Selected variables from the most recent 5 year ACS Community Survey (Released 2023) aggregated by Ward. Additional years will be added as they become available. The underlying algorithm to create the dataset calculates the percent of a census tract that falls within the boundaries of a given ward. Given that census tracts and ward boundaries are not aligned, these figures should be considered an estimate. Total Population in this Dataset: 2,649,803 Total Population of Chicago reported by ACS 2023: 2,664,452 % Difference: %-0.55 There are different approaches in common use for displaying Hispanic or Latino population counts. In this dataset, following the approach taken by the Census Bureau, a person who identifies as Hispanic or Latino will also be counted in the race category with which they identify. However, again following the Census Bureau data, there is also a column for White Not Hispanic or Latino. The City of Chicago is actively soliciting community input on how best to represent race, ethnicity, and related concepts in its data and policy. Every dataset, including this one, has a "Contact dataset owner" link in the Actions menu. You can use it to offer any input you wish to share or to indicate if you would be interested in participating in live discussions the City may host. Code can be found here: https://github.com/Chicago/5-Year-ACS-Survey-Data Ward Shapefile: https://data.cityofchicago.org/Facilities-Geographic-Boundaries/Boundaries-Wards-2023-Map/cdf7-bgn3 Census Area Python Package Documentation: https://census-area.readthedocs.io/en/latest/index.html

This dataset contains American Community Survey (ACS) data aggregated by ward. The current ACS vintage is for 2019-2023. Values are calculated by aggregating all the census tracts that fall within a given ward. If a census tract falls across two or more wards, the ward which contains most of the census tract's blocks is assigned said tract. Click here to learn more about how this process works.Update FrequencyThis dataset is updated annually when the new ACS vintage is released.This dataset is featured on the following app(s):Ward Census DashboardCity Census ViewerContactsSamuel Martinez, Urban Analytics and Innovationsmartinez2@clevelandohio.govData GlossaryTo view more information about individual fields, navigate to Data -> Fields.Methodology1. Get all census tracts within Cuyahoga county. 2. Determine which census tracts are within the city of Cleveland. a. If a census tract falls over multiple city boundaries, the city that contains more of that census tract’s blocks is assigned to said census tract. 3. Filter the dataset for census tracts within Cleveland. 4. Determine which census tracts are within which wards. a. If a census tract falls across two or more wards, whichever ward contains most of that tract’s blocks is assigned. 5. Aggregate counts for different ACS variables across census tracts within each ward. This results in the final estimates.

The following links provide a summarized demographic profile for each of the Wards and Superwards in the City of Norfolk. A citywide profile is also provided. City staff used ESRI ArcGIS software to create the demographic estimates. ESRI compiles data from the US Census Bureau and American Community Survey (ACS) to generate estimates based off provided custom geographic areas. The data used to create these visuals is not meant to represent Norfolk's authoritative source for City, Ward, or elections purposes. ESRI and ACS Demographics represent annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics. Detailed information on ESRI information can be found at https://doc.arcgis.com/en/esri-demographics/latest/regional-data/updated-demographics.htm

