This dataset was created to help users to go between County - State Name, State-County FIPS, City, or to ZIP Code. Most importantly, this dataset was created because we shouldn't have to pay for free & public data.

Assumptions - HUD uses the most up to date Zip Code boundaries from the USPS when they post their new Quarterly data. *ZIP Codes are updated on a regular basis. Here is an example announcement from the USPS. - City data only available from 2018 onward.

Data Sources

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

Census Bureau The table data, direct link. This data is only updated once every census, 10 years. The details of the National County text file can be found here

USPS Zip to City Lookup More information can be found here. It's a free API from the USPS. Need to create a username to pull the data.

Data Dictionary

Files 2018 -> Newer - ZIP ZIP Code - STCOUNTFP US State & County FIPS ID - CITY City for that Zip/Fips Code - STATE US State - COUNTYNAME US County Name - CLASSFP FIPS Class Code, as defined by the Census

Files 2010-2017 - ZIP ZIP Code - COUNTYNAME US County Name - STATE US State - STCOUNTFP US State & County FIPS ID - CLASSFP FIPS Class Code, as defined by the Census

FIPS Class Code Details Source Copied 7/29/17

• H1 identifies an active county or statistically equivalent entity that does not qualify under subclass C7 or H6.
• H4 identifies a legally defined inactive or nonfunctioning county or statistically equivalent entity that does not qualify under subclass H6.
• H5 identifies census areas in Alaska, a statistical county equivalent entity.
• H6 identifies a county or statistically equivalent entity that is a really coextensive or governmentally consolidated with an incorporated place, part of an incorporated place, or a consolidated city.
• C7 identifies an incorporated place that is an independent city; that is, it also serves as a county equivalent because it is not part of any county, and a minor civil division (MCD) equivalent because it is not part of any MCD.

Acknowlegement

Foto von Annie Spratt auf Unsplash

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

This tool--a simple csv or Stata file for merging--gives you a fast way to assign Census county FIPS codes to variously presented county names. This is useful for dealing with county names collected from official sources, such as election returns, which inconsistently present county names and often have misspellings. It will likely take less than ten minutes the first time, and about one minute thereafter--assuming all versions of your county names are in this file. There are about 3,142 counties in the U.S., and there are 77,613 different permutations of county names in this file (ave=25 per county, max=382). Counties with more likely permutations have more versions. Misspellings were added as I came across them over time. I DON'T expect people to cite the use of this tool. DO feel free to suggest the addition of other county name permutations.

State, County and City FIPS (Federal Information Processing Standards) codes are a set of numeric designations given to state, cities and counties by the U.S. federal government. All geographic data submitted to the FRA must have a FIPS code.

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

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

"This file provides digital data for all 1990 precensus map features, the associated 1990 census initial tabulation geographic area codes, such as 1990 census block numbers, and the codes for the Jan. 1, 1990 political areas on both sides of each line segment of every mapped feature. The data contain basic information on 1990 census geographic area codes, feature names, and address ranges in the form of ten ""Record Types."" The Census Bureau added four new record types in response to some us er and vendor requests to provide point and area information contained in the Census Bureau's Precensus Map sheets that is not contained in the Precensus TIGER/Line files. The record types include: Basic data records (individual Feature Segment Records), shape coordinate points (feature shape records), additional decennial census geographic area codes, index to alternate feature names, feature name list, additional address range and zip code data, landmark features, area landmarks, area boundaries, and polygon location. Each segment record contains appropriate decennial census and FIPS geographic area codes, latitude/longitude coordinates, the name of the feature (including the relevant census feature class code identifying the segment by category), and, for areas formerly covered by the GBF/DIME-Files, the address ranges and ZIP code associated with those address ranges for each side of street segments. For other areas, the TIGER?Line files do not contain address ranges or ZIP Codes. The shape records provide coordinate values that describe the shape of those feature segments that are not straight."

