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 Uniform Crime Reporting Program Data, Police Employee Data, 2012 file contains monthly data on felonious or accidental killings and assaults upon United States law enforcement officers acting in the line of duty. The Federal Bureau of Investigation (FBI) assembled the data and processed them from UCR Master Police Employee (LEOKA) data tapes. Each agency record in the file includes the following summary variables: state code, population group code, geographic division, Metropolitan Statistical Area code, and agency name. These variables afford considerable flexibility in creating subsets or aggregations of the data. Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as a periodic nationwide assessment of reported crimes not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Police Employee (LEOKA) Data provide information about law enforcement officers killed or assaulted (hence the acronym, LEOKA) in the line of duty. The variables created from the LEOKA forms provide in-depth information on the circumstances surrounding killings or assaults, including type of call answered, type of weapon used, and type of patrol the officers were on.

"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...

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.

As of November 17, 277 Black people were killed by the police in the United States in 2024. This compares to 201 Hispanic people and 445 white people. The rate of police shootings of Black Americans is much higher than any other ethnicity, at 6.2 per million people. This rate stands at 2.8 per million for Hispanic people and 2.4 per million for white people.

As of October 22, police in the United States had shot 23 unarmed people to death in 2024. The most common weapon for a victim of a fatal police shooting to be carrying is a gun. In 2023, 717 people carrying a gun were shot and killed by the U.S. police.

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.

A publication in which the FBI provides data on law enforcement uses of force that result in the death of a person, serious bodily injury of a person, or when law enforcement discharges a firearm at or in the direction of a person. In addition, law enforcement agencies can indicate months where no incidents meeting the above criteria occurred.

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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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.

This dataset, compiled by The Washington Post, logs every person shot and killed by an on-duty police officer in the United States from 2015 to 2024. Following the 2014 shooting of Michael Brown in Ferguson, it was discovered that FBI reports were significantly undercounted, with only a third of fatal shootings recorded by 2021. This comprehensive database aims to fill that gap and provide detailed information on each incident, including the police departments involved, to enhance accountability.

Investigator(s): Federal Bureau of Investigation Since 1930, the Federal Bureau of Investigation (FBI) has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. With the 1977 data, the title was expanded to Uniform Crime Reporting Program Data. Each year, participating law enforcement agencies contribute reports to the FBI either directly or through their state reporting programs. ICPSR archives the UCR data as five separate components: (1) summary data, (2) county-level data, (3) incident-level data (National Incident-Based Reporting System [NIBRS]), (4) hate crime data, and (5) various, mostly nonrecurring, data collections. Summary data are reported in four types of files: (a) Offenses Known and Clearances by Arrest, (b) Property Stolen and Recovered, (c) Supplementary Homicide Reports (SHR), and (d) Police Employee (LEOKA) Data (Law Enforcement Officers Killed or Assaulted). The county-level data provide counts of arrests and offenses aggregated to the county level. County populations are also reported. In the late 1970s, new ways to look at crime were studied. The UCR program was subsequently expanded to capture incident-level data with the implementation of the National Incident-Based Reporting System. The NIBRS data focus on various aspects of a crime incident. The gathering of hate crime data by the UCR program was begun in 1990. Hate crimes are defined as crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity. In September 1994, disabilities, both physical and mental, were added to the list. The fifth component of ICPSR's UCR holdings is comprised of various collections, many of which are nonrecurring and prepared by individual researchers. These collections go beyond the scope of the standard UCR collections provided by the FBI, either by including data for a range of years or by focusing on other aspects of analysis. NACJD has produced resource guides on UCR and on NIBRS data.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for State Police: Internet Crimes Against Children Unit (State Police) in West Virginia, including incidents, statistics, demographics, and detailed incident information.

Each day researchers at The Post identify and manually record data for fatal police shootings in the United States. Each record requires at least two sources and must be approved by our editors before being publicly released.

Data about each fatal shooting is provided via two comma-separated value (CSV) files:

Death Record data for each victim and incident is included in /v2/fatal-police-shootings-data.csv.

New in v2 is a second Agencies csv, /v2/fatal-police-shootings-agencies.csv, which contains data for police agencies involved in at least one fatal police shooting since 2015. The agencies csv has a field called agency_ids, which can be used to associate each death record with the agencies involved.

To enable joining this dataset with other federal law enforcement datasets, in 2022 The Post undertook an effort to increase the coverage of federal Originating Agency Identifier (ORI) codes recorded for agencies in the database. Using agency data from the FBI and Department of Justice, reporters did a combination of automated and manual name and ORI code matching to fill in missing ORI code data. They also standardized department names. Agency naming, organization, hierarchy and classification varies from state to state. For this reason, sub-agencies and local troops, regions and posts have been aggregated into their parent agencies, meaning that in some cases an individual agency will have multiple associated ORI codes. For instance, a state police depart

Original Data

Acknowlegement

Foto von ev auf Unsplash

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.

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.

