Neighborhood boundaries in Chicago, as developed by the Office of Tourism. These boundaries are approximate and names are not official. To view or use these files, compression software and special GIS software, such as ESRI ArcGIS, is required.

Dataset

This dataset was created by threadid

Released under Other (specified in description)

Contents

The rental housing developments listed below are among the thousands of affordable units that are supported by City of Chicago programs to maintain affordability in local neighborhoods. The list is updated periodically when construction is completed for new projects or when the compliance period for older projects expire, typically after 30 years. The list is provided as a courtesy to the public. It does not include every City-assisted affordable housing unit that may be available for rent, nor does it include the hundreds of thousands of naturally occurring affordable housing units located throughout Chicago without City subsidies. For information on rents, income requirements and availability for the projects listed, contact each property directly. For information on other affordable rental properties in Chicago and Illinois, call (877) 428-8844, or visit www.ILHousingSearch.org.

KML file of neighborhood boundaries in Chicago, as developed by the Office of Tourism. These boundaries are approximate and names are not official. To view or use these files, special GIS software, such as Google Earth, is required.

Historical dataset of population level and growth rate for the Chicago metro area from 1950 to 2025.

Public Health Indicators in Chicago

Natality, Mortality, Infectious Disease, Lead Poisoning and Economic Status

By City of Chicago [source]

About this dataset

This public health dataset contains a comprehensive selection of indicators related to natality, mortality, infectious disease, lead poisoning, and economic status from Chicago community areas. It is an invaluable resource for those interested in understanding the current state of public health within each area in order to identify any deficiencies or areas of improvement needed.

The data includes 27 indicators such as birth and death rates, prenatal care beginning in first trimester percentages, preterm birth rates, breast cancer incidences per hundred thousand female population, all-sites cancer rates per hundred thousand population and more. For each indicator provided it details the geographical region so that analyses can be made regarding trends on a local level. Furthermore this dataset allows various stakeholders to measure performance along these indicators or even compare different community areas side-by-side.

This dataset provides a valuable tool for those striving toward better public health outcomes for the citizens of Chicago's communities by allowing greater insight into trends specific to geographic regions that could potentially lead to further research and implementation practices based on empirical evidence gathered from this comprehensive yet digestible selection of indicators

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How to use the dataset

In order to use this dataset effectively to assess the public health of a given area or areas in the city: - Understand which data is available: The list of data included in this dataset can be found above. It is important to know all that are included as well as their definitions so that accurate conclusions can be made when utilizing the data for research or analysis. - Identify areas of interest: Once you are familiar with what type of data is present it can help to identify which community areas you would like to study more closely or compare with one another. - Choose your variables: Once you have identified your areas it will be helpful to decide which variables are most relevant for your studies and research specific questions regarding these variables based on what you are trying to learn from this data set.
- Analyze the Data : Once your variables have been selected and clarified take right into analyzing the corresponding values across different community areas using statistical tests such as t-tests or correlations etc.. This will help answer questions like “Are there significant differences between two outputs?” allowing you to compare how different Chicago Community Areas stack up against each other with regards to public health statistics tracked by this dataset!

Research Ideas

• Creating interactive maps that show data on public health indicators by Chicago community area to allow users to explore the data more easily.
• Designing a machine learning model to predict future variations in public health indicators by Chicago community area such as birth rate, preterm births, and childhood lead poisoning levels.
• Developing an app that enables users to search for public health information in their own community areas and compare with other areas within the city or across different cities in the US

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: public-health-statistics-selected-public-health-indicators-by-chicago-community-area-1.csv | Column name | Description | |:-----------------------------------------------|:--------------------------------------------------------------------------------------------------| | Community Area | Unique identifier for each community area in Chicago. (Integer) | | Community Area Name | Name of the community area in Chicago. (String) | | Birth Rate | Number of live births per 1,000 population. (Float) | | General Fertility Rate | Number of live births per 1,000 women aged 15-44. (Float) ...

This dataset contains a selection of 27 indicators of public health significance by Chicago community area, with the most updated information available. The indicators are rates, percents, or other measures related to natality, mortality, infectious disease, lead poisoning, and economic status. See the full description at https://data.cityofchicago.org/api/assets/BB7058D2-E8A1-4E11-86CE-6CF1738F0A02.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. 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. 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 Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

A dataset listing Illinois cities by population for 2024.

Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org.

