, U.S. Census Bureau, National Weather Service, American Community Survey, and the IRS.Contains most USPS zip codes (lat/long).

ZIP Code Business Patterns (ZBP) is an annual series that provides economic data by ZIP Code. This table includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll for All Industries by 5-digit ZIP Code. All Industries is set using SIC=00 from 1994 to 1997 and then with NAICS=00 from 1998 to present.

ZIP Code Business Patterns (ZBP) is an annual series that provides economic data by ZIP Code. This table includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll for All Industries by 5-digit ZIP Code. All Industries is set using SIC=00 from 1994 to 1997 and then with NAICS=00 from 1998 to present.

For many countries lat/lng are determined with an algorithm that searches the place names in the main geonames database using administrative divisions and numerical vicinity of the postal codes as factors in the disambiguation of place names. For postal codes and place name for which no corresponding toponym in the main geonames database could be found an average lat/lng of 'neighbouring' postal codes is calculated. Please let us know if you find any errors in the data set. ThanksFor Canada we have only the first letters of the full postal codes (for copyright reasons)For Ireland we have only the first letters of the full postal codes (for copyright reasons)For Malta we have only the first letters of the full postal codes (for copyright reasons)The Argentina data file contains 4-digit postal codes which were replaced with a new system in 1999.For Brazil only major postal codes are available (only the codes ending with -000 and the major code per municipality).For India the lat/lng accuracy is not yet comparable to other countries.Update frequency: 1 month

The H-GAC ZIP code coverage includes polygons and their attributes for Harris County. It was primarily created from the census 2002 ZIP code boundary data with secondary source data coming from Centerpoint ZIP code, Esri 2009 ZIP code, address point data from centerpoint and counties, CRIS ( Carrier Route Information System) data, US Postal Services Online site ( Look up a ZIP code) and parcels. Must Not Overlap and Must Not have Gaps topology rules have been used in order to create an accurate ZIP code layer. The layer represents physical ZIP codes and a few PO BOX ZIP codes are included rural areas . PO BOX ZIP codes can be identifying by "zip_type" field in the attribute table.

This data represents five-digit ZIP Code areas used by the U.S. Postal Service. This is an ArcGIS Online item directly from Esri. For more information see https://www.arcgis.com/home/item.html?id=8d2012a2016e484dafaac0451f9aea24.

Table contains count and percentage of county residents living below the 200% of Federal Poverty Level (FPL). Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table C17002; data accessed on April 11, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographypop (Numeric): Population for whom poverty status was assessedfpl200 (Numeric): Number of people living below 200% of Federal Poverty Levelpct_200 (Numeric): Percent of people living below 200% of Federal Poverty Level

This dataset is part of the Geographical repository maintained by Opendatasoft.This dataset contains data for zip codes 5 digits in United States of America.ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data for each decennial census. The Census Bureau delineates ZCTA boundaries for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands once each decade following the decennial census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery.Processors and tools are using this data.EnhancementsAdd ISO 3166-3 codes.Simplify geometries to provide better performance across the services.Add administrative hierarchy.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

Table contains total population and population density summarized at county, city, zip code, and census tract level. Population density is defined as number of people residing per square mile of area. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B01001; data accessed on April 11, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (String): Geography IDNAME (String): Name of geographyt_pop (Numeric): Total populationpop_density (Numeric): Area in square milesarea (Numeric): Population density