In 2021, the San Diego Police Department began reporting to the FBI’s National Incident-Based Reporting System (NIBRS) for statistics. NIBRS collects data on all crimes reported to law enforcement agencies, not just the highest charges within those crimes. Crime categories in NIBRS include crimes against Persons (i.e., assault, homicide, etc.), Property (i.e., burglary, theft, robbery, etc.), and Society (i.e., alcohol and drug offenses, weapon offenses, gambling, etc.). These new categories are a shift from the older FBI reporting style (UCR Summary) of simply reporting violent and property crime counts. For the most part, SDPD’s crime reporting will follow the NIBRS categories now. Historical data will still be posted to the Annual Crime Reports website. This dataset comprises of Crime Offense Data extracted from the San Diego Police Department’s Records Management System and includes information such as the date/time of the reported offense, offense category, underlying code sections, and the hundred block address where the incident occurred. This data is dynamic as records are updated daily and may change or be deleted as police investigations proceed. Records range from January 2020 – Present. The SDPD Neighborhood Crime Summary Dashboard visualizes this dataset. For more information on NIBRS reporting guidelines please refer to the FBI’s 2021.1 National Incident-Based Reporting System User Manual. For national NIBRS data, you can visit the FBI’s Crime Data Explorer.

The Washington Post is compiling a database 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 — including the race of the deceased, the circumstances of the shooting, whether the person was armed and whether the person was experiencing a mental-health crisis — 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 Post conducted additional reporting in many cases.

In 2016, The Post is gathering additional information about each fatal shooting by police 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. Officers’ names are being included in the database after The Post contacts the departments to request comment.

The Post is documenting only those shootings in which a police officer, in the line of duty, shoots and kills 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 twice as many fatal shootings by police as had been recorded by the FBI. Last year, the FBI announced plans to overhaul how it tracks fatal police encounters.

The Post's database is updated regularly as fatal shootings are reported and as facts emerge about individual cases. The Post is seeking assistance in making the database as comprehensive as possible. To provide information about fatal police shootings since Jan. 1, 2015, send us an email at policeshootingsfeedback@washpost.com. The Post is also interested in obtaining photos of the deceased and original videos of fatal encounters with police.

Data Dictionary

...

Key	List of...	Comment	Example Value
Person.Name	String	Full name of the individual or "Unknown" if not reported	"Tim Elliot"
Person.Age	Integer	Age in years of the individual or 0 (zero) if not reported	53
Person.Gender	String	One of Male, Female, or Unknown	"Male"
Person.Race	String	One of Asian, African American, White, Hispanic, Native American, Other, or Unknown.	"Asian"
Incident.Date.Month	Integer	Month (1-12) in which the shooting occurred	1
Incident.Date.Day	Integer	Day (1-31) in which the shooting occurred	2
Incident.Date.Year	Integer	Year (2015-2019) in which the shooting occurred	2015
Incident.Date.Full	String	Date in which shooting occurred (Year/Month/Day)	"2015/01/02"
Incident.Location.City	String	Name of city in which the shooting occurred	"Shelton"
Incident.Location.State	String	Name of U.S. State in which the shooting occurred	"WA"
Factors.Armed	String	Description of any weapon carried by the person (.e., "gun", "knife", "unarmed"); value is "unknown" if not reported.	"gun"
Factors.Mental-Illness	Boolean	True if factors of mental illness were perceived in the person; False otherwise	True
Factors.Threat-Level	String	Threat of person as perceived by police. One of "attack", "undetermined", or "other"; value is "unknown" if not reported.	"attack"
Factors.Fleeing	String	Means by which person was fleeing (e.g., "Car", "Foot") or "Not fleeing"; value is "unknown" if not reported.	"Not fleeing"
Shooting.Manner

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.

This is a collection of Offenses Known and Clearances By Arrest data from 1960 to 2016. The monthly zip files contain one data file per year(57 total, 1960-2016) as well as a codebook for each year. These files have been read into R using the ASCII and setup files from ICPSR (or from the FBI for 2016 data) using the package asciiSetupReader. The end of the zip folder's name says what data type (R, SPSS, SAS, Microsoft Excel CSV, feather, Stata) the data is in. Due to file size limits on open ICPSR, not all file types were included for all the data.

The files are lightly cleaned. What this means specifically is that column names and value labels are standardized. In the original data column names were different between years (e.g. the December burglaries cleared column is "DEC_TOT_CLR_BRGLRY_TOT" in 1975 and "DEC_TOT_CLR_BURG_TOTAL" in 1977). The data here have standardized columns so you can compare between years and combine years together. The same thing is done for values inside of columns. For example, the state column gave state names in some years, abbreviations in others. For the code uses to clean and read the data, please see my GitHub file here. https://github.com/jacobkap/crime_data/blob/master/R_code/offenses_known.R

The zip files labeled "yearly" contain yearly data rather than monthly. These also contain far fewer descriptive columns about the agencies in an attempt to decrease file size. Each zip folder contains two files: a data file in whatever format you choose and a codebook. The data file is aggregated yearly and has already combined every year 1960-2016. For the code I used to do this, see here https://github.com/jacobkap/crime_data/blob/master/R_code/yearly_offenses_known.R.

If you find any mistakes in the data or have any suggestions, please email me at jkkaplan6@gmail.com

As a description of what UCR Offenses Known and Clearances By Arrest data contains, the following is copied from ICPSR's 2015 page for the data.

The Uniform Crime Reporting Program Data: Offenses Known and Clearances By Arrest dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.