Rates of confirmed COVID-19 in Ottawa Wards, excluding LTC and RH cases, and number of cases in LTCH and RH in Ottawa Wards. Data are provided for all cases (i.e. cumulative), cases reported within 30 days of the data pull (i.e. last 30 days), and cases reported within 14 days of the data pull (i.e. last 14 days). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day prior to publication.Rates of confirmed COVID-19 in Ottawa Wards, excluding LTC and RH cases, and number of cases in LTCH and RH in Ottawa Wards. Data are provided for all cases (i.e. cumulative), cases reported within 30 days of the data pull (i.e. last 30 days), and cases reported within 14 days of the data pull (i.e. last 14 days). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day prior to publication. You can see the map on Ottawa Public Health's website.Accuracy: Points of consideration for interpretation of the data:Data extracted by Ottawa Public Health at 2pm from the COVID-19 Ottawa Database (The COD) on May 12th, 2020. The COD is a dynamic disease reporting system that allow for continuous updates of case information. These data are a snapshot in time, reflect the most accurate information that OPH has at the time of reporting, and the numbers may differ from other sources. Cases are assigned to Ward geography based on their postal code and Statistics’ Canada’s enhanced postal code conversion file (PCCF+) released in January 2020. Most postal codes have multiple geographic coordinates linked to them. Thus, when available, postal codes were attributed to a XY coordinates based on the Single Link Identifier provided by Statistics’ Canada’s PCCF+. Otherwise, postal codes that fall within the municipal boundaries but whose SLI doesn’t, were attributed to the first XY coordinates within Ottawa listed in the PCCF+. For this reason, results for rural areas should be interpreted with caution as attribution to XY coordinates is less likely to be based on an SLI and rural postal codes typically encompass a much greater surface area than urban postal codes (e.i. greater variability in geographic attribution, less precision in geographic attribution). Population estimates are based on the 2016 Census. Rates calculated from very low case numbers are unstable and should be interpreted with caution. Low case counts have very wide 95% confidence intervals, which are the lower and upper limit within which the true rate lies 95% of the time. A narrow confidence interval leads to a more precise estimate and a wider confidence interval leads to a less precise estimate. In other words, rates calculated from very low case numbers fluctuate so much that we cannot use them to compare different areas or make predictions over time.Update Frequency: Biweekly Attributes:Ward Number – numberWard Name – textCumulative rate (per 100 000 population), excluding cases linked to outbreaks in LTCH and RH – cumulative number of residents with confirmed COVID-19 in a Ward, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardCumulative number of cases, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward, excluding cases linked to outbreaks in LTCH and RHCumulative number of cases linked to outbreaks in LTCH and RH - Number of residents with confirmed COVID-19 linked to an outbreak in a long-term care home or retirement home by WardRate (per 100 000 population) in the last 30 days, excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardNumber of cases in the last 30 days, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding cases linked to outbreaks in LTCH and RHNumber of cases in the last 30 days linked to outbreaks in LTCH and RH - Number of residents with confirmed COVID-19, reported in the 30 days prior to the data pull, linked to an outbreak in a long-term care home or retirement home by WardRate (per 100 000 population) in the last 14 days, excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardNumber of cases in the last 14 days, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding cases linked to outbreaks in LTCH and RHContact: OPH Epidemiology Team

List of alderman, office address, phone number, and website for all 50 Chicago wards. To attempt to make historical versions of this dataset more available, "Dataset Changelog" is enabled at the bottom of the main page. We cannot guarantee that the archival records will remain permanently so advise downloading any you think you may want. Some intermediate versions, especially minor changes, may not be visible. The map based on this dataset will not have past versions.

The VA National Bed Control System records the levels of operating, unavailable and authorized beds at each VAMC, and it tracks requests for changes in these levels. For changes in operating, unavailable and authorized bed levels, the Director of a Medical Center or his/her authorized delegate enters a bed change request into the Bed Control Database. A Bed Control Database trigger automatically notifies the respective Veterans Integrated Support Network (VISN) director. The VISN director's designated staff reviews the request and either approves, disapproves, or cancels it through the Bed Control Database. If a medical center request is approved by the VISN director, a Bed Control Database trigger notifies staff in the Assistant Deputy Under Secretary for Health for Operations and Management (10N) to review and take action, followed by the appropriate VHA Program Office and then the Under Secretary for Health. Once a request has been approved, cancelled, or disapproved by either the Deputy Under Secretary for Health for Operations and Management, VHA Program Office, or the Under Secretary for Health, the medical center director and the appropriate VISN director are automatically notified of the action. The approval process is tracked and visible to the authorized user of the system. When changes are approved, the database updates its bed level information accordingly. Pertinent justification and documents associated with each bed change request are stored in the database.

Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber]). Current Vintage: 2019-2023. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: 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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

Ward boundaries in Chicago from May 2003 to May 2015, corresponding to the dates when a new City Council is sworn in, based on the immediately preceding elections. Neither this description nor the dataset should be relied upon in situations where legal precision is required. The data can be viewed on the Chicago Data Portal with a web browser. However, to view or use the files outside of a web browser, you will need to use compression software and special GIS software, such as ESRI ArcGIS (shapefile) or Google Earth (KML or KMZ), is required.

Comprehensive dataset of 46 Internal medicine wards in Texas, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 2 Internal medicine wards in West Virginia, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 74 Internal medicine wards in California, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This service is the City Ward map. The City of East Point is divided into 4 wards. Each ward is represented by 2 elected Council Members.

About this dataset

Context

The dataset tabulates the population of Ward by race. It includes the population of Ward across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Ward across relevant racial categories.

Key observations

The percent distribution of Ward population by race (across all racial categories recognized by the U.S. Census Bureau): 100% are white.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Ward
• Population: The population of the racial category (excluding ethnicity) in the Ward is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Ward total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Ward Population by Race & Ethnicity. You can refer the same here

Refer to the current geographies boundaries table for a list of all current geographies and recent updates.

