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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 housing units and the group quarters population for states and counties..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..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.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..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..The age dependency ratio is derived by dividing the combined under-18 and 65-and-over populations by the 18-to-64 population and multiplying by 100..The old-age dependency ratio is derived by dividing the population 65 and over by the 18-to-64 population and multiplying by 100..The child dependency ratio is derived by dividing the population under 18 by the 18-to-64 population and multiplying by 100..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..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..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.
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This dataset expands on my earlier New York City Census Data dataset. It includes data from the entire country instead of just New York City. The expanded data will allow for much more interesting analyses and will also be much more useful at supporting other data sets.
The data here are taken from the DP03 and DP05 tables of the 2015 American Community Survey 5-year estimates. The full datasets and much more can be found at the American Factfinder website. Currently, I include two data files:
The two files have the same structure, with just a small difference in the name of the id column. Counties are political subdivisions, and the boundaries of some have been set for centuries. Census tracts, however, are defined by the census bureau and will have a much more consistent size. A typical census tract has around 5000 or so residents.
The Census Bureau updates the estimates approximately every year. At least some of the 2016 data is already available, so I will likely update this in the near future.
The data here were collected by the US Census Bureau. As a product of the US federal government, this is not subject to copyright within the US.
There are many questions that we could try to answer with the data here. Can we predict things such as the state (classification) or household income (regression)? What kinds of clusters can we find in the data? What other datasets can be improved by the addition of census data?
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TwitterThis child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input features in the public supply delivery and water use machine learning models. This page includes the following file: census_data_collector.zip - a zip file containing the census data collector Python code used to retrieve data from the U.S. Census Bureau and a README file.
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Starting in July, data.census.gov will be the primary way to access Census Bureau data, including upcoming releases from the 2018 American Community Survey, 2017 Economic Census, 2020 Census and more. After July 1, 2019, all new data (previously released on American FactFinder) will be released on this new data platform. (https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml)
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TwitterThe Economic Census is the U.S. Government's official five-year measure of American business and the economy. It is conducted by the U.S. Census Bureau, and response is required by law. In October through December of the census year, forms are sent out to nearly 4 million businesses, including large, medium and small companies representing all U.S. locations and industries. Respondents were asked to provide a range of operational and performance data for their companies. This dataset presents company, establishments, value of shipments, value of product shipments, percentage of product shipments of the total value of shipments, and percentage of distribution of value of product shipments.
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The included data are from the Population By Gender & Age tables of the US Census Bureau's American Community Survey's (ACS) 5 year estimates by County. It includes data on the population by Gender and Age Group. For additional information about the data, visit https://www.census.gov/data/developers/data-sets/acs-5year.html.
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The Census Bureau conducts nearly one hundred surveys and censuses every year. By law, no one is permitted to reveal information from these censuses and surveys that could identify any person, household, or business. The Decennial Census collects data every 10 years about households, income, education, homeownership, and more. NOTE: Follow the link and search for SAN FRANCISCO data.
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TwitterThis resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. A tribal census tract is a relatively permanent statistical subdivision of a federally recognized American Indian reservation and/or off-reservation trust land, delineated by the American Indian tribal government and/or the Census Bureau for the purpose of presenting demographic data. For the 2020 Census, tribal census tracts are defined independently of the standard county-based census tract delineation. For federally recognized American Indian Tribes with reservations and/or off-reservation trust lands with a population less than 2,400, a single tribal census tract is defined. Qualifying areas with a population greater than 2,400 could define additional tribal census tracts within their area. The tribal census tract codes for the 2020 Census are six characters long with a leading ""T"" alphabetic character followed by a five-digit numeric code, for example, T01000, which translates as tribal census tract 10. Tribal block groups nest within tribal census tracts. Since individual tabulation blocks are defined within the standard State-county-census tract geographic hierarchy, a tribal census tract can contain seemingly duplicate block numbers, thus tribal census tracts cannot be used to uniquely identify census tabulation blocks for the 2020 Census. The boundaries of tribal census tracts are those delineated through the Participant Statistical Areas Program (PSAP) for the 2020 Census.
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TwitterCensus Tracts from the 2020 US Census for New York City clipped to the shoreline. These boundary files are derived from the US Census Bureau's TIGER project and have been geographically modified to fit the New York City base map. Because some census tracts are under water not all census tracts are contained in this file, only census tracts that are partially or totally located on land have been mapped in this file.
All previously released versions of this data are available on the DCP Website: BYTES of the BIG APPLE. Current version: 25d
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U.S. Census Bureau; TIGER/Line Shapefiles 2019 Data accessed from: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2019.html
TIGER/Line Shapefiles do not include demographic data, but they do contain geographic entity codes (GEOIDs) that can be linked to the Census Bureau’s demographic data.
The Geographic Areas Reference Manual (GARM) describes in great detail the basic geographic entities the Census Bureau uses (https://www.census.gov/programs-surveys/acs/geography-acs.html).
TIGER Data Products Guide (https://www.census.gov/programs-surveys/geography/guidance/tiger-data-products-guide.html)
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.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..For more information on understanding race and Hispanic origin data, please see the Census 2010 Brief entitled, Overview of Race and Hispanic Origin: 2010, issued March 2011. (pdf format).The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.