Key Table Information.Table Title.All Sectors: County Business Patterns, including ZIP Code Business Patterns, by Legal Form of Organization and Employment Size Class for the U.S., States, and Selected Geographies: 2023.Table ID.CBP2023.CB2300CBP.Survey/Program.Economic Surveys.Year.2023.Dataset.ECNSVY Business Patterns County Business Patterns.Source.U.S. Census Bureau, 2023 Economic Surveys, Business Patterns.Release Date.2025-06-26.Release Schedule.County Business Patterns (CBP) data, including ZIP Code Business Patterns (ZBP) data are released annually around the month of June. For more information about CBP data releases, see County Business Patterns Updates..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2023, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2017 North American Industry Classification System (NAICS). For more information, see County Business Patterns Methodology..Methodology.Data Items and Other Identifying Records.Number of establishmentsAnnual payroll ($1,000)First-quarter payroll ($1,000)Number of employees (during the pay period including March 12)Noise range for annual payroll, first-quarter payroll, and number of employees during the pay period including March 12Definitions of data items can be found in the table by clicking on the column header and selecting “Column Notes” or by accessing the County Business Patterns Glossary..Unit(s) of Observation.The units for CBP are employer establishments with paid employees extracted from the Business Register, Census Bureau's source of information on employer establishments. An establishment is a single physical location at which business is conducted or services or industrial operations are performed. An establishment is not necessarily equivalent to a company or enterprise, which may consist of one or more establishments. For more information, see County Business Patterns Methodology..Geography Coverage.The data are shown at the U.S., State, County, Metropolitan and Micropolitan Statistical Areas, Combined Statistical Area, 5-digit ZIP code, and Congressional District levels. Also available are data for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) at the state and county equivalent levels.Four additional employment-size classes (1,000 to 1,499 employees, 1,500 to 2,499 employees, 2,500 to 4,999 employees, and 5,000 or more employees) are available at the CSA, MSA, and county-levels.For information about geographic classification, see Program Methodology..Industry Coverage.The data are shown at the 2- through 6-digit NAICS code levels for all sectors with published data, and for NAICS code 00 (Total for all sectors).ZBP data by employment size class, shown at the 2- through 6-digit NAICS code levels, only contains data on the number of establishments. ZBP data shown for NAICS code 00 (Total across all sectors) contains data on the number of establishments, total employment, first quarter payroll, and annual payroll.For information about industry coverage, see Program Methodology..Business Characteristics.Data are classified by Legal Form of Organization (U.S. and state level only) and employment size category of the establishment (1,000 to 1,499 employees, 1,500 to 2,499 employees, 2,500 to 4,999 employees, and 5,000 or more employees). Definitions of data items can be found in the table by clicking on the column header and selecting “Column Notes” or by accessing the County Business Patterns Glossary..Sampling.There is no sampling done for County Business Patterns. CBP data are derived from a complete tabulation of all establishments on the Census Bureau’s Business Register that meet the in-scope criteria for being included in CBP. For more information about methodology and data limitations, see County Business Patterns Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7503949, Disclosure Review Board (DRB) approval number: CBDRB-FY25-0158). Beginning with reference year 2007, CBP and ZBP data are released using the Noise Infusion disclosure avoidance methodology to protect confidentiality. To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. In accordance with U.S. Code, Title 13, Section 9, no data are published that would disclose the operations of an individual employer. For more information on the coverage, disclosure avoidance, and methodology of the CBP and ZBP data products see Program Methodology..Technical Documentation/Methodology.For detailed information see, Program Methodology..Weigh...

Release Date: 2020-07-23.Release Schedule:.The data in this file were released on July 23, 2020....Key Table Information:.Beginning with reference year 2007, ZBP data are released using the Noise disclosure methodology to protect confidentiality. See Survey Methodology for complete information on the coverage and methodology of the ZIP Code Business Patterns data series..Includes only establishments with payroll..Data by employment size class, shown at the 2-6 digit NAICS code levels only contains data on the number of establishments..Data shown for NAICS code 00 (Total for all sectors) contains data on the number of establishments, total employment, first quarter payroll, and annual payroll...Data Items and Other Identifying Records: .This file contains data classified by employment size category of the establishment .Number of establishments.Annual payroll ($1,000).First-quarter payroll ($1,000).Number of employees ..Geography Coverage:.The data are shown at the 5-digit ZIP Code level only. ..Industry Coverage:.The data are shown at the 2- through 6- digit NAICS code levels for all sectors with published data, and for NAICS code 00 (Total for all sectors)..Footnotes:.Not applicable..FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/cbp/data/2018/CB1800ZBP.zip ..API Information:.ZIP Codes Business Patterns (ZBP) data are housed in the ZIP Codes Business Patterns (ZBP) API. For more information, see Census.gov: Developers: Available APIs, County Business Patterns and Nonemployer Statistics (1986-2018): ZIP Codes Business Patterns (ZBP) APIs...Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only. ..To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, see. County Business Patterns Methodology. ..Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals (used prior to 2017).N - Not available or not comparable.S - Withheld because estimate did not meet publication standards. Employment or payroll field set to zero. .G - Low Noise.H - Moderate Noise.J - High Noise.For a complete list of symbols, see County Business Partterns Abbreviations and Symbols Glossary...Source:.U.S. Census Bureau, 2018 ZIP Business Patterns..Contact Information:.U.S. Census Bureau.Economy-Wide Statistics Division.Business Statistics Branch.Tel: (301) 763 - 2580 .Email: ewd.county.business.patterns@census.gov

