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.

The study was a comprehensive analysis of felonious killings of officers. The purposes of the study were (1) to analyze the nature and circumstances of incidents of felonious police killings and (2) to analyze trends in the numbers and rates of killings across different types of agencies and to explain these differences. For Part 1, Incident-Level Data, an incident-level database was created to capture all incidents involving the death of a police officer from 1983 through 1992. Data on officers and incidents were collected from the Law Enforcement Officers Killed and Assaulted (LEOKA) data collection as coded by the Uniform Crime Reporting (UCR) program. In addition to the UCR data, the Police Foundation also coded information from the LEOKA narratives that are not part of the computerized LEOKA database from the FBI. For Part 2, Agency-Level Data, the researchers created an agency-level database to research systematic differences among rates at which law enforcement officers had been feloniously killed from 1977 through 1992. The investigators focused on the 56 largest law enforcement agencies because of the availability of data for explanatory variables. Variables in Part 1 include year of killing, involvement of other officers, if the officer was killed with his/her own weapon, circumstances of the killing, location of fatal wounds, distance between officer and offender, if the victim was wearing body armor, if different officers were killed in the same incident, if the officer was in uniform, actions of the killer and of the officer at entry and final stage, if the killer was visible at first, if the officer thought the killer was a felon suspect, if the officer was shot at entry, and circumstances at anticipation, entry, and final stages. Demographic variables for Part 1 include victim's sex, age, race, type of assignment, rank, years of experience, agency, population group, and if the officer was working a security job. Part 2 contains variables describing the general municipal environment, such as whether the agency is located in the South, level of poverty according to a poverty index, population density, percent of population that was Hispanic or Black, and population aged 15-34 years old. Variables capturing the crime environment include the violent crime rate, property crime rate, and a gun-related crime index. Lastly, variables on the environment of the police agencies include violent and property crime arrests per 1,000 sworn officers, percentage of officers injured in assaults, and number of sworn officers.

About this dataset

The Washington Post compiled a dataset of every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

In 2015, The Post began tracking more than a dozen details about each killing by culling local news reports, law enforcement websites and social media and by monitoring independent databases such as Killed by Police and Fatal Encounters. The available features are: - Race of the deceased; - Circumstances of the shooting; - Whether the person was armed; - Whether the victim was experiencing a mental-health crisis; - Among others.

In 2016, The Post is gathering additional information about each fatal shooting that occurs this year and is filing open-records requests with departments. More than a dozen additional details are being collected about officers in each shooting.

The Post is documenting only those shootings in which a police officer, in the line of duty, shot and killed a civilian — the circumstances that most closely parallel the 2014 killing of Michael Brown in Ferguson, Mo., which began the protest movement culminating in Black Lives Matter and an increased focus on police accountability nationwide. The Post is not tracking deaths of people in police custody, fatal shootings by off-duty officers or non-shooting deaths.

The FBI and the Centers for Disease Control and Prevention log fatal shootings by police, but officials acknowledge that their data is incomplete. In 2015, The Post documented more than two times more fatal shootings by police than had been recorded by the FBI. Last year, the FBI announced plans to overhaul how it tracks fatal police encounters.

How to use this dataset

• Understanding US Police Shootings by Curtis Thompson
• Dataset Questions and Suggestions
• More datasets

Acknowledgements

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

BibTeX

@misc{wapo-police-shootings-bot , author = {The Washington Post}, title = {data-police-shootings}, month = jan, year = 2015, publisher = {Github}, url = {https://github.com/washingtonpost/data-police-shootings} }

License

CC BY NC SA 4.0

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Analysis of ‘Police Killings US’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/azizozmen/police-killings-us on 13 February 2022.

--- Dataset description provided by original source is as follows ---

"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 was wearing a body camera and it may have recorded some portion of the incident.

