In 2020, **** percent of full-time sworn officers in local police departments in the United States were white, followed by **** percent who were Hispanic.

In 2023, ** offenders who killed law enforcement officers in the United States were of an unknown race or their race was not reported to the FBI. ** white offenders and ** Black offenders also killed law enforcement officers in that year. From the total of known offenders that year, ** were male.

This dataset contains Phoenix Police Department officer demographics as of January 1st of each year starting in 2018. All ranks of sworn employees are included.

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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 data was obtained from https://mappingpoliceviolence.us/.

Mapping Police Violence is a 501(c)(3) organization that publishes the most comprehensive and up-to-date data on police violence in America to support transformative change.

This is a database set on openly sharing information on police violence in America.

Some information on this data according to their website: Our data has been meticulously sourced from official police use of force data collection programs in states like California, Texas and Virginia, combined with nationwide data from The Gun Violence Archive and the Fatal Encounters database, two impartial crowdsourced databases. We've also done extensive original research to further improve the quality and completeness of the data; searching social media, obituaries, criminal records databases, police reports and other sources to identify the race of 90 percent of all victims in the database.

We believe the data represented on this site is the most comprehensive accounting of people killed by police since 2013. Note that the Mapping Police Violence database is more comprehensive than the Washington Post police shootings database: while WaPo only tracks cases where people are fatally shot by on-duty police officers, our database includes additional incidents such as cases where police kill someone through use of a chokehold, baton, taser or other means as well as cases such as killings by off-duty police. A recent report from the Bureau of Justice Statistics estimated approximately 1,200 people were killed by police between June, 2015 and May, 2016. Our database identified 1,100 people killed by police over this time period. While there are undoubtedly police killings that are not included in our database (namely, those that go unreported by the media), these estimates suggest that our database captures 92% of the total number of police killings that have occurred since 2013. We hope these data will be used to provide greater transparency and accountability for police departments as part of the ongoing work to end police violence in America.

In compliance with the 2015 Racial Identity Profiling Act, the Long Beach Police Department was one of seven law enforcement agencies required to begin collecting stop data on January 1, 2019, for individuals stopped by police and consensual encounters that resulted in a search. The Department will collect data for each calendar year and will submit the data to the California Department of Justice on an annual basis.

Data elements collected include demographic information of the stopped individuals that is perceived by the officer. This demographic information consists of race/ethnicity, gender, LGBT identity, age, English fluency, and perceived or known disability. The date, time, location, reason for stop, actions taken, contraband/evidence discovered, property seized, and result of stop are also included in the data collected.

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.

This special topic poll, conducted January 21-24, 2001, assessed respondents' opinions about the New York City Police Department (NYCPD). Inhabitants of New York City (NYC) gave their opinions on the way Rudolph Giuliani was handling his job as mayor, the way the police in NYC were doing their jobs, occupational dangers for the police, race relations and life conditions in NYC, and racial profiling and brutality against minorities by the NYCPD. Respondents were also asked whether the NYCPD was a good place to work, whether they wanted to join the NYCPD, and whether their parents and friends would approve if they wanted to become police officers. The survey investigated whether police officers were appreciated by their communities and vice versa, whether police officers showed respect toward society, whether respondents had been in situations where they felt in personal danger or safer because of a police officer, and whether the city should require the police force to live in NYC. Those polled were also asked about their employment status and school attendance, family financial situation, whether they had relatives/friends who worked in NYC as police officers, and whether they or their family members had been the victims of a crime in NYC in the last year. Background information on respondents includes age, gender, education, race/ethnic identity, religion, political party affiliation, political orientation, marital status, and household income.

This data contains information related to officer-initated stops by the City of Boulder Police Department. Information on the demographics of the person stopped (sex, race, ethnicity, year of birth, whether they are a Boulder resident) is included in this file. See the "Outcomes of Police Stops" dataset for more details on the outcome of the stop (stop location, duration, search, and result). This demographic data is collected at the stop level, and no individual-level identifiers are recorded in the system during a stop.The data published are limited to stops where the officer initiated, or had discretion, in making a stop. Instances where an officer is responding to a community or police call are considered non-discretionary, and demographics information is not collected for those stops and not included here. There are some instances of non-discretion within a stop interaction as well. For example, there may be instances where there is an outstanding felony warrant for the person stopped, and by law the officer must arrest that person.Please read the methodology and data dictionary documents for more information. The fields for this demographics dataset are referred to as the "Main" file in the data dictionary.

