66 datasets found
  1. C

    Violence Reduction - Victim Demographics - Aggregated

    • data.cityofchicago.org
    • s.cnmilf.com
    • +1more
    csv, xlsx, xml
    Updated Sep 30, 2025
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    City of Chicago (2025). Violence Reduction - Victim Demographics - Aggregated [Dataset]. https://data.cityofchicago.org/Public-Safety/Violence-Reduction-Victim-Demographics-Aggregated/gj7a-742p
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    xml, xlsx, csvAvailable download formats
    Dataset updated
    Sep 30, 2025
    Dataset authored and provided by
    City of Chicago
    Description

    This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

    This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

    The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

    How does this dataset classify victims?

    The methodology by which this dataset classifies victims of violent crime differs by victimization type:

    Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

    To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

    For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

    1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
    2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

    Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

    1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

    Note: All businesses identified as victims in CPD data have been removed from this dataset.

    Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

    Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

    Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

  2. Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race, United...

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated Jul 25, 2024
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    United States. Federal Bureau of Investigation (2024). Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race, United States, 2021 [Dataset]. http://doi.org/10.3886/ICPSR38795.v1
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    stata, spss, ascii, delimited, r, sasAvailable download formats
    Dataset updated
    Jul 25, 2024
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Federal Bureau of Investigation
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38795/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38795/terms

    Time period covered
    2021
    Area covered
    United States
    Description

    These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 43 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

  3. Murder in the U.S.: number of victims in 2023, by race

    • statista.com
    Updated Nov 7, 2024
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    Statista (2024). Murder in the U.S.: number of victims in 2023, by race [Dataset]. https://www.statista.com/statistics/251877/murder-victims-in-the-us-by-race-ethnicity-and-gender/
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the FBI reported that there were 9,284 Black murder victims in the United States and 7,289 white murder victims. In comparison, there were 554 murder victims of unknown race and 586 victims of another race. Victims of inequality? In recent years, the role of racial inequality in violent crimes such as robberies, assaults, and homicides has gained public attention. In particular, the issue of police brutality has led to increasing attention following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Studies show that the rate of fatal police shootings for Black Americans was more than double the rate reported of other races. Crime reporting National crime data in the United States is based off the Federal Bureau of Investigation’s new crime reporting system, which requires law enforcement agencies to self-report their data in detail. Due to the recent implementation of this system, less crime data has been reported, with some states such as Delaware and Pennsylvania declining to report any data to the FBI at all in the last few years, suggesting that the Bureau's data may not fully reflect accurate information on crime in the United States.

  4. AH Excess Deaths by Sex, Age, and Race and Hispanic Origin

    • catalog.data.gov
    • data.virginia.gov
    • +4more
    Updated Apr 23, 2025
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    Centers for Disease Control and Prevention (2025). AH Excess Deaths by Sex, Age, and Race and Hispanic Origin [Dataset]. https://catalog.data.gov/dataset/ah-excess-deaths-by-sex-age-and-race-2d26a
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Weekly data on the number of deaths from all causes by sex, age group, and race/Hispanic origin group for the United States. Counts of deaths in more recent weeks can be compared with counts from earlier years (2015-2019) to determine if the number is higher than expected.

  5. Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race,...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    Bureau of Justice Statistics (2025). Uniform Crime Reporting Program Data: Arrests by Age, Sex, and Race, Summarized Yearly, United States, 2010 [Dataset]. https://catalog.data.gov/dataset/uniform-crime-reporting-program-data-arrests-by-age-sex-and-race-summarized-yearly-united--34e1e
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Area covered
    United States
    Description

    These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing, per reporting police agency: an agency header record, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to logical record length format with the agency header record variables copied onto the detail records. Consequently, each record contains arrest counts for a particular agency-offense.