SOURCE

--- Original source retains full ownership of the source dataset ---

List of every shooting incident that occurred in NYC during the current calendar year. This is a breakdown of every shooting incident that occurred in NYC during the current calendar year. This data is manually extracted every quarter and reviewed by the Office of Management Analysis and Planning before being posted on the NYPD website. Each record represents a shooting incident in NYC and includes information about the event, the location and time of occurrence. In addition, information related to suspect and victim demographics is also included. This data can be used by the public to explore the nature of police enforcement activity. Please refer to the attached data footnotes for additional information about this dataset.

Police fatalities from 2000 to 2016

This dataset aims to provide insight into individuals who were killed during altercations with police. It includes information on their age, race, mental health status, weapons they were armed with, and if they were fleeing.

Content

some of the features are in the original data and the others were added in this updated version. 1. UID, Unique ID of the murdered, In the original data 2. Name, The name of the murdered, In the original data 3. Age, The age of the murdered, In the original data 4. Stages of Life, The age stage of the murdered, Added in this updated version 5. Gender, The Gender of the murdered, In the original data 6. Race, The Race of the murdered, In the original data 7. Date, The date of death, In the original data 8. Year, The year in which the death occurred, Added in this updated version 9. Quarter, The Quarter in which the death occurred, Added in this updated version 10. Month, The month in which the death occurred, Added in this updated version 11. Week, The week in which the death occurred, Added in this updated version 12. Day, The day in which the death occurred, Added in this updated version 13. City, The City in which the death occurred, In the original data 14. State, The State in which the death occurred, In the original data 15. Region, The Region in which the death occurred, Added in this updated version 16. Manner of death In what way was the victim killed?, In the original data 17. Armed, Did the victim have a weapon?, In the original data 18. Mental illness, Was the victim mentally ill?, In the original data 19. Flee, Did the victim try to escape?, In the original data

Acknowledgements

This dataset comes from https://data.world/awram/us-police-involved-fatalities.

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.

Context

Approximately 10 people are shot on an average day in Chicago.

http://www.chicagotribune.com/news/data/ct-shooting-victims-map-charts-htmlstory.html http://www.chicagotribune.com/news/local/breaking/ct-chicago-homicides-data-tracker-htmlstory.html http://www.chicagotribune.com/news/local/breaking/ct-homicide-victims-2017-htmlstory.html

Content

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. This data includes unverified reports supplied to the Police Department. 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.

Update Frequency: Daily

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:chicago_crime

https://cloud.google.com/bigquery/public-data/chicago-crime-data

Dataset Source: City of Chicago

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source —https://data.cityofchicago.org — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Ferdinand Stohr from Unplash.

Inspiration

What categories of crime exhibited the greatest year-over-year increase between 2015 and 2016?

Which month generally has the greatest number of motor vehicle thefts?

How does temperature affect the incident rate of violent crime (assault or battery)?

https://cloud.google.com/bigquery/images/chicago-scatter.png" alt=""> https://cloud.google.com/bigquery/images/chicago-scatter.png

The police shootings data is from the database maintained by Washington Post at https://github.com/washingtonpost/data-police-shootings (version 2) that covers the period 2015-2023.The curated datasets are included here along with a research question and guiding questions.See the codebook for full details.

The Counted is a project by the Guardian – and you – working to count the number of people killed by police and other law enforcement agencies in the United States throughout 2015 and 2016, to monitor their demographics and to tell the stories of how they died.

The database will combine Guardian reporting with verified crowdsourced information to build a more comprehensive record of such fatalities. The Counted is the most thorough public accounting for deadly use of force in the US, but it will operate as an imperfect work in progress – and will be updated by Guardian reporters and interactive journalists as frequently and as promptly as possible.

The Shootings dashboard contains information on shooting incidents where a victim was struck by a bullet, either fatally or non-fatally; that occurred in the City of Boston and fall under Boston Police Department jurisdiction. The dashboard does not contain records for self-inflicted gunshot wounds or shootings determined to be justifiable. Information on the incident, and the demographics of victims are included. This information is updated based on analysis conducted by the Boston Regional Intelligence Center under the Boston Police Department Bureau of Intelligence and Analysis. The data is for 2015 forward, with a 7 day rolling delay to allow for analysis and data entry to occur.

