Housing Units by Type by U.S. Postal ZIP Code from the 2020 Decennial Census

US Census American Community Survey (ACS) 2016, 5-year estimates of the key housing characteristics of ZIP Code Tabulation Areas geographic level in Orange County, California. The data contains 406 fields for the variable groups H01: Housing occupancy (universe: total housing units, table X25, 3 fields); H02: Units in structure (universe: total housing units, table X25, 11 fields); H03: Population in occupied housing units by tenure by units in structure (universe: total population in occupied housing units, table X25, 13 fields); H04: Year structure built (universe: total housing units, table X25, 15 fields); H05: Rooms (universe: total housing units, table X25, 18 fields); H06: Bedrooms (universe: total housing units, table X25, 21 fields); H07: Housing tenure by race of householder (universe: occupied housing units, table X25, 51 fields); H08: Total population in occupied housing units by tenure (universe: total population in occupied housing units, table X25, 3 fields); H09: Vacancy status (universe: vacant housing units, table X25, 8 fields); H10: Occupied housing units by race of householder (universe: occupied housing units, table X25, 8 fields); H11: Year householder moved into unit (universe: occupied housing units, table X25, 18 fields); H12: Vehicles available (universe: occupied housing units, table X25, 18 fields); H13: Housing heating fuel (universe: occupied housing units, table X25, 10 fields); H14: Selected housing characteristics (universe: occupied housing units, table X25, 9 fields); H15: Occupants per room (universe: occupied housing units, table X25, 13 fields); H16: Housing value (universe: owner-occupied units, table X25, 32 fields); H17: Price asked for vacant for sale only, and sold not occupied housing units (universe: vacant for sale only, and sold not occupied housing units, table X25, 28 fields); H18: Mortgage status (universe: owner-occupied units, table X25, 10 fields); H19: Selected monthly owner costs, SMOC (universe: owner-occupied housing units with or without a mortgage, table X25, 45 fields); H20: Selected monthly owner costs as a percentage of household income, SMOCAPI (universe: owner-occupied housing units with or without a mortgage, table X25, 26 fields); H21: Contract rent distribution and rent asked distribution in dollars (universe: renter-occupied housing units paying cash rent and vacant, for rent, and rented not occupied housing units, table X25, 7 fields); H22: Gross rent (universe: occupied units paying rent, table X25, 28 fields), and; X23: Gross rent as percentage of household income (universe: occupied units paying rent, table X25, 11 fields). The US Census geodemographic data are based on the 2016 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

Housing Units by Type by U.S. Postal ZIP Code from the SANDAG Vintage 24 Population and Housing Estimates

This layer shows housing units broken down by owner occupied and renter occupied in Tempe Zip Codes.Data is from US Census American Community Survey (ACS) 5-year estimates.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online).A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2016-2020ACS Table(s): S2502 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table downloaded and joined with Zip Code boundaries in the City of Tempe.Date of Census update: March 17, 2022National Figures: data.census.gov

Summary Tape File 3B contains sample data weighted to represent the total population. The collection also contains 100-percent counts and unweighted sample counts for total persons and total housing units. Additional population and housing variables include items such as age, ancestry, disability, citizenship, education, income, marital status, race, sex, travel time to work, rent, tenure, value of housing unit, number of vehicles, and monthly owner costs. The collection includes 178 population tables and 99 housing tables. Data are provided by 5-digit ZIP code within each state, including county portions of the ZIP codes.

Physical Housing Characteristics For Occupied Housing Units Report based on US Census and American Community Survey Data.

Table contains count and percentage of housing units in the county that were built before 1980. 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 B25034; 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 geographyHU_total (Numeric): Total housing unitsHU_before1980 (Numeric): Number of housing units built before 1980pct_before1980 (Numeric): Percent of housing units built before 1980

Key Table Information.Table Title.Selected Housing Characteristics.Table ID.ACSDP1Y2024.DP04.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Data Profiles.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of ...

This dataset identifies demographic and housing estimates including sex and age, race and housing units by zip code tabulation areas within the United States. This dataset resulted from the American Community Survey (ACS) conducted from 2010 through 2014. JSL enriched this dataset with Latitude and Longitude information and with the map information about the land and water area of zip code tabulation areas.

