The Demographic Reports are produced by the Economic, Demographic and Statistical Research unit within the Countywide Service Integration and Planning Management (CSIPM) Division of the Fairfax County Department of Neighborhood and Community Services. Information produced by the Economic, Demographic and Statistical Research unit is used by every county department, board, authority and the Fairfax County Public Schools.

Population weighted centroids are a common tool for spatial analysis, particularly when more granular data is unavailable or researchers lack sophisticated geocoding tools. The ZIP Code Population Weighted Centroids allows researchers and analysts to estimate the center of population in a given geography rather than the geometric center. Data to estimate ZIP code centroids is extracted from administrative USPS address data. The population weighted centroids are based on the number of residential addresses in the component ZIP+4 (also sometimes referred to as 'ZIP9') locations for each ZIP code. The data is based on ZIP+4 centroids, not ZIP Code Tabulation Areas (ZCTAs).To learn more about administrative USPS address data, please visit: https://www.huduser.gov/portal/datasets/usps.htmlData Dictionary: DD_ZIP Code Population Weighted Centroids, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 12/2023

This annual study provides selected income and tax items classified by State, ZIP Code, and the size of adjusted gross income. These data include the number of returns, which approximates the number of households; the number of personal exemptions, which approximates the population; adjusted gross income; wages and salaries; dividends before exclusion; and interest received. Data are based who reported on U.S. Individual Income Tax Returns (Forms 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, ZIP Code Data.

Comprehensive, annually-updated population datasets at ZIP code and administrative levels for 247 countries, spanning from 1975 to 2030, including historical, current, and projected population figures, enriched with attributes like area size, multilingual support, UNLOCODEs, IATA codes, and time zones.

This dataset contains data from California resident tax returns filed with California adjusted gross income and self-assessed tax listed by zip code. This dataset contains data for taxable years 1992 to the most recent tax year available.

Dataset

This dataset was created by Shaswot Joshi

Released under Database: Open Database, Contents: Database Contents

Contents

This data package has the purpose to offer data for demographic indicators, part of 5-years American Community Census, that could be needed in the analysis made along with health-related data or as stand-alone. The American Community Survey based on 5-years estimates is, according to U.S Census Bureau, the most reliable, because the samples used are the largest and the data collected cover all country areas, regardless of the population number.

Zip Code; Population Size; African American; Asian/Pacific Islander; Latino; White; Foreign-born; Speaks a language other than English at home; Single parent households; Households with children; Average household size; 0-5 years; 6-11 years; 12-17 years; 18-24 years; 25-34 years; 35-44 years; 45-54 years; 55-64 years; Ages 65 and older; Ages 17 and younger. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

demographic_statistics_zipcode

This statistic shows the share of zip codes where all homes were unaffordable in selected markets in the United States in 2019. In 2019, 100 percent of homes in **** percent of San Francisco zip codes were unaffordable for buyers earning the local median income.

These datasets contain measures of socioeconomic and demographic characteristics by U.S. census tract for the years 1990-2022 and ZIP code tabulation area (ZCTA) for the years 2008-2022. Example measures include population density; population distribution by race, ethnicity, age, and income; income inequality by race and ethnicity; and proportion of population living below the poverty level, receiving public assistance, and female-headed or single parent families with kids. The datasets also contain a set of theoretically derived measures capturing neighborhood socioeconomic disadvantage and affluence, as well as a neighborhood index of Hispanic, foreign born, and limited English.

Our zip code Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

This statistic shows the share of zip codes where all homes were affordable in selected markets in the United States in 2019. In 2019, 100 percent of homes in 22.5 percent of Pittsburgh zip codes were affordable for buyers earning the local median income.

This dataset provides a Demographic breakdown of only DYCD-funded participants within a Zip Code of NYC. The data displays the counts, and percentages of the participants in each of the following categories: ● Gender (Male, Female, Unknown) ● Ethnicity (Hispanic/Latino, non-Hispanic/non-Latino) ● Race (Pacific Islander, American Indian, Asian, White, Black, Other, Unknown) This data is used to measure the numbers of the different population groups that are served by DYCD for a Borough, and Community.

County of San Diego confirmed COVID cases by zip code. NO LONGER UPDATED. Updated dataset can be found: https://data.sandiegocounty.gov/dataset/COVID-19-Statistics-by-Zip-Code/jtds-js8h

Population by U.S. Postal ZIP Code from the 2020 Decennial Census

Population by 5-year Age Groups by U.S. Postal ZIP Code from the 2010 Decennial Census

The Kresge early childhood interactive map contains data relating to early childhood and education. It is meant to help stakeholders better understand the early childhood landscape better.

This statistic shows the most vacant zip codes in the United States in 2016, by ratio of vacant single-family homes with deceased owner to single-family homes in area. The second most vacant zip code was ***** in Gary, IN with *** in every 52 single-family homes being vacant and having a deceased listed owner.

This statistic shows the risk index scores for zip codes in the United States in 2016, based on environmental housing risks. As of that time, Denver was the city with the highest risk when it comes to environmental hazards. The index was based off of four factors, including: air quality, superfunds on national priorities, brownfield sites, and polluters.