This dataset contains individual-level homicide and non-fatal shooting victimizations, including homicide data from 1991 to the present, and non-fatal shooting data from 2010 to the present (2010 is the earliest available year for shooting data). 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-access dataset, but with "UNKNOWN" in the shooting column.

Each row represents a single victimization, i.e., a unique event when an individual became the victim of a homicide or non-fatal shooting. Each row does not represent a unique victim—if someone is victimized multiple times there will be multiple rows for each of those distinct events.

The dataset is refreshed daily, but excludes the most recent complete day to allow the Chicago Police Department (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.

A version of this dataset with additional crime types is available by request. To make a request, please email dataportal@cityofchicago.org with the subject line: Violence Reduction Victims Access Request. Access will require an account on this site, which you may create at https://data.cityofchicago.org/signup.

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: 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.” Officer-involved shootings are not included.

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.

Note: In some instances, CPD'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 reliable crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: Homicide victims names are delayed by two weeks to allow time for the victim’s family to be notified of their passing.

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.

Note: This dataset includes variables referencing administrative or political boundaries that are subject to change. These include Street Outreach Organization boundary, Ward, Chicago Police Department District, Chicago Police Department Area, Chicago Police Department Beat, Illinois State Senate District, and Illinois State House of Representatives District. These variables reflect current geographic boundaries as of November 1st, 2021. In some instances, current boundaries may conflict with those that were in place at the time that a given incident occurred in prior years. For example, the Chicago Police Department districts 021 and 013 no longer exist. Any historical violent crime victimization that occurred in those districts when they were in existence are marked in this dataset as having occurred in the current districts that expanded to replace 013 and 021."

What is The Counted? The Counted is a project by the Guardian – and you – working to count the number of people killed by police and other law enforcement agencies in the United States throughout 2015, to monitor their demographics and to tell the stories of how they died. The database will combine Guardian reporting with verified crowdsourced information to build a more comprehensive record of such fatalities. The Counted is the most thorough public accounting for deadly use of force in the US, but it will operate as an imperfect work in progress – and will be updated by Guardian reporters and interactive journalists as frequently and as promptly as possible.

Since 2013, protests opposing police violence against Black people have occurred across a number of American cities under the banner of “Black Lives Matter.” We develop a new dataset of Black Lives Matter protests that took place in 2014–2015 and explore the contexts in which they emerged. We find that Black Lives Matter protests are more likely to occur in localities where more Black people have previously been killed by police. We discuss the implications of our findings in light of the literature on the development of social movements and recent scholarship on the carceral state’s impact on political engagement.

The Toronto’s Police Service Annual Statistical Report (ASR) is a comprehensive overview of police related statistics including reported crimes, victims of crime, search of persons, firearms, traffic collisions, personnel, budget, communications, public complaints, regulated interactions and other administrative information. This dataset includes all shooting occurrences from 2014 to 2019 by occurred date aggregated by Division. This data includes all shooting-related events reported to the Toronto Police Service, including, but not limited to, those that may have been deemed unfounded after investigation. Data is accurate as of the date and time of reporting. In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. The data has been aggregated by year, category, subtype and geographic division. As there is no criminal offence code for shootings, a shooting occurrence number may also be present in other data sets including, but not limited to, assault and robbery. Note: The further breakdown of this information at the event level will be made available in the future releases of the Shootings open data. Shootings in this data set include both firearm discharges and shooting events, which are defined as follows: Shooting Event/Occurrence: Any incident in which a projectile is discharged from a firearm (as defined under the Criminal Code of Canada) and injures a person. This excludes events such as suicide and police involved firearm discharges. Firearm Discharge: Any incident where evidence exists that a projectile was discharged from a firearm (as defined under the Criminal Code of Canada) including accidental discharge (non-police), celebratory fire, drive-by etc. Persons Injured (previously classified as “victims”): A person who was struck by a bullet(s) as a result of the discharge of a firearm (as defined under the Criminal Code of Canada). This excludes events such as suicide, police-involved event or where the weapon used was not a real firearm (such as pellet gun, air pistol, “sim-munition” etc.) Injury Levels Death: Where the injured person (as defined above) has died as a result of injuries sustained from a bullet(s). Injuries: Where the injured person (as defined above) has non-fatal physical injuries as a result of a bullet(s). This data is related to table (ASR-SH-TBL-001) in The Annual Statistical Report. Additional information can be found here.

