Table from the American Community Survey (ACS) 5-year series on age and gender related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B01001 Sex by Age, B01002 Median Age by Sex. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B01001, B01002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. 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 estima

This layer shows the age statistics in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This file contains demographic, social, economic, and housing information from the "100-percent" and unweighted sample counts from the 1980 census for locally defined neighborhoods. The Neighborhood Publication Area (NPA) is the total area within which neighborhoods were defined by each participant in the Neighborhood Statistics Program (NSP), which was developed by the Census Bureau. Population items include age, race, sex, marital status, Spanish origin, employment status, and language spoken at home. Housing items include occupancy/vacancy status, tenure, contract rent, value, condominium status, number of rooms, and plumbing facilities.

This dataset reflects reported incidents of crime that have occurred in the City of Chicago over the past year, minus the most recent seven days of data. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited.

The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. Any use of the information for commercial purposes is strictly prohibited. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily.

Business Analyst Neighborhood Demographics Feature Service

This polygon feature class contains Neighborhood Statistical Areas (NSAs) based on Census Tracts within Newport News, Virginia.. There are relatively permanent statistical subdivisions of a county or statistically equivalent entity delineated by local participants as part of the U.S. Census Bureau's Participant Statistical Areas Program. For more information on NSAs, visit the US Census Bureau.

In 2022, the New Orleans-Metairie, LA metro area recorded the highest homicide rate of U.S. cities with a population over 250,000, at 27.1 homicides per 100,000 residents, followed by the Memphis, TN-MS-AR metro area. However, homicide data was not recorded in all U.S. metro areas, meaning that there may be some cities with a higher homicide rate.

St. Louis

St. Louis, which had a murder and nonnegligent manslaughter rate of 11.6 in 2022, is the second-largest city by population in Missouri. It is home to many famous treasures such as the St. Louis Cardinals baseball team, Washington University in St. Louis, the Saint Louis Zoo, and the renowned Gateway Arch. It is home to many corporations such as Monsanto, Arch Coal, and Emerson Electric. The economy of St. Louis is centered around business and healthcare, and in addition is home to ten Fortune 500 companies.

Crime in St. Louis

Despite all of this, St. Louis suffers from high levels of crime and violence. As of 2023, it was listed as the seventh most dangerous city in the world as a result of their extremely high murder rate. Not only does St. Louis have one of the highest homicide rates in the United States, it also reports one of the highest numbers of violent crimes. In spite of high crime levels, the GDP of the St. Louis metropolitan area has been increasing since 2001.

NSP Production Reports contain cumulative data on units assisted with NSP funds. An NSP grantee reports on the accomplishment of an activity when it meets an End Use, such as providing down payment assistance to an eligible household, demolition of a blighted property, or acquiring and rehabbing a foreclosed property and selling it to an eligible owner occupant. These reports include three Summary Reports of aggregated data for all NSP1, NPS2 and NSP3 grantees, as well as individual state reports for the NSP1 and NSP3 programs. The NSP2 Summary Report does not include State and Local Government data, as NSP2 funding was awarded through a competitive process that includes non-profit organizations. It should also be noted that where the data indicate State vs. Local Government, State refers to the state grantees while Local Government refers to the municipal and urban county grantees.