This dataset is the definitive version of the annually released ward boundaries as at 1 January 2025, as defined by the territorial authorities and/or Local Government Commission and maintained by Stats NZ. This version contains 224 wards, excluding ‘area outside ward’.

Wards are defined under the Local Electoral Act 2001 and result from dividing a territorial authority for electoral purposes. Wards were originally set up within any territorial authority with a population of at least 20,000. The ward system was designed to allow for the recognition of communities within a territorial authority and to increase community involvement in the local government system.

Territorial authorities can now choose whether they would like to maintain electoral wards. As a result, the number of wards has steadily decreased since they were first created in 1989. Ward boundaries are reviewed in the year before the three-yearly local government elections.

Wards are defined at meshblock level, and do not coincide with the statistical area 1 (SA1), statistical area 2 (SA2), or statistical area 3 (SA3) geographies.

Numbering

Wards are numbered based on their corresponding territorial authority. Each ward has a unique five-digit number. The first three digits represent the territorial authority that the ward lies within. The following two digits are sequential and represent the number of wards within a territorial authority. For example, Westland District (057) has three wards, which are coded 05701, 05702, and 05703.

Some territorial authorities do not use wards. In the classification, these territorial authorities use ‘99’ for the last two digits of the ward code, and the descriptor “Area Outside Ward”.

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High-definition version

This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

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Macrons

Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

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Digital data

Digital boundary data became freely available on 1 July 2007.

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Further information

To download geographic classifications in table formats such as CSV please use Ariā

For more information please refer to the Statistical standard for geographic areas 2023.

Contact: geography@stats.govt.nz

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) Database (MTDB). The MTDB 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. Edge refers to the linear topological primitives that make up MTDB. The All Lines Shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the All Lines Shapefile are available in relationship (.dbf) files that users must download separately. The All Lines Shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value.

Administrative Boundaries of Indian Villages with demographic data like Population, Sex, Household, etc

Ward Boundaries of 1663 Cities

Attributes: Ward Boundaries, Population, Gender, Sex, and household

Ward Boundaries of 1663 Cities

Attributes: Ward Boundaries, Population, Gender, Sex, and household

Land Use Statistics by ward (Generalised Land Use Database) 2005 (Enhanced Basemap). Uses include, domestic buildings, gardens, non-domestic buildings, greenspace, paths, rail, road and water.

Area is presented in Thousands of square metres ('000s m2).

These are experimental Statistics - this information has been developed in accordance with the principles set out in the National Statistics Code of Practice but has yet to be fully accredited as a National Statistic.

Communities and Local Government consider the 2005 figures to be the definitive land use statistics. No further work is planned on the Generalised Land Use Database.

The statistics have been calculated for each ward. Generalised Land Use Database (GLUD) 2005 (Enhanced Basemap) statistics are available for a number of other administrative areas such as output areas and local authorities from http://www.neighbourhood.statistics.gov.uk/

Open this dataset aggregated to borough level.

This dataset contains polygons features representing neighborhood Ward and Representatives in the City of Norfolk.

The dataset is available using the link:https://norfolkgisdata-orf.opendata.arcgis.com/datasets/18726a8e41ba4a9685d450925bc1a8b6_7/about

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) Database (MTDB). The MTDB 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. Edge refers to the linear topological primitives that make up MTDB. The All Lines Shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the All Lines Shapefile are available in relationship (.dbf) files that users must download separately. The All Lines Shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value.

The Historical Urban Ecological (HUE) data project was created for exploring and analyzing the urban health environments of seven major United States cities - Baltimore, Boston, Brooklyn, Chicago, Cincinnati, Manhattan, and Philidelphia - from 1830 through 1930. The data for each city includes ward boundary changes, street networks, and ward-level data on disease, mortality, crime, and other variables reported by municipal departments. The HUE data set was produced for the "Early Indicators of Later Work Levels, Disease and Death" project, funded by the National Institute of Aging. This collection represents the GIS data for each of the seven American cities, and in addition to ward boundary changes and street networks, includes in-street sewer and water sanitation systems coverage. All cities except Cincinnati include sanitation infrastructure data, and for Baltimore only water infrastructure is available. The city of Chicago includes supplemental GIS layers which reflect a reconstruction of two of Homer Hoyt's maps of average land value (1933 dollars) in the City of Chicago for 1873 and 1892. The square mile areas defined by Hoyt using Chicago's system of mile streets have been fit to the HUE street centerlines for Chicago. The Excel data tables include information about deaths in each ward broken down by cause of death, age, race, gender, as well as information about live births and deliveries.