BackgroundPrior research suggests that United States governmental sources documenting the number of law-enforcement-related deaths (i.e., fatalities due to injuries inflicted by law enforcement officers) undercount these incidents. The National Vital Statistics System (NVSS), administered by the federal government and based on state death certificate data, identifies such deaths by assigning them diagnostic codes corresponding to “legal intervention” in accordance with the International Classification of Diseases–10th Revision (ICD-10). Newer, nongovernmental databases track law-enforcement-related deaths by compiling news media reports and provide an opportunity to assess the magnitude and determinants of suspected NVSS underreporting. Our a priori hypotheses were that underreporting by the NVSS would exceed that by the news media sources, and that underreporting rates would be higher for decedents of color versus white, decedents in lower versus higher income counties, decedents killed by non-firearm (e.g., Taser) versus firearm mechanisms, and deaths recorded by a medical examiner versus coroner.Methods and findingsWe created a new US-wide dataset by matching cases reported in a nongovernmental, news-media-based dataset produced by the newspaper The Guardian, The Counted, to identifiable NVSS mortality records for 2015. We conducted 2 main analyses for this cross-sectional study: (1) an estimate of the total number of deaths and the proportion unreported by each source using capture–recapture analysis and (2) an assessment of correlates of underreporting of law-enforcement-related deaths (demographic characteristics of the decedent, mechanism of death, death investigator type [medical examiner versus coroner], county median income, and county urbanicity) in the NVSS using multilevel logistic regression. We estimated that the total number of law-enforcement-related deaths in 2015 was 1,166 (95% CI: 1,153, 1,184). There were 599 deaths reported in The Counted only, 36 reported in the NVSS only, 487 reported in both lists, and an estimated 44 (95% CI: 31, 62) not reported in either source. The NVSS documented 44.9% (95% CI: 44.2%, 45.4%) of the total number of deaths, and The Counted documented 93.1% (95% CI: 91.7%, 94.2%). In a multivariable mixed-effects logistic model that controlled for all individual- and county-level covariates, decedents injured by non-firearm mechanisms had higher odds of underreporting in the NVSS than those injured by firearms (odds ratio [OR]: 68.2; 95% CI: 15.7, 297.5; p < 0.01), and underreporting was also more likely outside of the highest-income-quintile counties (OR for the lowest versus highest income quintile: 10.1; 95% CI: 2.4, 42.8; p < 0.01). There was no statistically significant difference in the odds of underreporting in the NVSS for deaths certified by coroners compared to medical examiners, and the odds of underreporting did not vary by race/ethnicity. One limitation of our analyses is that we were unable to examine the characteristics of cases that were unreported in The Counted.ConclusionsThe media-based source, The Counted, reported a considerably higher proportion of law-enforcement-related deaths than the NVSS, which failed to report a majority of these incidents. For the NVSS, rates of underreporting were higher in lower income counties and for decedents killed by non-firearm mechanisms. There was no evidence suggesting that underreporting varied by death investigator type (medical examiner versus coroner) or race/ethnicity.

Data on police personnel (police officers by gender, civilian and other personnel), police-civilian ratio, police officers and authorized strength per 100,000 population, authorized police officer strength and selected crime statistics. Data is provided for Canada, provinces, territories and the Royal Canadian Mounted Police (RCMP) headquarters, training academy depot division and forensic labs, 1986 to 2023.