In 2023, the majority of law enforcement officers that were killed in the United States were white. That year, ** white law enforcement officers as well as **** Black officers were killed. Overall, a total of ** law enforcement officers were killed in the United States in that year.

We report the first empirical estimates of the race-specific effects of larger police forces in the United States. Each additional police officer abates approximately 0.1 homicides. In per capita terms, effects are twice as large for Black versus white victims. Larger police forces also make fewer arrests for serious crimes, with larger reductions for crimes with Black suspects, implying that police force growth does not increase racial disparities among the most serious charges. At the same time, larger police forces make more arrests for low-level "quality of life" offenses, with effects that imply a disproportionate impact for Black Americans.

Fatal police shootings in the United States continue to be a polarizing social and political issue. Clear disagreement between racial proportions of victims and nationwide racial demographics together with graphic video footage has created fertile ground for controversy. However, simple population level summary statistics fail to take into account fundamental local characteristics such as county-level racial demography, local arrest demography, and law enforcement density. Using data on fatal police shootings between January 2015 and July 2016, I implement a number of straightforward resampling procedures designed to carefully examine how unlikely the victim totals from each race are with respect to these local population characteristics if no racial bias were present in the decision to shoot by police. I present several approaches considering the shooting locations both as fixed and also as a random sample. In both cases, I find overwhelming evidence of a racial disparity in shooting victims with respect to local population demographics but substantially less disparity after accounting for local arrest demographics. I conclude the analyses by examining the effect of police-worn body cameras and find no evidence that the presence of such cameras impacts the racial distribution of victims. Supplementary materials for this article are available online.

The race of persons stopped by the San Diego Police Department, as perceived by the officer conducting the stop. This data is collected according to requirements set forth in Government Code section 12525.5 that was enacted as a result of the Racial and Identity Profiling Act of 2015 (AB 953), also known as RIPA. The file contains one row per perceived race per person stopped by Police. An officer may perceive more than one race for a person stopped. The person stopped is uniquely identified in the pid field, and the stop is uniquely identified in the stop_id field. These two fields can be used to join this dataset to the other RIPA datasets available at the following links: (Deprecated) Actions taken Contraband and/or evidence found Disability of persons Force Actions (Deprecated) Gender of persons Non-Force Actions Basis for property seizure Property seized Basis for searches conducted Reason for stop Result of stop Stop details For more information about RIPA regulations, see the California Code of Regulations final text.

Related Tables / Normalized VersionThis dataset provides demographic information related to arrests made by the Tempe Police Department. Demographic fields include race and ethnicity, age range at the time of arrest, and gender for each party. The data is sourced from the Police Department’s Records Management System (RMS) and supports analysis of patterns related to arrests, enforcement activity, and demographic trends over time. This information is a component of ongoing efforts to promote transparency and provide context for law enforcement within the community.For detailed guidance on interpreting arrest counts and demographic breakdowns, please refer to the User Guide: Understanding the Arrest Demographic Datasets - Related Tables.Why this Dataset is Organized this Way?The related tables such as persons, charges, and locations follow a normalized data model. This structure is often preferred by data professionals for more advanced analysis, filtering, or joining with external datasets.Providing this format supports a wide range of users, from casual data explorers to experienced analysts.Understanding the Arrests Data (as related tables)The related tables represent different parts of the arrest data. Each one focuses on a different type of information, like the officers, individuals arrested, charges, and arrest details.All of these tables connect back to the arrests table, which acts as the central record for each event. This structure is called a normalized model and is often used to manage data in a more efficient way. Visit the User Guide: Understanding the Arrest Demographic Datasets - Related Tables for more details outlining the relationships between the related tables.Data DictionaryAdditional InformationContact Email: PD_DataRequest@tempe.govContact Phone: N/ALink: N/AData Source: Versaterm RMSData Source Type: SQL ServerPreparation Method: Automated processPublish Frequency: DailyPublish Method: Automatic

Content

Police Residence

This folder contains data behind the story Most Police Don’t Live In The Cities They Serve.