This dataset contains a selection of 27 indicators of public health significance by Chicago community area, with the most updated information available. The indicators are rates, percents, or other measures related to natality, mortality, infectious disease, lead poisoning, and economic status. See the full description at https://data.cityofchicago.org/api/assets/2107948F-357D-4ED7-ACC2-2E9266BBFFA2.

In 2023, the population of the Chicago-Naperville-Elgin metropolitan area in the United States was about 9.26 million people. This was a slight decrease from the previous year, which was about 9.27 million.

Context

The City of Chicago's open data portal lets you find city data, lets you find facts about your neighborhood, lets you create maps and graphs about the city, and lets you freely download the data for your own analysis. Many of these datasets are updated at least once a day, and many of them are updated several times a day... [Ref: https://data.cityofchicago.org/#about]

Content

Latitude and longitude data of each Chicago Neighborhood.

Neighborhood boundaries in Chicago, as developed by the Office of Tourism. These boundaries are approximate and names are not official. 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.

Vacant property owned and managed by the City of Chicago Department of Housing and Economic Development. Information provided in the database, or on the City’s website generally, should not be used as a substitute for title research, title evidence, title insurance, real estate tax exemption or payment status, environmental or geotechnical due diligence, or as a substitute for legal, accounting, real estate, business, tax or other professional advice. The City assumes no liability for any damages or loss of any kind that might arise from the reliance upon, use of, misuse of, or the inability to use the LIS database or the City’s web site and the materials contained on the website. The City also assumes no liability for improper or incorrect use of materials or information contained on its website. All materials that appear in the LIS database or on the City’s web site are distributed and transmitted "as is," without warranties of any kind, either express or implied as to the accuracy, reliability or completeness of any information, and subject to the terms and conditions stated in this disclaimer.

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 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.

This map is part of a collection of 10 maps showing the location of Presbyterian Churches in relation to ethnic groups in the city of Chicago. The manuscript title is "The effects of subsity of Presbyterian Churches", by Henry Hughes Presler, and can be found at Mansueto Library, University of Chicago under the call number BX 10999. These maps have been outlined and vectorized as the originals, and points placed for location of churches as they were in the original. Call number for the maps: G4104.C6E1 1948.H6. Map Collection, Regenstein Library, University of Chicago. Drawn from Map 10 - Churches in Hinterland of Chicago Presbytery, 1940.

Despite much recent attention devoted to understanding the ramifications of residential mobility, especially negative consequences for youth, there is scant research exploring how inner-city mobility impacts youth violence and victimization among minorities and immigrants. Leaving the city imparts benefits: decreasing deviance and improving youth outcomes. Considering that many are unable to "escape" the city, clarifying what effects, if any, inner-city mobility has is critical. Destination neighborhoods for youth who move in the city are either contextually the same, better, or worse than their original neighborhood. Evidence suggests that immigrant families are more likely to move as are racial minorities. Because of this, the researchers examined the extent to which moving within a city affects minority and immigrant youth experiences, particularly in relation to changes in neighborhood collective efficacy; a major characteristic shaping community crime rates and youth violence. This project involved four main goals: identify key characteristics of the destination neighborhoods and those who are moving within the city of Chicago; understand how inner-city mobility of minority and immigrant youth affects engagement in violence and victimization; determine whether vertical or horizontal mobility with respect to key neighborhood factors differentially influences minority and immigrant youth outcomes; assess who fares better - youth who vertically move (to better or worse neighborhoods), those who do not move, or those who horizontally move (to equivalent neighborhoods). This research used data from the Project on Human Development in Chicago Neighborhoods (PHDCN). Data were drawn from both the Longitudinal Cohort Study (N=1,611) and Community Survey (N=97). The rich data from the Community Survey affords the opportunity to examine how community characteristics like collective efficacy, disorder, and indicators of social disorganization can impact a variety of youth behaviors among at-risk youth over time between Wave 1 and Wave 2 and Wave 2 and Wave 3. The Longitudinal Cohort Study provides data on youth characteristics and experiences with violence, and ecological information on family and peer relationships. The investigators focused primarily on three of the seven youth cohorts from the Longitudinal Cohort Study: 9, 12, and 15. The ages of these youth during the study period place them at increased risk for exposure to community violence, and place them in range for aging into, peaking, or aging out of crime and delinquency. The Longitudinal Cohort Study respondents are nested in neighborhood clusters and multilevel models are employed to assess the outcomes victimization and violence within neighborhood context. The researchers employed a series of hierarchical generalized linear models using HLM 7 in addition to running several analyses of variance (ANOVA) permitting examinations between groups of interest.

