100+ datasets found
  1. Crime Rate and GDP Datasets 2021 & 2023

    • kaggle.com
    Updated May 28, 2024
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    Fran Llamas (2024). Crime Rate and GDP Datasets 2021 & 2023 [Dataset]. https://www.kaggle.com/datasets/franllamas/crime-rate-and-gdp-datasets-2021-and-2023
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 28, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Fran Llamas
    Description

    Overview:

    This project aims to investigate the potential correlation between the Gross Domestic Product (GDP) of approximately 190 countries for the years 2021 and 2023 and their corresponding crime ratings. The crime ratings are represented on a scale from 0 to 10, with 0 indicating minimal or null crime activity and 10 representing the highest level of criminal activity.

    Dataset:

    The dataset used in this project comprises GDP data for the years 2021 and 2023 for around 190 countries, sourced from reputable international databases. Additionally, crime rating scores for the same countries and years are collected from credible sources such as governmental agencies, law enforcement organizations, or reputable research institutions.

    Methodology:

    • Data Collection: GDP data for 2021 and 2023, along with crime rating scores, are gathered for approximately 190 countries.
    • Data Preprocessing: The collected data is cleaned and standardized to ensure consistency and compatibility across different datasets.
    • Analysis: Statistical methods and data visualization techniques are employed to explore the potential relationship between GDP and crime ratings.
    • Interpretation: Findings from the analysis are interpreted to determine the strength and direction of any observed correlations between GDP and crime ratings.
    • Conclusion: Based on the analysis results, conclusions are drawn regarding the existence and significance of the relationship between GDP and crime ratings.

    Expected Outcomes:

    Identification of any significant correlations or patterns between GDP and crime ratings across different countries. Insights into the potential socioeconomic factors influencing crime rates and their relationship with economic indicators like GDP. Implications for policymakers, law enforcement agencies, and researchers in understanding the dynamics between economic development and crime prevalence.

  2. United States Crime Rates By City Population

    • kaggle.com
    zip
    Updated Dec 28, 2022
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    kabhishm (2022). United States Crime Rates By City Population [Dataset]. https://www.kaggle.com/datasets/kabhishm/united-states-crime-rates-by-city-population
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    zip(40122 bytes)Available download formats
    Dataset updated
    Dec 28, 2022
    Authors
    kabhishm
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

    FILE DESCRIPTION

    File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

    COLUMN DESCRIPTION

    For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

    FILE DESCRIPTION

    File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

    COLUMN DESCRIPTION

    For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

    crime_60 _100.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

    crime_100 _250.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

    crime_250 _plus.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'total_crime': total crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'total_violent _crime': total violent crime - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft - 'tot_prop _crime': total property crime - 'arson': arson

    Photo by David von Diemar on Unsplash

  3. Number, percentage and rate of homicide victims, by racialized identity...

    • www150.statcan.gc.ca
    • data.urbandatacentre.ca
    • +3more
    Updated Jul 22, 2025
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    Government of Canada, Statistics Canada (2025). Number, percentage and rate of homicide victims, by racialized identity group, gender and region [Dataset]. http://doi.org/10.25318/3510020601-eng
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    Dataset updated
    Jul 22, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.

  4. Number, rate and percentage changes in rates of homicide victims

    • www150.statcan.gc.ca
    • datasets.ai
    • +1more
    Updated Jul 22, 2025
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    Government of Canada, Statistics Canada (2025). Number, rate and percentage changes in rates of homicide victims [Dataset]. http://doi.org/10.25318/3510006801-eng
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    Dataset updated
    Jul 22, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number, rate and percentage changes in rates of homicide victims, Canada, provinces and territories, 1961 to 2024.

  5. Homicide rates in Brazil

    • kaggle.com
    zip
    Updated Mar 31, 2025
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    willian oliveira (2025). Homicide rates in Brazil [Dataset]. https://www.kaggle.com/datasets/willianoliveiragibin/homicide-rates-in-brazil
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    zip(37098 bytes)Available download formats
    Dataset updated
    Mar 31, 2025
    Authors
    willian oliveira
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Brazil
    Description

    Measuring homicides across the world helps us understand violent crime and how people are affected by interpersonal violence.

    But measuring homicides is challenging. Even homicide researchers do not always agree on whether the specific cause of death should be considered a homicide. Even when they agree on what counts as a homicide, it is difficult to count all of them.

    In many countries, national civil registries do not certify most deaths or their cause. Besides lacking funds and personnel, a body has to be found to determine whether a death has happened. Authorities may also struggle to distinguish a homicide from a similar cause of death, such as an accident.