Traffic fatalities within the City of Chicago that are included in Vision Zero Chicago (VZC) statistics. Vision Zero is Chicago’s commitment to eliminating fatalities and serious injuries from traffic crashes. The VZC Traffic Fatality List is compiled by the Chicago Department of Transportation (CDOT) after monthly reviews of fatal traffic crash information provided by Chicago Police Department’s Major Accident Investigation Unit (MAIU). CDOT uses a standardized process – sometimes differing from other sources and everyday use of the term -- to determine whether a death is a “traffic fatality.” Therefore, the traffic fatalities included in this list may differ from the fatal crashes reported in the full Traffic Crashes dataset (https://data.cityofchicago.org/d/85ca-t3if). Official traffic crash data are published by the Illinois Department of Transportation (IDOT) on an annual basis. This VZC Traffic Fatality List is updated monthly. Once IDOT publishes its crash data for a year, this dataset is edited to reflect IDOT’s findings. VZC Traffic Fatalities can be linked with other traffic crash datasets using the “Person_ID” field. State of Illinois considers a “traffic fatality” as any death caused by a traffic crash involving a motor vehicle, within 30 days of the crash. Fatalities that meet this definition are included in this VZC Traffic Fatality List unless excluded by any criteria below. There may be records in this dataset that do not appear as fatalities in the other datasets. The following criteria exclude a death from being considered a "traffic fatality," and are derived from Federal and State reporting standards. The Medical Examiner determined that the primary cause of the fatality was not the traffic crash, including: a. The fatality was reported as a suicide based on a police investigation. b. The fatality was reported as a homicide in which the "party at fault" intentionally inflicted serious bodily harm that caused the victim's death. c. The fatality was caused directly and exclusively by a medical condition or the fatality was not attributable to road user movement on a public roadway. (Note: If a person driving suffers a medical emergency and consequently hits and kills another road user, the other road user is included, although the driver suffering a medical emergency is excluded.) The crash did not occur within a trafficway. The crash involved a train or other such mode of transport within the rail dedicated right-of-way. The fatality was on a roadway not under Chicago Police Department jurisdiction, including: a. The fatality was occurred on an expressway. The City of Chicago does not have oversight on the expressway system. However, a fatality on expressway ramps occurring within the City jurisdiction will be counted in VZC Traffic Fatality List. b. The fatality occurred outside City limits. Crashes on streets along the City boundary may be assigned to another jurisdiction after the investigation if it is determined that the crash started or substantially occurred on the side of the street that is outside the City limits. Jurisdiction of streets along the City boundary are split between City and neighboring jurisdictions along the street centerline. The fatality is not a person (e.g., an animal). Change 12/7/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

Version 3 release notes:

• Fix bug where Philadelphia Police Department had incorrect FIPS county code.

The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. Each data set contains over 2,200 columns and has a wealth of information about the circumstances of assaults on officers.

All the data was downloaded from NACJD as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. It was then cleaned in 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).

About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself.

I did not make any changes to the numeric columns except for the following. A few years of data had the values "blank" or "missing" as indicators of missing values. Rows in otherwise numeric columns (e.g. jan_asslt_no_injury_knife) with these values were replaced with NA. There were three obvious data entry errors in officers killed by felony/accident that I changed to NA.

In 1978 the agency "pittsburgh" (ORI = PAPPD00) reported 576 officers killed by accident during March.
In 1979 the agency "metuchen" (ORI = NJ01210) reported 991 officers killed by felony during August.
In 1990 the agency "penobscot state police" (ORI = ME010SP) reported 860 officers killed by accident during July.

No other changes to numeric columns were made.

Each zip file contains all years as individual monthly files of the specified data type It also includes a file with all years aggregated yearly and stacked into a single data set. Please note that each monthly file is quite large (2,200+ columns) so it may take time to download the zip file and open each data file.

For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data.

The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:

"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety.

"... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."

If you have any questions, comments, or suggestions please contact me at jkkaplan6@gmail.com

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