12 datasets found
  1. Police Killings US

    • kaggle.com
    zip
    Updated Feb 6, 2022
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    Matthew Connor (2022). Police Killings US [Dataset]. https://www.kaggle.com/datasets/azizozmen/police-killings-us
    Explore at:
    zip(62816 bytes)Available download formats
    Dataset updated
    Feb 6, 2022
    Authors
    Matthew Connor
    Description

    "In 2015, The Washington Post began to log every fatal shooting by an on-duty police officer in the United States. In that time there have been more than 5,000 such shootings recorded by The Post. After Michael Brown, an unarmed Black man, was killed in 2014 by police in Ferguson, Mo., a Post investigation found that the FBI undercounted fatal police shootings by more than half. This is because reporting by police departments is voluntary and many departments fail to do so. The Washington Post’s data relies primarily on news accounts, social media postings, and police reports. Analysis of more than five years of data reveals that the number and circumstances of fatal shootings and the overall demographics of the victims have remained relatively constant..." SOURCE ==> Washington Post Article

    For more information about this story

    This dataset has been prepared by The Washington Post (they keep updating it on runtime) with every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

    2016 PoliceKillingUS DATASET
    2017 PoliceKillingUS DATASET
    2018 PoliceKillingUS DATASET
    2019 PoliceKillingUS DATASET
    2020 PoliceKillingUS DATASET

    Features at the Dataset:

    The file fatal-police-shootings-data.csv contains data about each fatal shooting in CSV format. The file can be downloaded at this URL. Each row has the following variables:

    • id: a unique identifier for each victim
    • name: the name of the victim
    • date: the date of the fatal shooting in YYYY-MM-DD format
    • manner_of_death: shot, shot and Tasered
    • armed: indicates that the victim was armed with some sort of implement that a police officer believed could inflict harm
      • undetermined: it is not known whether or not the victim had a weapon
      • unknown: the victim was armed, but it is not known what the object was
      • unarmed: the victim was not armed
    • age: the age of the victim
    • gender: the gender of the victim. The Post identifies victims by the gender they identify with if reports indicate that it differs from their biological sex.
      • M: Male
      • F: Female
      • None: unknown
    • race:
      • W: White, non-Hispanic
      • B: Black, non-Hispanic
      • A: Asian
      • N: Native American
      • H: Hispanic
      • O: Other
      • None: unknown
    • city: the municipality where the fatal shooting took place. Note that in some cases this field may contain a county name if a more specific municipality is unavailable or unknown.
    • state: two-letter postal code abbreviation
    • signs of mental illness: News reports have indicated the victim had a history of mental health issues, expressed suicidal intentions or was experiencing mental distress at the time of the shooting.
    • threat_level: The threat_level column was used to flag incidents for the story by Amy Brittain in October 2015. http://www.washingtonpost.com/sf/investigative/2015/10/24/on-duty-under-fire/ As described in the story, the general criteria for the attack label was that there was the most direct and immediate threat to life. That would include incidents where officers or others were shot at, threatened with a gun, attacked with other weapons or physical force, etc. The attack category is meant to flag the highest level of threat. The other and undetermined categories represent all remaining cases. Other includes many incidents where officers or others faced significant threats.
    • flee: News reports have indicated the victim was moving away from officers
      • Foot
      • Car
      • Not fleeing

    The threat column and the fleeing column are not necessarily related. For example, there is an incident in which the suspect is fleeing and at the same time turns to fire at gun at the officer. Also, attacks represent a status immediately before fatal shots by police while fleeing could begin slightly earlier and involve a chase. - body_camera: News reports have indicated an officer w...

  2. People shot to death by U.S. police 2017-2024, by race

    • statista.com
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    Statista, People shot to death by U.S. police 2017-2024, by race [Dataset]. https://www.statista.com/statistics/585152/people-shot-to-death-by-us-police-by-race/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

  3. A Multi-Level Bayesian Analysis of Racial Bias in Police Shootings at the...

    • plos.figshare.com
    zip
    Updated Jun 5, 2023
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    Cody T. Ross (2023). A Multi-Level Bayesian Analysis of Racial Bias in Police Shootings at the County-Level in the United States, 2011–2014 [Dataset]. http://doi.org/10.1371/journal.pone.0141854
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Cody T. Ross
    License