  6. AH Monthly Provisional Counts of Deaths for Select Causes of Death by Sex,...

    • catalog.data.gov
    • data.virginia.gov
    • +3more
    Updated Apr 23, 2025
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    Centers for Disease Control and Prevention (2025). AH Monthly Provisional Counts of Deaths for Select Causes of Death by Sex, Age, and Race and Hispanic Origin [Dataset]. https://catalog.data.gov/dataset/monthly-provisional-counts-of-deaths-by-age-group-sex-and-race-ethnicity-for-select-causes
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Provisional counts of deaths by the month the deaths occurred, by age group, sex, and race/ethnicity, for select underlying causes of death for 2020-2021. Final data are provided for 2019. The dataset also includes monthly provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death.

  7. Number of murder offenders 2023, by race

    • statista.com
    Updated Nov 7, 2024
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    Statista (2024). Number of murder offenders 2023, by race [Dataset]. https://www.statista.com/statistics/1466623/murder-offenders-in-the-us-by-race/
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, 8,842 murderers in the United States were white, while 6,405 were Black. A further 461 murderers were of another race, including American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander. However, not all law enforcement agencies submitted homicide data to the FBI in 2023, meaning there may be more murder offenders of each race than depicted. While the majority of circumstances behind murders in the U.S. are unknown, narcotics, robberies, and gang killings are most commonly identified.

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

    • www150.statcan.gc.ca
    • data.urbandatacentre.ca
    • +2more
    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.

  9. Number of murder offenders in the U.S. 2023, by gender

    • statista.com
    Updated Nov 7, 2024
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    Statista (2024). Number of murder offenders in the U.S. 2023, by gender [Dataset]. https://www.statista.com/statistics/251886/murder-offenders-in-the-us-by-gender/
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, there were 14,327 murder offenders in the United States who were male, in comparison to 1,898 who were female. However, there were also 5,279 murder offenders where their gender was unknown. Homicides in the U.S. Murder and non-negligent manslaughter in the United States is defined as the willful killing of another human being. Justifiable homicides, or cases where a felon is killed by an officer in the line of duty or a felon is killed during a felony by a private citizen, are not included in murder counts by the Federal Bureau of Investigation (FBI). The total number of murders varies from state to state in the U.S., with more populous states having higher numbers of murders. Murder offenders and victims Most murder offenders in the United States are between the ages of 17 and 39, with the number of offenders declining steadily after age 40. Additionally, the highest rate of death by homicide was found among males between the ages of 15 and 24. The highest rate of death by homicide for females was for girls under the age of one.

  10. AH Quarterly Excess Deaths by State, Sex, Age, and Race

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • odgavaprod.ogopendata.com
    • +4more
    Updated Apr 23, 2025
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    Centers for Disease Control and Prevention (2025). AH Quarterly Excess Deaths by State, Sex, Age, and Race [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/ah-quarterly-excess-deaths-by-state-sex-age-and-race-010d6
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    Dataset updated
    Apr 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Quarterly data on the number of deaths from all causes by state (of occurrence), sex, age group, and race/Hispanic origin group for the United States. Counts of deaths in more recent time periods can be compared with counts from earlier years (2015-2019) to determine if the number is higher than expected. Annual and cumulative counts (from Quarter 2, 2020 through the most recent quarter) are also shown.

  11. Homicide in the U.S. - number of victims 2023, by age

    • statista.com
    Updated Nov 7, 2024
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    Statista (2024). Homicide in the U.S. - number of victims 2023, by age [Dataset]. https://www.statista.com/statistics/251878/murder-victims-in-the-us-by-age/
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, around 2,444 homicide victims in the United States were aged between 20 and 24 years old. A further 2,362 murder victims were between the ages of 30 and 34 years old. Most murder victims in the United States in 2023 were between the ages of 17 and 54 years old.