This survey was conducted as part of the Citizen Participation and Community Crime Prevention project at the Center for Urban Affairs and Policy Research, Northwestern University. The project was conducted to gain a deeper understanding of the wide range of activities in which the American public engages to be secure from crime. In particular, this survey was designed to identify the scope of anti-crime activities and investigate the processes that facilitate or inhibit the public's involvement in those activities. The geographical area for the survey was defined by the "commuting basin" of Chicago, excluding several independent cities and their suburbs (e.g., Aurora, Waukegan, and Joliet) on the northern and western fringes of that area, and excluding all areas in Indiana. Interviewing was carried out by the Survey Research Laboratory at the University of Illinois during June through August 1979. Information was gathered on people's opinions toward safety, their involvement with crime prevention activities, and the quality of life in their neighborhoods. In addition, data were assembled from Census Bureau and police reports for each community area in which respondents lived in the years immediately preceding the survey.

Abstract (en): The Project on Human Development in Chicago Neighborhoods (PHDCN) was a large-scale, interdisciplinary study of how families, schools, and neighborhoods affect child and adolescent development. One component of the PHDCN was the Longitudinal Cohort Study, which was a series of coordinated longitudinal studies that followed over 6,000 randomly selected children, adolescents, and young adults, and their primary caregivers over time to examine the changing circumstances of their lives, as well as the personal characteristics, that might lead them toward or away from a variety of antisocial behaviors. Numerous measures were administered to respondents to gauge various aspects of human development, including individual differences, as well as family, peer, and school influences. The Substance Use interview was a self-report measure administered to Cohorts 6, 9, 12, 15, and 18 to obtain information regarding the subject's use of specific drugs. Project on Human Development in Chicago Neighborhoods The Project on Human Development in Chicago Neighborhoods (PHDCN) was a large-scale, interdisciplinary study of how families, schools, and neighborhoods affect child and adolescent development. It was designed to advance the understanding of the developmental pathways of both positive and negative human social behaviors. In particular, the project examined the causes and pathways of juvenile delinquency, adult crime, substance abuse, and violence. At the same time, the project provided a detailed look at the environments in which these social behaviors took place by collecting substantial amounts of data about urban Chicago, including its people, institutions, and resources. Longitudinal Cohort Study One component of the PHDCN was the Longitudinal Cohort Study, which was a series of coordinated longitudinal studies that followed over 6,000 randomly selected children, adolescents, and young adults, and their primary caregivers over time to examine the changing circumstances of their lives, as well as the personal characteristics, that might lead them toward or away from a variety of antisocial behaviors. The age cohorts include birth (0), 3, 6, 9, 12, 15, and 18 years. Numerous measures were administered to respondents to gauge various aspects of human development, including individual differences, as well as family, peer, and school influences. Substance Use The data in this collection are from Wave 3 of the Longitudinal Cohort Study, which was administered between 2000 and 2002. The data files contain information from the Substance Use protocol. The Substance Use instrument was a self-report measure administered to Cohorts 6, 9, 12, 15, and 18 to obtain information regarding the subject's use of specific drugs. Project on Human Development in Chicago Neighborhoods The city of Chicago was selected as the research site for the PHDCN because of its extensive racial, ethnic, and social-class diversity. The project collapsed 847 census tracts in the city of Chicago into 343 neighborhood clusters (NCs) based upon seven groupings of racial/ethnic composition and three levels of socioeconomic status. The NCs were designed to be ecologically meaningful. They were composed of geographically contiguous census tracts, and geographic boundaries, and knowledge of Chicago's neighborhoods were considered in the definition of the NCs. Each NC was comprised of approximately 8,000 people. Longitudinal Cohort Study For the Longitudinal Cohort Study, a stratified probability sample of 80 neighborhoods was selected. The 80 NCs were sampled from the 21 strata (seven racial/ethnic groups by three socioeconomic levels) with the goal of representing the 21 cells as equally as possible to eliminate the confounding between racial/ethnic mix and socioeconomic status. Once the 80 NCs were chosen, then block groups were selected at random within each of the sample neighborhoods. A complete listing of dwelling units was collected for all sampled block groups. Pregnant women, children, and young adults in seven age cohorts (birth, 3, 6, 9, 12, 15, and 18 years) were identified through in-person screening of approximately 40,000 dwelling units within the 80 NCs. The screening response rate was 80 percent. Children within six months of the birthday that qualified them for the sample were selected for inclusion in the Longitudinal Cohort Study. A total of 8,347 participants were identified through the screening. Of the eligible study participants, 6...