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

    Area covered
    United States
    Description

    A geographically-resolved, multi-level Bayesian model is used to analyze the data presented in the U.S. Police-Shooting Database (USPSD) in order to investigate the extent of racial bias in the shooting of American civilians by police officers in recent years. In contrast to previous work that relied on the FBI’s Supplemental Homicide Reports that were constructed from self-reported cases of police-involved homicide, this data set is less likely to be biased by police reporting practices. County-specific relative risk outcomes of being shot by police are estimated as a function of the interaction of: 1) whether suspects/civilians were armed or unarmed, and 2) the race/ethnicity of the suspects/civilians. The results provide evidence of a significant bias in the killing of unarmed black Americans relative to unarmed white Americans, in that the probability of being {black, unarmed, and shot by police} is about 3.49 times the probability of being {white, unarmed, and shot by police} on average. Furthermore, the results of multi-level modeling show that there exists significant heterogeneity across counties in the extent of racial bias in police shootings, with some counties showing relative risk ratios of 20 to 1 or more. Finally, analysis of police shooting data as a function of county-level predictors suggests that racial bias in police shootings is most likely to emerge in police departments in larger metropolitan counties with low median incomes and a sizable portion of black residents, especially when there is high financial inequality in that county. There is no relationship between county-level racial bias in police shootings and crime rates (even race-specific crime rates), meaning that the racial bias observed in police shootings in this data set is not explainable as a response to local-level crime rates.

  4. Rate of fatal police shootings U.S. 2015-2024, by ethnicity

    • statista.com
    Updated Nov 19, 2025
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    Statista (2025). Rate of fatal police shootings U.S. 2015-2024, by ethnicity [Dataset]. https://www.statista.com/statistics/1123070/police-shootings-rate-ethnicity-us/
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    Dataset updated
    Nov 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The rate of fatal police shootings in the United States shows large differences based on ethnicity. Among Black Americans, the rate of fatal police shootings between 2015 and December 2024 stood at 6.1 per million of the population per year, while for white Americans, the rate stood at 2.4 fatal police shootings per million of the population per year. Police brutality in the United States Police brutality is a major issue in the United States, but recently saw a spike in online awareness and protests following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Just a few months before, Breonna Taylor was fatally shot in her apartment when Louisville police officers forced entry into her apartment. Despite the repeated fatal police shootings across the country, police accountability has not been adequate according to many Americans. A majority of Black Americans thought that police officers were not held accountable for their misconduct, while less than half of White Americans thought the same. Political opinions Not only are there differences in opinion between ethnicities on police brutality, but there are also major differences between political parties. A majority of Democrats in the United States thought that police officers were not held accountable for their misconduct, while a majority of Republicans that they were held accountable. Despite opposing views on police accountability, both Democrats and Republicans agree that police should be required to be trained in nonviolent alternatives to deadly force.

  5. f

    Predictors of an increased county-level risk of being {black, unarmed, and...

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    + more versions
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    Cody T. Ross (2023). Predictors of an increased county-level risk of being {black, unarmed, and shot by police} relative to being {white, armed, and shot by police}. [Dataset]. http://doi.org/10.1371/journal.pone.0141854.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Cody T. Ross
    License

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

    Description

    Values are: posterior mean (posterior standard deviation) of the regression coefficients. The symbol log referes to the natural logarithm. Pop refers to absolute population size. Pct. B. refers to the percentage of the county population that is black. Md. In. refers to median income. Gini refers to the Gini index of inequality. GRP refers to the Google search racism proxy. W. Ast and B. Ast refer to the white- and black-specific arrest rates for assualt, respectively. W. Wps and B. Wps refer to the white- and black-specific arrest rates for weapons violations, respectively. Posterior probabilty that a postive regression coeffcient is less than zero (or a negative one greater than zero) is coded as: * indicates a probability between 0.10 and 0.05, ** indicates a probability between 0.05 and 0.01, and *** indicates a probability of 0.01 or less.

  6. Police Killings

    • kaggle.com
    zip
    Updated Sep 13, 2021
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    mysar ahmad bhat (2021). Police Killings [Dataset]. https://www.kaggle.com/mysarahmadbhat/police-killings
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    zip(52377 bytes)Available download formats
    Dataset updated
    Sep 13, 2021
    Authors
    mysar ahmad bhat
    License

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

    Description

    Field descriptions:

    HeaderDescriptionSource
    nameName of deceasedGuardian
    ageAge of deceasedGuardian
    genderGender of deceasedGuardian
    raceethnicityRace/ethnicity of deceasedGuardian
    monthMonth of killingGuardian
    dayDay of incidentGuardian
    yearYear of incidentGuardian
    streetaddressAddress/intersection where incident occurredGuardian
    cityCity where incident occurredGuardian
    stateState where incident occurredGuardian
    latitudeLatitude, geocoded from address
    longitudeLongitude, geocoded from address
    state_fpState FIPS codeCensus
    county_fpCounty FIPS codeCensus
    tract_ceTract ID codeCensus
    geo_idCombined tract ID code
    county_idCombined county ID code
    namelsadTract descriptionCensus
    lawenforcementagencyAgency involved in incidentGuardian
    causeCause of deathGuardian
    armedHow/whether deceased was armedGuardian
    popTract populationCensus
    share_whiteShare of pop that is non-Hispanic whiteCensus
    share_bloackShare of pop that is black (alone, not in combination)Census
    share_hispanicShare of pop that is Hispanic/Latino (any race)Census
    p_incomeTract-level median personal incomeCensus
    h_incomeTract-level median household incomeCensus
    county_incomeCounty-level median household incomeCensus
    comp_incomeh_income / county_incomeCalculated from Census
    county_bucketHousehold income, quintile within countyCalculated from Census
    nat_bucketHousehold income, quintile nationallyCalculated from Census
    povTract-level poverty rate (official)Census
    urateTract-level unemployment rateCalculated from Census
    collegeShare of 25+ pop with BA or higherCalculated from Census

    Note regarding income calculations:

    All income fields are in inflation-adjusted 2013 dollars.

    comp_income is simply tract-level median household income as a share of county-level median household income.

    county_bucket provides where the tract's median household income falls in the distribution (by quintile) of all tracts in the county. (1 indicates a tract falls in the poorest 20% of tracts within the county.) Distribution is not weighted by population.

    nat_bucket is the same but for all U.S. counties.

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

    • www150.statcan.gc.ca
    • data.urbandatacentre.ca
    • +3more
    Updated Jul 22, 2025
    + more versions
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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.

  8. w

    Officer Involved Shootings Data

    • data.wu.ac.at
    • data.amerigeoss.org
    csv
    Updated Feb 9, 2018
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    City of Bloomington (2018). Officer Involved Shootings Data [Dataset]. https://data.wu.ac.at/schema/data_gov/MTY5ZWUzOGMtOTYzYi00MjhkLWE4OWYtZmI3OWVlODJjNzE2
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    csvAvailable download formats
    Dataset updated
    Feb 9, 2018
    Dataset provided by
    City of Bloomington
    Description

    This set of raw data contains information from Bloomington Police Department cases, specifically it identified cases where officers have fired a gun at a suspect.

    **Please note that this particular dataset contains no data. As of current date, the Bloomington Police Department has had no officer involved shootings to report. **

    Key code for Race:

    • A- Asian/Pacific Island, Non-Hispanic
    • B- African American, Non-Hispanic
    • I- Indian/Alaskan Native, Non-Hispanic
    • K- African American, Hispanic
    • L- Caucasian, Hispanic
    • N- Indian/Alaskan Native, Hispanic
    • P- Asian/Pacific Island, Hispanic
    • U- Unknown
    • W- Caucasian, Non-Hispanic

    Key Code for Reading Districts:

    Example: LB519

    • ‘L’ for Law call or incident
    • ‘B’ stands for Bloomington
    • 5 is the district or beat where incident occurred
    • All numbers following represents a grid sector.

    A map of the five districts can be located on Raidsonline.com, under the tab labeled ‘Agency Layers’.

    Disclaimer: The Bloomington Police Department takes great effort in making all sets of data as accurate as possible, but there is no avoiding the introduction of errors in this process. Information contained in this dataset may change over a period of time. The Bloomington Police Department is not responsible for any error or omission from this data or for the use, or interpretation of the results of any research conducted.

  9. l

    Louisville Metro KY - Officer Involved Shooting Database and Statistical...

    • data.louisvilleky.gov
    • data.lojic.org
    • +3more
    Updated May 25, 2022
    + more versions
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    Louisville/Jefferson County Information Consortium (2022). Louisville Metro KY - Officer Involved Shooting Database and Statistical Analysis 08-04-2021 [Dataset]. https://data.louisvilleky.gov/documents/daf3bbcacaa14edab904cbcfd9c89a3f
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    Dataset updated
    May 25, 2022
    Dataset authored and provided by
    Louisville/Jefferson County Information Consortium
    License

    https://louisville-metro-opendata-lojic.hub.arcgis.com/pages/terms-of-use-and-licensehttps://louisville-metro-opendata-lojic.hub.arcgis.com/pages/terms-of-use-and-license