  12. AH Cumulative Provisional COVID-19 Deaths by Sex, Race, and Age from...

    • data.virginia.gov
    • datahub.hhs.gov
    • +4more
    csv, json, rdf, xsl
    Updated Apr 21, 2025
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    Centers for Disease Control and Prevention (2025). AH Cumulative Provisional COVID-19 Deaths by Sex, Race, and Age from 1/1/2020 to 7/28/2020 [Dataset]. https://data.virginia.gov/dataset/ah-cumulative-provisional-covid-19-deaths-by-sex-race-and-age-from-1-1-2020-to-7-28-2020
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    xsl, csv, rdf, jsonAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Cumulative provisional counts of deaths sex, race/Hispanic origin, age group, and by select underlying causes of death. The dataset also includes provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death. Includes deaths that occurred between January 1, 2020 to July 28, 2020.

  13. Number, percentage and rate of homicide victims, by gender and Indigenous...

    • www150.statcan.gc.ca
    Updated Jul 27, 2021
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    Government of Canada, Statistics Canada (2021). Number, percentage and rate of homicide victims, by gender and Indigenous identity [Dataset]. http://doi.org/10.25318/3510015601-eng
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    Dataset updated
    Jul 27, 2021
    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 gender (all genders; male; female; gender unknown) and Indigenous identity (total; Indigenous identity; non-Indigenous identity; unknown Indigenous identity), Canada, provinces and territories, 2014 to 2020.

  14. Cumulative Provisional Counts of Deaths by Sex, Race, and Age - mskm-2qbg -...

    • healthdata.gov
    application/rdfxml +5
    Updated Jul 16, 2025
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    (2025). Cumulative Provisional Counts of Deaths by Sex, Race, and Age - mskm-2qbg - Archive Repository [Dataset]. https://healthdata.gov/dataset/Cumulative-Provisional-Counts-of-Deaths-by-Sex-Rac/sdha-jppy
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    application/rdfxml, csv, application/rssxml, xml, json, tsvAvailable download formats
    Dataset updated
    Jul 16, 2025
    Description

    This dataset tracks the updates made on the dataset "Cumulative Provisional Counts of Deaths by Sex, Race, and Age" as a repository for previous versions of the data and metadata.

  15. COVID-19 Weekly Cases and Deaths by Age, Race/Ethnicity, and Sex - ARCHIVED

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Feb 23, 2025
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    Centers for Disease Control and Prevention (2025). COVID-19 Weekly Cases and Deaths by Age, Race/Ethnicity, and Sex - ARCHIVED [Dataset]. https://data.virginia.gov/dataset/covid-19-weekly-cases-and-deaths-by-age-race-ethnicity-and-sex-archived
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    rdf, json, csv, xslAvailable download formats
    Dataset updated
    Feb 23, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    Note: Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

    This table summarizes COVID-19 case and death data submitted to CDC as case reports for the line-level dataset. Case and death counts are stratified according to sex, age, and race and ethnicity at regional and national levels. Data for US territories are included in case and death counts, but not population counts. Weekly cumulative counts with five or fewer cases or deaths are not reported to protect confidentiality of patients. Records with unknown or missing sex, age, or race and ethnicity and of multiple, non-Hispanic race and ethnicity are included in case and death totals. COVID-19 case and death data are provisional and are subject to change. Visualization of COVID-19 case and death rate trends by demographic variables may be viewed on COVID Data Tracker (https://covid.cdc.gov/covid-data-tracker/#demographicsovertime).

  16. o

    Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program...

    • openicpsr.org
    Updated Jun 1, 2017
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    Jacob Kaplan (2017). Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Supplementary Homicide Reports (SHR), 1976-2024 [Dataset]. http://doi.org/10.3886/E100699V16
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    Dataset updated
    Jun 1, 2017
    Dataset provided by
    Princeton University
    Authors
    Jacob Kaplan
    License

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

    Time period covered
    1976 - 2020
    Area covered
    United States
    Description