This data collection is a component of Summary Tape File (STF) 3, which consists of four sets of data files containing detailed tabulations of the nation's population and housing characteristics produced from the 1980 Census. The STF 3 files contain sample data inflated to represent the total United States population. The files also contain 100-percent counts and unweighted sample counts of persons and housing units. All files in the STF 3 series are identical, containing 321 substantive data variables organized in the form of 150 "tables," as well as standard geographic identification variables. Population items tabulated for each person include demographic data and information on schooling, Spanish origin, language spoken at home and ability to speak English, labor force status in 1979, residency in 1975, number of children ever born, means of transportation to work, current occupation, industry, and 1979 details on occupation, hours worked, and income. Housing items include size and condition of the housing unit as well as information on value, age, water, sewage and heating, number of vehicles, and monthly owner costs (e.g., sum of payments for real estate taxes, property insurance, utilities, and regular mortgage payments). Selected aggregates and medians are also provided. Each dataset in STF 3 provides different geographic coverage. Summary Tape File 3B provides summaries for each 5-digit ZIP-code area within a state, and for 5-digit ZIP-code areas within states that were contained within Standard Metropolitan Statistical Areas (SMSAs), portions of SMSAs, or within counties, county portions, or county equivalents. All persons and housing units in the United States were sampled. Population and housing items include household relationship, sex, race, age, marital status, Hispanic origin, number of units at address, complete plumbing facilities, number of rooms, whether owned or rented, vacancy status, and value for noncondominiums. The Census Bureau's machine-readable data dictionary for STF 3 is also available through CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: CENSUS SOFTWARE PACKAGE (CENSPAC) VERSION 3.2 WITH STF4 DATA DICTIONARIES (ICPSR 7789), the software package designed specifically by the Census Bureau for use with the 1980 Census data files.

Housing Units by Type by U.S. Postal ZIP Code from the 2000 Decennial Census

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show age, type, vacancy rates, and owner/renter tenure of housing units by Zip Code Tabulation Area in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

Attributes and definitions available below under "Attributes" section and in Infrastructure Manifest (due to text box constraints, attributes cannot be displayed here).

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

Housing Units by Type by U.S. Postal ZIP Code from the Series 13 Regional Growth Forecast

Housing Units by Type by U.S. Postal ZIP Code from the Series 15 Regional Growth Forecast

Housing Units by Type by U.S. Postal ZIP Code from the Series 12 Regional Growth Forecast

Master Area Reference Files (MARFs) link geographic areas with their respective numeric codes. This data collection is a five-digit ZIP-code equivalency file created for the 1980 Census of Population and Housing. The data contain geographic items from Summary Tape Files 1A and 3A, as well as total population and housing unit counts. This equivalency file was created to allow users to prepare additional data summaries relevant to ZIP-code areas. The file enables users to equate detailed record files having ZIP codes with census geographic units. This national file is hierarchically sequenced by geographic area.

This data collection relates ZIP codes to counties, to standard metropolitan statistical areas (SMSAs), and, in New England, to minor civil divisions (MCDs). The relationships between ZIP codes and other geographical units are based on 1979 boundaries, and changes since that time are not reflected. The Census Bureau used various sources to determine ZIP code-county or ZIP code-MCD relationships. In the cases where the sources were confusing or contradictory as to the geographical boundaries of a ZIP code, multiple ZIP-code records (each representing the territory contained in that ZIP-code area) were included in the data file. As a result, the file tends to overstate the ZIP code-county or ZIP code-MCD crossovers. The file is organized by ZIP code and is a byproduct of data used to administer the 1980 Census. Variables include ZIP codes, post office names, FIPS state and county codes, county or MCD names, and SMSA codes.

This feature service outlines relationships between Zip Code Tabulation Areas (ZCTAs) used to denote Small Area Fair Market Rents (SAFMRs) and the Fair Market Rents (FMRs) calculated for Metropolitan Statistical Areas (MSAs) and County geographies. Small Area Fair Market Rents (SAFMRs) are FMRs calculated for ZIP Codes within Metropolitan Areas. Small Area FMRs are required to be used to set Section 8 Housing Choice Voucher payment standards in areas designated by HUD (available here). Other Housing Agencies operating in non-designated metropolitan areas may opt-in to the use of Small Area FMRs. Furthermore, Small Area FMRs may be used as the basis for setting Exception Payment Standards – PHAs may set exception payment standards up to 110 percent of the Small Area FMR. PHAs administering Public Housing units may use Small Area FMRs as an alternative to metropolitan area-wide FMRs when calculating Flat Rents.

Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. There are approximately 1.2 million households living in public housing units, managed by over 3,300 housing agencies (HAs). HUD administers Federal aid to local housing agencies (HAs) that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Public Housing Authorities Date Updated: Q2 2025

Housing Units by Type by U.S. Postal ZIP Code from the Series 14 Regional Growth Forecast