Dataset contains the ZIP code boundaries inside of Hennepin County. Non-taxing polygons for Zip code areas are defined using parcel attributes of property mailing address. The field NAME_TXT contains the ZIP Code number for each polygon.

Link to Attribute Table Information: http://gis.hennepin.us/OpenData/Metadata/Zipcodes.pdf

Use Limitations: This data (i) is furnished "AS IS" with no representation as to completeness or accuracy; (ii) is furnished with no warranty of any kind; and (iii) is not suitable for legal, engineering or surveying purposes. Hennepin County shall not be liable for any damage, injury or loss resulting from this data. General questions about this dataset, including errors, omissions, corrections and/or updates should be directed to the Survey Division, Resident and Real Estate Services Department, Hennepin County at 612-348-3131.

© This data set is maintained by Hennepin County Resident and Real Estate Services Survey Division. This layer is a component of Datasets for Hennepin County AGOL and Hennepin County Open Data..

This data comes from the 2010 Census Profile of General Population and Housing Characteristics. Zip codes are limited to those that fall at least partially within LA city boundaries. The dataset will be updated after the next census in 2020. To view all possible columns and access the data directly, visit http://factfinder.census.gov/faces/affhelp/jsf/pages/metadata.xhtml?lang=en&type=table&id=table.en.DEC_10_SF1_SF1DP1#main_content.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and Zip codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential Zip code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the Zip code-level life expectancy calculation, it is assumed that postal Zip codes share the same boundaries as Zip Code Census Tabulation Areas (ZCTAs). More information on the relationship between Zip codes and ZCTAs can be found at https://www.census.gov/geo/reference/zctas.html. Zip code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 Zip code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for Zip codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest Zip code with population. Zip code population for 2000 estimates comes from the Decennial Census. Zip code population for 2013 estimates are from the American Community Survey (5-Year Average). The ACS provides Zip code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to Zip codes based on majority land-area.

Zip codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, Zip codes with populations of less than 5,000 were aggregated with neighboring Zip codes until the merged areas had a population of more than 5,000. In this way, the original 305 Bay Area Zip codes were reduced to 218 Zip code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

A listing of NYS counties with accompanying Federal Information Processing System (FIPS) and US Postal Service ZIP codes sourced from the NYS GIS Clearinghouse.

Table contains count and percentage of county residents living with a cognitive disability. Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table S1801; data accessed on July 20, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographypop (Numeric): Population for whom disability was assessedt_disability (Numeric): Number of people living with any type of disability (total)pct_t_disability (Numeric): Percent of people living with any type of disability (total)cognitive_diff (Numeric): Number of people living with cognitive disabilitypct_cognitive (Numeric): Percent of people living with cognitive disability

ZIP Code Business Patterns (ZBP) is an annual series that provides economic data by ZIP Code. This table includes the number of establishments, employment during the week of March 12, first quarter payroll, and annual payroll for All Industries by 5-digit ZIP Code. All Industries is set using SIC=00 from 1994 to 1997 and then with NAICS=00 from 1998 to present.