    For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 16 release notes:Adds .parquet file formatVersion 15 release notes:Adds 2023 and 2024 dataVersion 14 release notes:Reupload data to fix issue with Stata file not opening.Version 13 release notes:Adds 2022 dataVersion 12 release notes:Adds 2021 data.Version 11 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last SHR data they release. Changes .rda file to .rds.Version 10 release notes:Changes release notes description, does not change data.Version 9 release notes:Adds 2019 data.Version 8 release notes:Adds 2018 data.Changes source of data for years 1985-2018 to be directly from the FBI. 2018 data was received via email from the FBI, 2016-2017 is from the FBI who mailed me a DVD, and 1985-2015 data is from the FBI's Crime Data Explorer site (https://crime-data-explorer.fr.cloud.gov/downloads-and-docs).Adds .csv version of the data.Makes minor changes to value labels for consistency and to fix grammar. Version 7 release notes:Changes project name to avoid confusing this data for the ones done by NACJD.Version 6 release notes:Adds 2017 data.Version 5 release notes:Adds 2016 data.Standardizes the "group" column which categorizes cities and counties by population.Arrange rows in descending order by year and ascending order by ORI. Version 4 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. Version 3 Release Notes:Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Change column names for relationship variables from offender_n_relation_to_victim_1 to victim_1_relation_to_offender_n to better indicate that all relationship are victim 1's relationship to each offender. Reorder columns.This is a single file containing all data from the Supplementary Homicide Reports from 1976 to 2018. The Supplementary Homicide Report provides detailed information about the victim, offender, and circumstances of the murder. Details include victim and offender age, sex, race, ethnicity (Hispanic/not Hispanic), the weapon used, circumstances of the incident, and the number of both offenders and victims. Years 1976-1984 were downloaded from NACJD, while more recent years are from the FBI. All files came as ASCII+SPSS Setup files and were cleaned using R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors, have terminology be the same across years). The following is the summary of the Supplementary Homicide Report copied from ICPSR's 2015 page for the data.The Uniform Crime Reporting Program Data: Supplementary Homicide Reports (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

  17. o

    Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program...

    • openicpsr.org
    Updated Mar 29, 2018
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    Jacob Kaplan (2018). Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Arrests by Age, Sex, and Race, 1974-2020 [Dataset]. http://doi.org/10.3886/E102263V14
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    Dataset updated
    Mar 29, 2018
    Dataset provided by
    Princeton University
    Authors
    Jacob Kaplan
    License

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

    Time period covered
    1974 - 2020
    Area covered
    United States
    Description

    For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 14 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last Arrests by Age, Sex, and Race data they release. Version 13 release notes:Changes R files from .rda to .rds.Fixes bug where the number_of_months_reported variable incorrectly was the largest of the number of months reported for a specific crime variable. For example, if theft was reported Jan-June and robbery was reported July-December in an agency, in total there were 12 months reported. But since each crime (and let's assume no other crime was reported more than 6 months of the year) only was reported 6 months, the number_of_months_reported variable was incorrectly set at 6 months. Now it is the total number of months reported of any crime. So it would be set to 12 months in this example. Thank you to Nick Eubank for alerting me to this issue.Adds rows even when a agency reported zero arrests that month; all arrest values are set to zero for these rows.Version 12 release notes:Adds 2019 data.Version 11 release notes:Changes release notes description, does not change data.Version 10 release notes:The data now has the following age categories (which were previously aggregated into larger groups to reduce file size): under 10, 10-12, 13-14, 40-44, 45-49, 50-54, 55-59, 60-64, over 64. These categories are available for female, male, and total (female+male) arrests. The previous aggregated categories (under 15, 40-49, and over 49 have been removed from the data). Version 9 release notes:For each offense, adds a variable indicating the number of months that offense was reported - these variables are labeled as "num_months_[crime]" where [crime] is the offense name. These variables are generated by the number of times one or more arrests were reported per month for that crime. For example, if there was at least one arrest for assault in January, February, March, and August (and no other months), there would be four months reported for assault. Please note that this does not differentiate between an agency not reporting that month and actually having zero arrests. The variable "number_of_months_reported" is still in the data and is the number of months that any offense was reported. So if any agency reports murder arrests every month but no other crimes, the murder number of months variable and the "number_of_months_reported" variable will both be 12 while every other offense number of month variable will be 0. Adds data for 2017 and 2018.Version 8 release notes:Adds annual data in R format.Changes project name to avoid confusing this data for the ones done by NACJD.Fixes bug where bookmaking was excluded as an arrest category. Changed the number of categories to include more offenses per category to have fewer total files. Added a "total_race" file for each category - this file has total arrests by race for each crime and a breakdown of juvenile/adult by race. Version 7 release notes: Adds 1974-1979 dataAdds monthly data (only totals by sex and race, not by age-categories). All data now from FBI, not NACJD. Changes some column names so all columns are <=32 characters to be usable in Stata.Changes how number of months reported is calculated. Now it is the number of unique months with arrest data reported - months of data from the monthly header file (i.e. juvenile disposition data) are not considered in this calculation. Version 6 release notes: Fix bug where juvenile female columns had the same value as juvenile male columns.Version 5 release notes: Removes support for SPSS and Excel data.Changes the crimes that are stored in each file. There are more files now with fewer crimes per file. The files and their included crimes have been updated below.Adds in agencies that report 0 months of the year.Adds a column that indicates the number of months reported. This is generated summing up the number of unique months an agency reports data for. Note that this indicates the number of months an agency reported arrests for ANY crime. They may not necessarily report every crime every month. Agencies that did not report a crime with have a value of NA for every arrest column for that crime.Removes data on runaways.Version 4 release notes: Changes column names from "poss_coke" and "sale_coke" to "poss_heroi