The dataset contains a hierarchal listing of New York State counties, cities, towns, and villages, as well as official locality websites

Abstract (en): This dataset contains records for each public secondary and elementary education agency in the United States and its outlying areas (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) for 1985-1986. Reporting agencies serve instructional levels from pre-kindergarten through grade 12, or the equivalent span of instruction in ungraded or special education districts. Regional Educational Service Agencies, supervisory unions, and county superintendents are also represented. Variables include state and federal ID numbers, agency name, address, city, and ZIP code, FIPS county and out-of-state indicators, instructional operating status, agency type, grade span, metropolitan statistical area (MSA) ID and status, and board of control selection code. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. All public elementary and secondary education agencies in operation during 1985-1986 in the 50 states, the District of Columbia, and United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands). The codebook is provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.

Abstract (en): This poll, fielded December 10-13 2009, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked to give their opinions of President Barack Obama and his handling of the presidency, the federal budget deficit, health care, the situation in Afghanistan, unemployment, global warming, and the economy. Respondents were asked whether the Obama Administration or the Republicans in Congress could be trusted to do a better job handling the economy, health care reform, the situation in Afghanistan and energy policy. Several questions addressed health care including whether respondents supported the health care system being developed by Congress and the Obama Administration, whether they believed health care reform would increase the federal budget deficit, whether government should lower the age requirement for Medicare, and what the respondents' plan preference was for people who are not insured. Noneconomic questions focused on the role of the United States in Afghanistan, confidence in the Obama Administration in the handling of Afghanistan and the Taliban, and the environment. Other questions focused on the topics of health care in the United States, job availability, personal finances as well as opinions on professional golfer Tiger Woods. Demographic variables include sex, age, race, political political philosophy, party affiliation, education level, religious preference, household income, and whether respondents considered themselves to be a born-again Christian. The data contain a weight variable (WEIGHT) that should be used in analyzing the data. The weights were derived using demographic information from the Census to adjust for sampling and nonsampling deviations from population values. Until 2008 ABC News used a cell-based weighting system in which respondents were classified into one of 48 or 32 cells (depending on sample size) based on their age, race, sex, and education; weights were assigned so the proportion in each cell matched the Census Bureau's most recent Current Population Survey. To achieve greater consistency and reduce the chance of large weights, ABC News in 2007 tested and evaluated iterative weighting, commonly known as raking or rim weighting, in which the sample is weighted sequentially to Census targets one variable at a time, continuing until the optimum distribution across variables (again, age, race, sex, and education) is achieved. ABC News adopted rim weighting in January 2008. Weights are capped at lows of 0.2 and highs of 6. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Persons aged 18 and over living in households with telephones in the contiguous 48 United States. Households were selected by random-digit dialing. Within households, the respondent selected was the youngest adult living in the household who was home at the time of the interview. Please refer to the codebook documentation for more information on sampling. computer-assisted telephone interview (CATI)The data available for download are not weighted and users will need to weight the data prior to analysis.The variables PCTBLACK, PCTASIAN, PCTHISP, MSAFLAG, CSA, CBSA, METRODIV, NIELSMKT, BLOCKCNT, STATE, CONGDIST, and ZIP were converted from character variables to numeric.To preserve respondent confidentiality, codes for the variables FIPS (FIPS County) and ZIP (ZIP Code) have been replaced with blank codes.System-missing values were recoded to -1.The CASEID variable was created for use with online analysis.Several codes in the variable CBSA contain diacritical marks.Value labels for unknown codes were added in variables MSA, CSA, CBSA, COLLEDUC, and METRODIV. The data collection was produced by Taylor Nelson Sofres of Horsham, PA. Original reports using these data may be found via the ABC News Polling Unit Web site and via the Washington Post Opinion Surveys and Polls Web site.

This dataset contains FIPS (Federal Information Processing Standard), GNIS (Geographic Name Information System common) codes for identifying Washington state counties cities and towns. This is an official list from OFM (Office of Financial Management).