    Area covered
    Louisville, Kentucky
    Description

    Officer Involved Shooting (OIS) Database and Statistical Analysis. Data is updated after there is an officer involved shooting.PIU#Incident # - the number associated with either the incident or used as reference to store the items in our evidence rooms Date of Occurrence Month - month the incident occurred (Note the year is labeled on the tab of the spreadsheet)Date of Occurrence Day - day of the month the incident occurred (Note the year is labeled on the tab of the spreadsheet)Time of Occurrence - time the incident occurredAddress of incident - the location the incident occurredDivision - the LMPD division in which the incident actually occurredBeat - the LMPD beat in which the incident actually occurredInvestigation Type - the type of investigation (shooting or death)Case Status - status of the case (open or closed)Suspect Name - the name of the suspect involved in the incidentSuspect Race - the race of the suspect involved in the incident (W-White, B-Black)Suspect Sex - the gender of the suspect involved in the incidentSuspect Age - the age of the suspect involved in the incidentSuspect Ethnicity - the ethnicity of the suspect involved in the incident (H-Hispanic, N-Not Hispanic)Suspect Weapon - the type of weapon the suspect used in the incidentOfficer Name - the name of the officer involved in the incidentOfficer Race - the race of the officer involved in the incident (W-White, B-Black, A-Asian)Officer Sex - the gender of the officer involved in the incidentOfficer Age - the age of the officer involved in the incidentOfficer Ethnicity - the ethnicity of the suspect involved in the incident (H-Hispanic, N-Not Hispanic)Officer Years of Service - the number of years the officer has been serving at the time of the incidentLethal Y/N - whether or not the incident involved a death (Y-Yes, N-No, continued-pending)Narrative - a description of what was determined from the investigationContact:Carol Boylecarol.boyle@louisvilleky.gov

  10. N

    The relationship between domestic violence and shooting incidents in New...

    • data.cityofnewyork.us
    • s.cnmilf.com
    • +1more
    csv, xlsx, xml
    Updated Jan 14, 2025
    + more versions
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    Mayor's Office to End Domestic and Gender-Based Violence (ENDGBV) (2025). The relationship between domestic violence and shooting incidents in New York City [Dataset]. https://data.cityofnewyork.us/Public-Safety/The-relationship-between-domestic-violence-and-sho/rvmf-4sg6
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Jan 14, 2025
    Dataset authored and provided by
    Mayor's Office to End Domestic and Gender-Based Violence (ENDGBV)
    Area covered
    New York
    Description

    This data set contains New York City Police Department provided domestic violence incident data for calendar years 2020, 2021 and 2022. In addition, ENDGBV obtained through Open Data the number of shooting incidents for calendar years 2020, 2021 and 2022. The data includes counts of the number of domestic violence incidents, shooting incidents and the number of expected domestic violence incidents and shooting incidents by: race (American Indian/Alaska Native, Asian/Pacific Islander, Black, and White) and sex (male, female) for New York City, each borough (Bronx, Brooklyn, Manhattan, Queens and Staten Island). It also provides the count and rate of domestic violence and shooting incidents by police precinct. The expected number of domestic violence incidents and shooting incidents were calculated by taking the total number of actual domestic violence and shooting incidents for a given geography (New York City, the Bronx, Brooklyn, Manhattan, Queens and Staten Island) and proportioning them by demographic breakdown of the geographic area.

  11. H

    Replication Data for: Seeing Blue in Black and White: Race and Perceptions...

    • dataverse.harvard.edu
    • commons.datacite.org
    Updated Sep 4, 2020
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    Hakeem Jefferson (2020). Replication Data for: Seeing Blue in Black and White: Race and Perceptions of Officer-Involved Shootings [Dataset]. http://doi.org/10.7910/DVN/7XST1I
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 4, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Hakeem Jefferson
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Following racially charged events, individuals often diverge in perceptions of what happened and how justice should be served. Examining data gathered shortly after the 2014 shooting of Michael Brown in Ferguson, Missouri alongside reactions to a novel officer-involved shooting, we unpack the processes by which racial divisions emerge. Even in a controlled information environment, White Americans preferred information that supported claims of a justified shooting. Conversely, Black Americans preferred information that implied the officer behaved inappropriately. These differences stemmed from two distinct processes: we find some evidence for a form of race-based motivated reasoning and strong evidence for belief updating based on racially distinct priors. Differences in summary judgments were larger when individuals identified strongly with their racial group or when expectations about the typical behaviors of Black Americans and police diverged. The findings elucidate processes whereby individuals in different social groups come to accept differing narratives about contentious events.