  18. o

    Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program...

    • openicpsr.org
    Updated Mar 29, 2018
    + more versions
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    Jacob Kaplan (2018). Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Arrests by Age, Sex, and Race, 1974-2018 [Dataset]. http://doi.org/10.3886/E102263V11
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    Dataset updated
    Mar 29, 2018
    Dataset provided by
    University of Pennsylvania
    Authors
    Jacob Kaplan
    License

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

    Time period covered
    1974 - 2018
    Area covered
    United States
    Description

    Version 11 release notes:Changes release notes description, does not change data.Version 10 release notes:The data now has the following age categories (which were previously aggregated into larger groups to reduce file size): under 10, 10-12, 13-14, 40-44, 45-49, 50-54, 55-59, 60-64, over 64. These categories are available for female, male, and total (female+male) arrests. The previous aggregated categories (under 15, 40-49, and over 49 have been removed from the data). Version 9 release notes:For each offense, adds a variable indicating the number of months that offense was reported - these variables are labeled as "num_months_[crime]" where [crime] is the offense name. These variables are generated by the number of times one or more arrests were reported per month for that crime. For example, if there was at least one arrest for assault in January, February, March, and August (and no other months), there would be four months reported for assault. Please note that this does not differentiate between an agency not reporting that month and actually having zero arrests. The variable "number_of_months_reported" is still in the data and is the number of months that any offense was reported. So if any agency reports murder arrests every month but no other crimes, the murder number of months variable and the "number_of_months_reported" variable will both be 12 while every other offense number of month variable will be 0. Adds data for 2017 and 2018.Version 8 release notes:Adds annual data in R format.Changes project name to avoid confusing this data for the ones done by NACJD.Fixes bug where bookmaking was excluded as an arrest category. Changed the number of categories to include more offenses per category to have fewer total files. Added a "total_race" file for each category - this file has total arrests by race for each crime and a breakdown of juvenile/adult by race. Version 7 release notes: Adds 1974-1979 dataAdds monthly data (only totals by sex and race, not by age-categories). All data now from FBI, not NACJD. Changes some column names so all columns are <=32 characters to be usable in Stata.Changes how number of months reported is calculated. Now it is the number of unique months with arrest data reported - months of data from the monthly header file (i.e. juvenile disposition data) are not considered in this calculation. Version 6 release notes: Fix bug where juvenile female columns had the same value as juvenile male columns.Version 5 release notes: Removes support for SPSS and Excel data.Changes the crimes that are stored in each file. There are more files now with fewer crimes per file. The files and their included crimes have been updated below.Adds in agencies that report 0 months of the year.Adds a column that indicates the number of months reported. This is generated summing up the number of unique months an agency reports data for. Note that this indicates the number of months an agency reported arrests for ANY crime. They may not necessarily report every crime every month. Agencies that did not report a crime with have a value of NA for every arrest column for that crime.Removes data on runaways.Version 4 release notes: Changes column names from "poss_coke" and "sale_coke" to "poss_heroin_coke" and "sale_heroin_coke" to clearly indicate that these column includes the sale of heroin as well as similar opiates such as morphine, codeine, and opium. Also changes column names for the narcotic columns to indicate that they are only for synthetic narcotics. Version 3 release notes: Add data for 2016.Order rows by year (descending) and ORI.Version 2 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The Arrests by Age, Sex, and Race (ASR) data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains highly granular data on the number of people arrested for a variety of crimes (see below for a full list of included crimes). The data sets here combine data from the years 1974-2018 into a single file for each group of crimes. Each monthly file is only a single year as my laptop can't handle combining all the years together. These files are quite large and may take some time to load. Columns are crime-arrest category units. For example, If you choose the data set that includes murder, you would have rows for each age