    Law enforcement and criminal justice agencies collect more data on whether a death was unlawful — but their definition of unlawfulness may differ across countries and time.

    Estimating homicides where neither of these sources is available or good enough is difficult. Estimates rely on inferences from similar countries and contextual factors that are based on strong assumptions. So how do researchers address these challenges and measure homicides?

    In our work on homicides, we provide data from five main sources:

    The WHO Mortality Database (WHO-MD)1 The Global Study on Homicide by the UN Office on Drugs and Crime (UNODC)2 The History of Homicide Database by Manuel Eisner (20033 and 20144) The Global Burden of Disease (GBD) study by the Institute for Health Metrics and Evaluation (IHME)5 The WHO Global Health Estimates (WHO-GHE)6 These sources all report homicides, cover many countries and years, and are frequently used by researchers and policymakers. They are not entirely separate, as they partially build upon each other.

  6. o

    First In Line for Murder: police stations with highest murder rates -...

    • open.africa
    Updated Oct 20, 2015
    + more versions
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    (2015). First In Line for Murder: police stations with highest murder rates - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/first-in-line-for-murder-police-stations-with-highest-murder-rates
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    Dataset updated
    Oct 20, 2015
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The 20 police stations as at 31 Jul 2015 with the highest murder rates per 100 000 population in South Africa, using the mid-term population figures released annually by Statistics SA (which are based on the 2011 census data). Research by Lizette Lancaster, ISS Manager at the Crime and Justice Information Hub, Governance, Crime and Justice Division, ISS Pretoria and Ellen Kamman, Independent Researcher

  7. Reported violent crime rate in the U.S. 1990-2023

    • statista.com
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    Statista, Reported violent crime rate in the U.S. 1990-2023 [Dataset]. https://www.statista.com/statistics/191219/reported-violent-crime-rate-in-the-usa-since-1990/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

  8. d

    Mass Killings in America, 2006 - present

    • data.world
    csv, zip
    Updated Dec 1, 2025
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    The Associated Press (2025). Mass Killings in America, 2006 - present [Dataset]. https://data.world/associatedpress/mass-killings-public
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    zip, csvAvailable download formats
    Dataset updated
    Dec 1, 2025
    Authors
    The Associated Press
    Time period covered
    Jan 1, 2006 - Nov 29, 2025
    Area covered
    Description

    THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

    OVERVIEW

    2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

    In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

    A total of 229 people died in mass killings in 2019.

    The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

    One-third of the offenders died at the scene of the killing or soon after, half from suicides.

    About this Dataset

    The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

    The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

    This data will be updated periodically and can be used as an ongoing resource to help cover these events.

    Using this Dataset

    To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

    Mass killings by year

    Mass shootings by year

    To get these counts just for your state:

    Filter killings by state

    Definition of "mass murder"

    Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

    This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

    Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

    Methodology

    Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

    Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

    In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

    Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

    Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

    This project started at USA TODAY in 2012.

    Contacts

    Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

  9. Violent Crime Rate

    • data.ca.gov
    • healthdata.gov
    • +3more
    pdf, xlsx, zip
    Updated Nov 7, 2025
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    California Department of Public Health (2025). Violent Crime Rate [Dataset]. https://data.ca.gov/dataset/violent-crime-rate
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    xlsx, pdf, zipAvailable download formats
    Dataset updated
    Nov 7, 2025
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This table contains data on the rate of violent crime (crimes per 1,000 population) for California, its regions, counties, cities and towns. Crime and population data are from the Federal Bureau of Investigations, Uniform Crime Reports. Rates above the city/town level include data from city, university and college, county, state, tribal, and federal law enforcement agencies. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Ten percent of all deaths in young California adults aged 15-44 years are related to assault and homicide. In 2010, California law enforcement agencies reported 1,809 murders, 8,331 rapes, and over 95,000 aggravated assaults. African Americans in California are 11 times more likely to die of assault and homicide than Whites. More information about the data table and a data dictionary can be found in the About/Attachments section.

  10. Violent Crime in CA

    • kaggle.com
    Updated Jan 28, 2023
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    The Devastator (2023). Violent Crime in CA [Dataset]. https://www.kaggle.com/datasets/thedevastator/violent-crime-in-ca
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 28, 2023
    Dataset provided by
    Kaggle
    Authors
    The Devastator
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    California
    Description

    Violent Crime in CA

    Regional, County, City/Town Rates 2006-2010

    By Health [source]

    About this dataset

    This dataset contains information on the rate of violent crime across California - its regions, counties, cities and towns. The data was collected as part of a larger effort by the Office of Health Equity to better understand public health indicators and ensure equitable outcomes for all.