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TwitterThe United States census count (also known as the Decennial Census of Population and Housing) is a count of every resident of the US. The census occurs every 10 years and is conducted by the United States Census Bureau. Census data is publicly available through the census website, but much of the data is available in summarized data and graphs. The raw data is often difficult to obtain, is typically divided by region, and it must be processed and combined to provide information about the nation as a whole. Update frequency: Historic (none)
United States Census Bureau
SELECT
zipcode,
population
FROM
bigquery-public-data.census_bureau_usa.population_by_zip_2010
WHERE
gender = ''
ORDER BY
population DESC
LIMIT
10
This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/united-states-census-bureau/us-census-data
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Key Table Information.Table Title.Special District Governments by Function: U.S. and State: 2012 - 2022.Table ID.GOVSTIMESERIES.CG00ORG08.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2023-08-24.Release Schedule.For information about Census of Governments planned data product releases, see https://www.census.gov/programs-surveys/gus/newsroom/updates.html.Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Special District Governments - Single-function - Air transportationSpecial District Governments - Single-function - CemeteriesSpecial District Governments - Single-function - Drainage and flood controlSpecial District Governments - Single-function - EducationSpecial District Governments - Single-function - Fire protectionSpecial District Governments - Single-function - HighwaysSpecial District Governments - Single-function - HospitalsSpecial District Governments - Single-function - Housing and community developmentSpecial District Governments - Single-function - Industrial development and mortgage creditSpecial District Governments - Single-function - LibrariesSpecial District Governments - Single-function - Other natural resourcesSpecial District Governments - Single-function - Other single function districtsSpecial District Governments - Single-function - Other transportationSpecial District Governments - Single-function - Other utility districtsSpecial District Governments - Single-function - Parks and recreationSpecial District Governments - Single-function - Sewerage...
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The Monthly State Retail Sales (MSRS) is the Census Bureau's new experimental data product featuring modeled state-level retail sales. This is a blended data product using Monthly Retail Trade Survey data, administrative data, and third-party data. Year-over-year percentage changes are available for Total Retail Sales excluding Non-store Retailers as well as 11 retail North American Industry Classification System (NAICS) retail subsectors. These data are provided by state and NAICS codes beginning with January 2019.
Geography: US
Time period: 2019 - 2022
Unit of analysis: US Census Bureau's Monthly State Retail Sales Data
| Variable | Description |
|---|---|
| fips | 2-digit State Federal Information Processing Standards (FIPS) code. For more information on FIPS Codes, please reference this document. Note: The US is assigned a "00" State FIPS code. |
| state_abbr | States are assigned 2-character official U.S. Postal Service Code. The United States is assigned "USA" as its state_abbr value. For more information, please reference this document. |
| naics | Three-digit numeric NAICS value for retail subsector code. |
| subsector | Retail subsector. |
| year | Year. |
| month | Month. |
| change_yoy | Numeric year-over-year percent change in retail sales value. |
| change_yoy_se | Numeric standard error for year-over-year percentage change in retail sales value. |
| coverage_code | Character values assigned based on the non-imputed coverage of the data. |
| Variable | Description |
|---|---|
| coverage_code | Character values assigned based on the non-imputed coverage of the data. |
| coverage | Definition of the codes. |
Datasource: United States Census Bureau's Monthly State Retail Sales
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Release Date: 2020-12-17.Release Schedule:.The data in this file come from the 2017 Economic Census. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments of firms with payroll...Data Items and Other Identifying Records:.Number of establishments.Sales, value of shipments, or revenue ($1,000).Sales on own account ($1,000).Purchases ($1,000).Total inventories, beginning of year ($1,000).Total inventories, end of year ($1,000).Cost of goods sold ($1,000).Gross margin ($1,000).Gross margin as percent of sales on own account (%)..Geography Coverage:.The data are shown for employer establishments at the U.S. level only. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown at the 2- through 7-digit and selected 8-digit 2017 NAICS code levels. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector42/EC1742MARGIN.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..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, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.
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Twitter2020 Census P.L. 94-171 is the first detailed data release from the 2020 Decennial Census of Population and Housing. The web layer is based on an extract for Table P1 – Race at the place level geography of Broward County, Florida. The data extract was then joined to the 2020 Census TIGER/Line Shapefiles.
For details on field names, table hierarchy, and table contents refer to TABLE (MATRIX) SECTION in Chapter 6. Data Dictionary, https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_StatesTechDoc_English.pdf" STYLE="text-decoration:underline;">2020 Census State Public Law 94-171 Summary File Technical Documentation.
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Twitter2020 Census P.L. 94-171 is the first detailed data release from the 2020 Decennial Census of Population and Housing. The web layer is based on an extract for Table P4 – Hispanic or Latino, and Not Hispanic or Latino by Race for the Population 18 Years and Over at the census tract level geography of Broward County, Florida. The data extract was then joined to the 2020 Census TIGER/Line Shapefiles.
For details on field names, table hierarchy, and table contents refer to TABLE (MATRIX) SECTION in Chapter 6. Data Dictionary, https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/2020Census_PL94_171Redistricting_StatesTechDoc_English.pdf" STYLE="text-decoration:underline;">2020 Census State Public Law 94-171 Summary File Technical Documentation.
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TwitterLink to the Open Data site for the United States Census Bureau.
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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 housing units and the group quarters population for states and counties..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..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.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..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..The age dependency ratio is derived by dividing the combined under-18 and 65-and-over populations by the 18-to-64 population and multiplying by 100..The old-age dependency ratio is derived by dividing the population 65 and over by the 18-to-64 population and multiplying by 100..The child dependency ratio is derived by dividing the population under 18 by the 18-to-64 population and multiplying by 100..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..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..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.