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

Comprehensive, weekly-updated postal and ZIP code datasets covering 247 countries...

Abstract

Dataset quality ***: High quality dataset that was quality-checked by the EIDC team

The United States Environmental Protection Agency (EPA) collects occurrence data for contaminants that may be present in drinking water, but are not currently subject to the agency's drinking water regulations.

Methodology

How does EPA select the contaminants for UCMR?

In establishing the list of contaminants for each Unregulated Contaminant Monitoring Rule (UCMR) cycle, EPA considers the Contaminant Candidate List (CCL) and other priority contaminants. Further, EPA considered the opportunity to use multi-contaminant methods to collect occurrence data in an efficient, cost-effective manner.

EPA evaluates candidate UCMR contaminants using a multi-step prioritization process. The first step includes identifying contaminants that:

(1) were not monitored under prior UCMR cycles

(2) may occur in drinking water

(3) are expected to have a completed, validated drinking water method in time for rule proposal.

The next step is to consider the following: availability of health assessments or other health-effects information (e.g., critical health endpoints suggesting carcinogenicity); public interest (e.g., PFAS); active use (e.g., pesticides that are registered for use); and availability of occurrence data.

During the final step, EPA considers stakeholder input; looks at cost-effectiveness of the potential monitoring approaches; considers implementation factors (e.g., laboratory capacity); and further evaluates health effects, occurrence, and persistence/mobility data to identify the list of proposed UCMR contaminants.

Usage

There are 3 different UCMR waves in this dataset: UCMR 2 (2008 - 2010), UCMR 3 (2013 - 2015), UCMR 4 (2018 - 2020). All three have their unique key identifiers to be the combination of %3Cu%3ESample ID and Contaminant Name and Public Water System ID%3C/u%3E

. NOTE: The first two variables can be combined to uniquely identify most observations. The third variable is added to ensure absolute uniqueness.

For UCMR 2, we have one main table corresponding.

For UCMR 3, in addition to the main table, we have two additional tables for residual disinfectant type detected in some of the PWSs that are subject to such regulations, and for the service area zipcodes reported by some PWSs.

For UCMR 4, in addition to the main table, we have four additional tables for additional results for total organic carbon and bromide from select PWSs, for additional data elements for cyanotoxins, for additional disinfectant type information for some PWSs, and for the service area zipcodes reported by some PWSs. NOTE: UCMR 4 has no Associated Facility information.

Context

The EPA uses the UCMR to collect data for contaminants that are suspected to be present in drinking water and do not have health-based standards set under the Safe Drinking Water Act (SDWA).

Occurrence data are collected through UCMR to support the Administrator's determination of whether to regulate particular contaminants in the interest of protecting public health. The program was developed in coordination with the Contaminant Candidate List (CCL) a list of contaminants that:

• Are not regulated by the National Primary Drinking Water Regulations
• Are known or anticipated to occur at public water systems (PWS)
• May warrant regulation under the SDWA

%3C!-- --%3E

What are the public health benefits of UCMR?

UCMR provides EPA and others with scientifically valid data on the occurrence of these contaminants in drinking water. This permits assessment of the population being exposed and the levels of exposure.

UCMR data represent one of the primary sources of national occurrence data in drinking water that EPA uses to inform regulatory and other risk management decisions for drinking water contaminant candidates. This data will ensure science-based decision-making and help prioritize protection of disadvantaged communities.

This is the ONS Postcode Directory (ONSPD) for the United Kingdom as at February 2024 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. This file contains the multi CSVs so that postcode areas can be opened in MS Excel. To download the zip file click the Download button. The ONSPD relates both current and terminated postcodes in the United Kingdom to a range of current statutory administrative, electoral, health and other area geographies. It also links postcodes to pre-2002 health areas, 1991 Census enumeration districts for England and Wales, 2001 Census Output Areas (OA) and Super Output Areas (SOA) for England and Wales, 2001 Census OAs and SOAs for Northern Ireland and 2001 Census OAs and Data Zones (DZ) for Scotland. It now contains 2021 Census OAs and SOAs for England, Wales and Northern Ireland. It helps support the production of area-based statistics from postcoded data. The ONSPD is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The ONSPD is issued quarterly. (File size - 231 MB) Please note that this product contains Royal Mail, Gridlink, LPS (Northern Ireland), Ordnance Survey and ONS Intellectual Property Rights.

A dataset listing Georgia cities by population for 2024.

A dataset listing Florida cities by population for 2024.