    The numbers reflect more than just a problem in California communities - it reflects a problem with unequal access to resources and opportunity across race, ethnicities and geographies. African Americans in California are 11 times more likely to die from assault or homicide compared to white Californians. Similarly, certain regions report higher crime rates than others at the county level- indicating underlying issues with poverty or institutionalized inequality.

    Law enforcement agencies teamed up with the Federal Bureau of Investigations’ Uniform Crime Reports to collect this data table which includes details such as reported number of violent crimes (numerator), population size (denominator), rate per 1,000 population (ratex1000) confidence intervals (LL_95CI & UL_95CI ) standard errors & relative standard errors (se & rse) as well as ratios between city/town rates vs state rates (RR_city2state). Additionally, each record is classified according to region name/code and race/ethnicity code/name , giving researchers further insight into these troubling statistics at both macro and micro levels.

    Armed with this information we can explore new ways identify inequitable areas and begin looking for potential solutions that combat health disparities within our communities like never before!

    More Datasets

    For more datasets, click here.

    Featured Notebooks

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    How to use the dataset

    The data is presented with twenty columns providing various segments within each row including:

    • Crime definition
    • Race/ethnicity code
    • Region code
    • Geographic area identifier
    • Numerator and Denominator values of population
    • Standard Error and 95% Confidence Intervals
    • Relatvie Standard Error (RSE) value
    • Ratios related to city/towns rate to state rate

      The information provided can be used for a variety of applications such as creating visualizations or developing predictive models. It is important to note that rates are expressed per 1,000 population for their respective geographic area during each period noted by the report year field within the dataset. Additionally CA_decile column may be useful in comparing counties due numerical grading system identifying a region’s percentile ranking when compared to other counties within the current year’s entire dataset as well as ratios present under RR_city2state which presents ratio comparison between city/town rate and state rate outside given geographic area have made this an extremely valuable dataset for further analysis

    Research Ideas

    • Developing a crime prediction and prevention program that uses machine learning models to identify criminal hotspots and direct resources to those areas
    • Exploring the connection between race/ethnicity and rates of violence in California
    • Creating visualizations and interactive maps to display types of violent crime across different counties within California

    Acknowledgements

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

    License

    License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

    Columns

    File: Violent_Crime_Rate_California_2006-2010-DD.csv

    File: rows.csv | Column name | Description ...

  11. C

    Violent Crime Rate

    • data.ccrpc.org
    csv
    Updated Nov 20, 2024
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    Champaign County Regional Planning Commission (2024). Violent Crime Rate [Dataset]. https://data.ccrpc.org/dataset/violent-crime-rate
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    csvAvailable download formats
    Dataset updated
    Nov 20, 2024
    Dataset authored and provided by
    Champaign County Regional Planning Commission
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    The violent crime rate indicator includes both the total number of violent crime incidents per year in Champaign County, and the number of violent crime incidents per 100,000 people per year in Champaign County. “Violent crimes” are those counted in the following categories in the Illinois State Police’s annual Crime in Illinois report: Criminal Homicide, Criminal Sexual Assault (Rape), Robbery, Aggravated Assault, and Aggravated Battery. The incidence of violent crime is an integral part of understanding the safety of a given community.

    Both the total number of offenses in Champaign County and the rate per 100,000 population were significantly lower in 2021 than at the start of the measured time period, 1996. The most recent rise in both of these figures was in 2019-2020, before falling again in 2021. The year with the lowest number of total offenses and the rate per 100,000 population in the study period was 2015; both measures are slightly higher since then.

    This data is sourced from the Illinois State Police’s annually released Crime in Illinois: Annual Uniform Crime Report, available on the Uniform Crime Report Index Offense Explorer.