  19. Firearm homicide rate U.S. 2021, by race and gender

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Firearm homicide rate U.S. 2021, by race and gender [Dataset]. https://www.statista.com/statistics/1466192/firearm-homicide-rate-by-race-and-gender-us/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    As of 2021, Black men had the highest firearm homicide rate in the United States, with ***** homicides by firearm per 100,000 of the population. In comparison, Black women had a firearm homicide rate of **** per 100,000 of the population. In that year, the risk of gun homicide was lowest among Asian people across all genders.

  20. Gun homicide rate U.S. 2022, by race and age

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Gun homicide rate U.S. 2022, by race and age [Dataset]. https://www.statista.com/statistics/1466060/gun-homicide-rate-by-race-and-age-us/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    In the United States, Black people have higher rates of gun homicide than White people across all age groups. As of 2022, gun homicide rates were highest among Black people aged between 15 and 24 years, at ***** gun homicides per 100,000 of the population. In comparison, there were only **** gun homicides per 100,000 of the White population within this age range. However, the risk for gun homicide was greatest among all adolescents and adults between the ages of 15 to 44 in that year. The impact of guns on young Americans In the last few years, firearms have become the leading cause of death for American children and teenagers aged one to 19 years old, accounting for more deaths than car crashes and diseases. School shootings also remain on the rise recently, with the U.S. recording ** times as many school shootings than other high-income nations from 2009 to 2018. Black students in particular experience a disproportionately high number of school shootings relative to their population, and K-12 teachers at schools made up mostly of students of color are more likely to report feeling afraid that they or their students would be a victim of attack or harm. The right to bear arms Despite increasingly high rates of gun-related violence, gun ownership remains a significant part of American culture, largely due to the fact that the right to bear arms is written into the U.S. Constitution. Although firearms are the most common murder weapon used in the U.S., accounting for approximately ****** homicides in 2022, almost **** of American households have at least one firearm in their possession. Consequently, it is evident that firearms remain easily accessible nationwide, even though gun laws may vary from state to state. However, the topic of gun control still causes political controversy, as the majority of Republicans agree that it is more important to protect the right of Americans to own guns, while Democrats are more inclined to believe that it is more important to limit gun ownership.

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City of Chicago (2025). Violence Reduction - Victim Demographics - Aggregated [Dataset]. https://data.cityofchicago.org/Public-Safety/Violence-Reduction-Victim-Demographics-Aggregated/gj7a-742p

Violence Reduction - Victim Demographics - Aggregated

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xml, xlsx, csvAvailable download formats
Dataset updated
Sep 30, 2025
Dataset authored and provided by
City of Chicago
Description

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

  1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
  2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

  1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: All businesses identified as victims in CPD data have been removed from this dataset.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

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