  12. Female homicide rates from the Porto Alegre Medicolegal Department from...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    • +1more
    xls
    Updated Jun 21, 2023
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    Angelita Maria Ferreira Machado Rios; Kleber Cardoso Crespo; Murilo Martini; Lisieux Elaine De Borba Telles; Pedro V. S. Magalhães (2023). Female homicide rates from the Porto Alegre Medicolegal Department from January 2010 to December 2016 per 100,000 population. [Dataset]. http://doi.org/10.1371/journal.pone.0281924.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Angelita Maria Ferreira Machado Rios; Kleber Cardoso Crespo; Murilo Martini; Lisieux Elaine De Borba Telles; Pedro V. S. Magalhães
    License

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

    Area covered
    Porto Alegre
    Description

    Female homicide rates from the Porto Alegre Medicolegal Department from January 2010 to December 2016 per 100,000 population.

  13. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Matthew Connor (2022). Police Killings US [Dataset]. https://www.kaggle.com/datasets/azizozmen/police-killings-us
Organization logo

Police Killings US

Explore at:
453 scholarly articles cite this dataset (View in Google Scholar)
zip(62816 bytes)Available download formats
Dataset updated
Feb 6, 2022
Authors
Matthew Connor
Description

"In 2015, The Washington Post began to log every fatal shooting by an on-duty police officer in the United States. In that time there have been more than 5,000 such shootings recorded by The Post. After Michael Brown, an unarmed Black man, was killed in 2014 by police in Ferguson, Mo., a Post investigation found that the FBI undercounted fatal police shootings by more than half. This is because reporting by police departments is voluntary and many departments fail to do so. The Washington Post’s data relies primarily on news accounts, social media postings, and police reports. Analysis of more than five years of data reveals that the number and circumstances of fatal shootings and the overall demographics of the victims have remained relatively constant..." SOURCE ==> Washington Post Article

For more information about this story

This dataset has been prepared by The Washington Post (they keep updating it on runtime) with every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

2016 PoliceKillingUS DATASET
2017 PoliceKillingUS DATASET
2018 PoliceKillingUS DATASET
2019 PoliceKillingUS DATASET
2020 PoliceKillingUS DATASET

Features at the Dataset:

The file fatal-police-shootings-data.csv contains data about each fatal shooting in CSV format. The file can be downloaded at this URL. Each row has the following variables:

  • id: a unique identifier for each victim
  • name: the name of the victim
  • date: the date of the fatal shooting in YYYY-MM-DD format
  • manner_of_death: shot, shot and Tasered
  • armed: indicates that the victim was armed with some sort of implement that a police officer believed could inflict harm
    • undetermined: it is not known whether or not the victim had a weapon
    • unknown: the victim was armed, but it is not known what the object was
    • unarmed: the victim was not armed
  • age: the age of the victim
  • gender: the gender of the victim. The Post identifies victims by the gender they identify with if reports indicate that it differs from their biological sex.
    • M: Male
    • F: Female
    • None: unknown
  • race:
    • W: White, non-Hispanic
    • B: Black, non-Hispanic
    • A: Asian
    • N: Native American
    • H: Hispanic
    • O: Other
    • None: unknown
  • city: the municipality where the fatal shooting took place. Note that in some cases this field may contain a county name if a more specific municipality is unavailable or unknown.
  • state: two-letter postal code abbreviation
  • signs of mental illness: News reports have indicated the victim had a history of mental health issues, expressed suicidal intentions or was experiencing mental distress at the time of the shooting.
  • threat_level: The threat_level column was used to flag incidents for the story by Amy Brittain in October 2015. http://www.washingtonpost.com/sf/investigative/2015/10/24/on-duty-under-fire/ As described in the story, the general criteria for the attack label was that there was the most direct and immediate threat to life. That would include incidents where officers or others were shot at, threatened with a gun, attacked with other weapons or physical force, etc. The attack category is meant to flag the highest level of threat. The other and undetermined categories represent all remaining cases. Other includes many incidents where officers or others faced significant threats.
  • flee: News reports have indicated the victim was moving away from officers
    • Foot
    • Car
    • Not fleeing

The threat column and the fleeing column are not necessarily related. For example, there is an incident in which the suspect is fleeing and at the same time turns to fire at gun at the officer. Also, attacks represent a status immediately before fatal shots by police while fleeing could begin slightly earlier and involve a chase. - body_camera: News reports have indicated an officer w...

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