    Sources: Illinois State Police. (2021). Crime in Illinois: Annual Uniform Crime Report 2021. Illinois State Police. (2020). Crime in Illinois: Annual Uniform Crime Report 2020. Illinois State Police. (2019). Crime in Illinois: Annual Uniform Crime Report 2019. Illinois State Police. (2018). Crime in Illinois: Annual Uniform Crime Report 2018. Illinois State Police. (2017). Crime in Illinois: Annual Uniform Crime Report 2017.Illinois State Police. (2016). Crime in Illinois: Annual Uniform Crime Report 2016. Illinois State Police. (2015). Crime in Illinois: Annual Uniform Crime Report 2015. Illinois State Police. (2014). Crime in Illinois: Annual Uniform Crime Report 2014.; Illinois State Police. (2012). Crime in Illinois: Annual Uniform Crime Report 2012.; Illinois State Police. (2011). Crime in Illinois: Annual Uniform Crime Report 2010-2011.; Illinois State Police. (2009). Crime in Illinois: Annual Uniform Crime Report 2009.; Illinois State Police. (2007). Crime in Illinois: Annual Uniform Crime Report 2007.; Illinois State Police. (2005). Crime in Illinois: Annual Uniform Crime Report 2005.; Illinois State Police. (2003). Crime in Illinois: Annual Uniform Crime Report 2003.; Illinois State Police. (2001). Crime in Illinois: Annual Uniform Crime Report 2001.; Illinois State Police. (1999). Crime in Illinois: Annual Uniform Crime Report 1999.; Illinois State Police. (1997). Crime in Illinois: Annual Uniform Crime Report 1997.

  12. Data from: Homicides in New York City, 1797-1999 [And Various Historical...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Nov 14, 2025
    + more versions
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    National Institute of Justice (2025). Homicides in New York City, 1797-1999 [And Various Historical Comparison Sites] [Dataset]. https://catalog.data.gov/dataset/homicides-in-new-york-city-1797-1999-and-various-historical-comparison-sites-f1e29
    Explore at:
    Dataset updated
    Nov 14, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    New York
    Description

    There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

  13. C

    murder rates

    • data.cityofchicago.org
    Updated Nov 23, 2025
    + more versions
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    Chicago Police Department (2025). murder rates [Dataset]. https://data.cityofchicago.org/Public-Safety/murder-rates/ej5x-8yqr
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    kml, xlsx, xml, application/geo+json, csv, kmzAvailable download formats
    Dataset updated
    Nov 23, 2025
    Authors
    Chicago Police Department
    Description

    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

  14. World Crime Index 2023

    • kaggle.com
    zip
    Updated Jun 17, 2023
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    Arsalan ur Rehman (2023). World Crime Index 2023 [Dataset]. https://www.kaggle.com/datasets/arsalanrehman/world-crime-index-2023/code
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    zip(6480 bytes)Available download formats
    Dataset updated
    Jun 17, 2023
    Authors
    Arsalan ur Rehman
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    World
    Description

    The World Crime Index 2023 dataset provides records of crime rankings for cities worldwide, along with associated information on their respective countries. This dataset is focused on the year 2023 and includes the following columns:

    • Rank: The ranking of a city based on its crime index, with lower numbers indicating higher crime rates.
    • City: The name of the city for which crime data is reported.
    • Country: The country to which the city belongs.
    • Crime Index: A numerical value representing the overall level of crime in a city, with higher values indicating higher crime rates.
    • Safety Index: An index indicating the general level of safety in a city, derived from factors such as infrastructure, healthcare, and political stability.

    This dataset enables data scientists to analyze and compare crime rankings across cities and countries, providing insights into the relative safety levels of different locations in the year 2023. By leveraging this dataset, researchers can conduct exploratory data analysis, perform comparative studies, and identify potential trends and patterns in crime rates globally for the specified year.

  15. l

    Violent Crime Rate

    • data.lacounty.gov
    • ph-lacounty.hub.arcgis.com
    • +1more
    Updated Dec 19, 2023
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    County of Los Angeles (2023). Violent Crime Rate [Dataset]. https://data.lacounty.gov/datasets/violent-crime-rate
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    Dataset updated
    Dec 19, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  16. Police-recorded offences by NUTS 3 region

    • ec.europa.eu
    Updated Oct 10, 2025
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    Eurostat (2025). Police-recorded offences by NUTS 3 region [Dataset]. http://doi.org/10.2908/CRIM_GEN_REG
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    application/vnd.sdmx.genericdata+xml;version=2.1, application/vnd.sdmx.data+xml;version=3.0.0, application/vnd.sdmx.data+csv;version=1.0.0, json, tsv, application/vnd.sdmx.data+csv;version=2.0.0Available download formats
    Dataset updated
    Oct 10, 2025
    Dataset authored and provided by
    Eurostathttps://ec.europa.eu/eurostat
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2008 - 2023
    Area covered
    Galicia, Vukovarsko-srijemska županija, Zuid-Holland (NUTS 2021), Bistriţa-Năsăud, Valladolid, Dobrich, Çankırı, Sinop, Kastamonu, Srednjobanatska oblast, Potsdam-Mittelmark, Targovishte
    Description

    Crime regional data are police-recorded offences. The data are collected at regional level for European Union Member States, EFTA countries, and potential EU members where NUTS3 is relevant and available. National data are presented in the dataset for countries where NUTS3 is not relevant (Cyprus, Luxembourg, Liechtenstein, Montenegro as the whole territory is one single NUTS region) or still not available (Bosnia and Herzegovina and Kosovo - this designation is without prejudice to positions on status, and is in line with UNSCR 1244/1999 and the ICJ Opinion on the Kosovo declaration of independence).