Population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2023 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries as of July 1, 2023. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/)released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Fields:CT20: 2020 Census tractFIP22: 2023 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2023) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP23CSA: 2020 census tract with 2023 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP23_AGE_0_4: 2023 population 0 to 4 years oldPOP23_AGE_5_9: 2023 population 5 to 9 years old POP23_AGE_10_14: 2023 population 10 to 14 years old POP23_AGE_15_17: 2022 population 15 to 17 years old POP23_AGE_18_19: 2023 population 18 to 19 years old POP23_AGE_20_44: 2023 population 20 to 24 years old POP23_AGE_25_29: 2023 population 25 to 29 years old POP23_AGE_30_34: 2023 population 30 to 34 years old POP23_AGE_35_44: 2023 population 35 to 44 years old POP23_AGE_45_54: 2023 population 45 to 54 years old POP23_AGE_55_64: 2023 population 55 to 64 years old POP23_AGE_65_74: 2023 population 65 to 74 years old POP23_AGE_75_84: 2023 population 75 to 84 years old POP23_AGE_85_100: 2023 population 85 years and older POP23_WHITE: 2023 Non-Hispanic White POP23_BLACK: 2023 Non-Hispanic African AmericanPOP23_AIAN: 2023 Non-Hispanic American Indian or Alaska NativePOP23_ASIAN: 2023 Non-Hispanic Asian POP23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific IslanderPOP23_HISPANIC: 2023 HispanicPOP23_MALE: 2023 Male POP23_FEMALE: 2023 Female POV23_WHITE: 2023 Non-Hispanic White below 100% Federal Poverty Level POV23_BLACK: 2023 Non-Hispanic African American below 100% Federal Poverty Level POV23_AIAN: 2023 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV23_ASIAN: 2023 Non-Hispanic Asian below 100% Federal Poverty Level POV23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV23_HISPANIC: 2023 Hispanic below 100% Federal Poverty Level POV23_TOTAL: 2023 Total population below 100% Federal Poverty Level POP23_TOTAL: 2023 Total PopulationAREA_SQMil: Area in square mile.POP23_DENSITY: 2023 Population per square mile.POV23_PERCENT: 2023 Poverty rate/percentage.How this data created?Population by age groups, ethnic groups and gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Notes:1. Population and poverty data estimated as of July 1, 2023. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundaries are as of July 1, 2023.

The median age indicates the age separating the population group into two halves of equal size.

The 2017-2018 School Neighborhood Poverty Estimates are based on school locations from the 2017-2018 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2014-2018 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

All BPD data on Open Baltimore is preliminary data and subject to change. The information presented through Open Baltimore represents Part I victim based crime data. The data do not represent statistics submitted to the FBI's Uniform Crime Report (UCR); therefore any comparisons are strictly prohibited. For further clarification of UCR data, please visit http://www.fbi.gov/about-us/cjis/ucr/ucr. Please note that this data is preliminary and subject to change. Prior month data is likely to show changes when it is refreshed on a monthly basis. All data is geocoded to the approximate latitude/longitude location of the incident and excludes those records for which an address could not be geocoded. Any attempt to match the approximate location of the incident to an exact address is strictly prohibited.

Table of Census Demographics represented at the NYC Community District level

Financial overview and grant giving statistics of Neighborhood Housing Services

This provides the population statistics of each neighborhood in the West District of Chiayi City in 2025, with statistical data collected every month.

This dataset represents neighborhood level data derived from the American Community Survey; 5 year average, years 2011-2015. Data was aggregated at the census tract level, and then summarized into neighborhoods. This information was then joined with the Community Planning and Developments Neighborhoods layer. This data does not contain data for any enclaves administered by other jurisdictions that are located within the City and County of Denver's boundary. This data is a sample, not a census. Results should be considered estimates. See American Community Survey website for margin of error information.

Contains data on Community Services Statistics for October 2024 and a provisional data file for November 2024 (note this is intended as an early view until providers submit a refresh of their data).

Table of ACS Demographics and profile represented at the NTA level. NTAs are aggregations of census tracts that are subsets of New York City's 55 Public Use Microdata Areas (PUMAs)

Context

With a population just short of 3 million people, the city of Toronto is the largest in Canada, and one of the largest in North America (behind only Mexico City, New York and Los Angeles). Toronto is also one of the most multicultural cities in the world, making life in Toronto a wonderful multicultural experience for all. More than 140 languages and dialects are spoken in the city, and almost half the population Toronto were born outside Canada.It is a place where people can try the best of each culture, either while they work or just passing through. Toronto is well known for its great food.

Content

This dataset was created by doing webscraping of Toronto wikipedia page . The dataset contains the latitude and longitude of all the neighborhoods and boroughs with postal code of Toronto City,Canada.

From February 29 to June 1, 2020, there were 268 deaths due to COVID-19 per 100,000 population in very high poverty neighborhoods in New York City, compared to a rate of around 125 deaths per 100,000 population in low poverty neighborhoods. This statistic illustrates the rate of deaths for COVID-19 in New York City from February 29 to June 1, 2020, by neighborhood poverty.