    From 2008 onwards, the statistics include police-recorded offences for homicide, assault, sexual violence, robbery, burglary, (of which) burglary of residential premises, theft, (of which) theft of motorized land vehicle.

  17. Crime Risk Database, MSA

    • search.dataone.org
    Updated Oct 14, 2013
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne (2013). Crime Risk Database, MSA [Dataset]. https://search.dataone.org/view/knb-lter-bes.110.570
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    Dataset updated
    Oct 14, 2013
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne
    Time period covered
    Jan 1, 2004 - Nov 17, 2011
    Area covered
    Description

    Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

  18. Crime rate U.S. 2023, by state

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Crime rate U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/301549/us-crimes-committed-state/
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    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the state with the highest crime rate in the United States per 100,000 inhabitants was New Mexico. That year, the crime rate was ******** crimes per 100,000 people. In comparison, New Hampshire had the lowest crime rate at ****** crimes per 100,000 people. Crime rate The crime rate in the United States has generally decreased over time. There are several factors attributed to the decrease in the crime rate across the United States. An increase in the number of police officers and an increase in income are some of the reasons for a decrease in the crime rate. Unfortunately, people of color have been disproportionately affected by crime rates, as they are more likely to be arrested for a crime versus a white person. Crime rates regionally The District of Columbia had the highest rate of reported violent crimes in the United States in 2023 per 100,000 inhabitants. The most common crime clearance type in metropolitan counties in the United States in 2020 was murder and non-negligent manslaughter. The second most dangerous city in the country in 2020 was Detroit. Detroit has faced severe levels of economic and demographic declines in the past years. Not only has the population decreased, the city has filed for bankruptcy. Despite the median household income increasing, the city still struggles financially.

  19. NCHS - Drug Poisoning Mortality by State: United States

    • catalog.data.gov
    • data.virginia.gov
    • +6more
    Updated Apr 23, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). NCHS - Drug Poisoning Mortality by State: United States [Dataset]. https://catalog.data.gov/dataset/nchs-drug-poisoning-mortality-by-state-united-states
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances. REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

  20. Number and rate of homicide victims, by Census Metropolitan Areas

    • www150.statcan.gc.ca
    • open.canada.ca
    Updated Jul 22, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Number and rate of homicide victims, by Census Metropolitan Areas [Dataset]. http://doi.org/10.25318/3510007101-eng
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    Dataset updated
    Jul 22, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

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Fran Llamas (2024). Crime Rate and GDP Datasets 2021 & 2023 [Dataset]. https://www.kaggle.com/datasets/franllamas/crime-rate-and-gdp-datasets-2021-and-2023
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Crime Rate and GDP Datasets 2021 & 2023

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CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 28, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Fran Llamas
Description

Overview:

This project aims to investigate the potential correlation between the Gross Domestic Product (GDP) of approximately 190 countries for the years 2021 and 2023 and their corresponding crime ratings. The crime ratings are represented on a scale from 0 to 10, with 0 indicating minimal or null crime activity and 10 representing the highest level of criminal activity.

Dataset:

The dataset used in this project comprises GDP data for the years 2021 and 2023 for around 190 countries, sourced from reputable international databases. Additionally, crime rating scores for the same countries and years are collected from credible sources such as governmental agencies, law enforcement organizations, or reputable research institutions.

Methodology:

  • Data Collection: GDP data for 2021 and 2023, along with crime rating scores, are gathered for approximately 190 countries.
  • Data Preprocessing: The collected data is cleaned and standardized to ensure consistency and compatibility across different datasets.
  • Analysis: Statistical methods and data visualization techniques are employed to explore the potential relationship between GDP and crime ratings.
  • Interpretation: Findings from the analysis are interpreted to determine the strength and direction of any observed correlations between GDP and crime ratings.
  • Conclusion: Based on the analysis results, conclusions are drawn regarding the existence and significance of the relationship between GDP and crime ratings.

Expected Outcomes:

Identification of any significant correlations or patterns between GDP and crime ratings across different countries. Insights into the potential socioeconomic factors influencing crime rates and their relationship with economic indicators like GDP. Implications for policymakers, law enforcement agencies, and researchers in understanding the dynamics between economic development and crime prevalence.

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