Includes the cities with the 75 largest police forces, with the exception of Honolulu for which data is not available. All calculations are based on data from the U.S. Census.

The Census Bureau numbers are potentially going to differ from other counts for three reasons:

1. The census category for police officers also includes sheriffs, transit police and others who might not be under the same jurisdiction as a city’s police department proper. The census category won’t include private security officers.
2. The census data is estimated from 2006 to 2010; police forces may have changed in size since then.
3. There is always a margin of error in census numbers; they are estimates, not complete counts.

How to read police-locals.csv

Note: When a cell contains ** it means that there are fewer than 100 police officers of that race serving that city.

Context

This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using GitHub's API and Kaggle's API.

This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

ADDED 5 SEP 2021: Contracts for 140 police departments

This dataset is Part 2 of a three-part series that pulls together data from several different sources regarding police-related violence and racial equity in the United States. The datasets currently include these types of data:

Part 1: Citizen deaths, police deaths, and other outcomes - Police shootings - Citizen fatalities involving police - Police officer deaths suffered in the line of duty

**Part 2: Demographics, crime stats, protests, and other data - Social and economic data - Political leanings of citizens - Sales of DoD equipment to law enforcement agencies - City budgets - Police department headcounts - Police department policies and contract provisions - Juvenile arrests by type of crime and race - Crimes and arrests for the prime city in the four largest metro areas. - Protest activity - Police response - Press activity - Video clips of incidents

I don't believe that any amount of data can fully describe the social dysfunction we have. At the same time, I hope these datasets can be an objective source for providing thoughtful, fact-based analysis of this important issue.

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.

The data shows the number and percentage of people working for the police, by ethnicity. It covers the 43 police forces in England and Wales, and the British Transport Police. Data is shown by: ethnicity (police officers) ethnicity over time (police officers) ethnicity and area (police officers) ethnicity and rank over time (police officers) role and percentage of ethnic group (all police staff) ethnicity (special constables only)

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.

In 1980, the National Institute of Justice awarded a grant to the Cornell University College of Human Ecology for the establishment of the Center for the Study of Race, Crime, and Social Policy in Oakland, California. This center mounted a long-term research project that sought to explain the wide variation in crime statistics by race and ethnicity. Using information from eight ethnic communities in Oakland, California, representing working- and middle-class Black, White, Chinese, and Hispanic groups, as well as additional data from Oakland's justice systems and local organizations, the center conducted empirical research to describe the criminalization process and to explore the relationship between race and crime. The differences in observed patterns and levels of crime were analyzed in terms of: (1) the abilities of local ethnic communities to contribute to, resist, neutralize, or otherwise affect the criminalization of its members, (2) the impacts of criminal justice policies on ethnic communities and their members, and (3) the cumulative impacts of criminal justice agency decisions on the processing of individuals in the system. Administrative records data were gathered from two sources, the Alameda County Criminal Oriented Records Production System (CORPUS) (Part 1) and the Oakland District Attorney Legal Information System (DALITE) (Part 2). In addition to collecting administrative data, the researchers also surveyed residents (Part 3), police officers (Part 4), and public defenders and district attorneys (Part 5). The eight study areas included a middle- and low-income pair of census tracts for each of the four racial/ethnic groups: white, Black, Hispanic, and Asian. Part 1, Criminal Oriented Records Production System (CORPUS) Data, contains information on offenders' most serious felony and misdemeanor arrests, dispositions, offense codes, bail arrangements, fines, jail terms, and pleas for both current and prior arrests in Alameda County. Demographic variables include age, sex, race, and marital status. Variables in Part 2, District Attorney Legal Information System (DALITE) Data, include current and prior charges, days from offense to charge, disposition, and arrest, plea agreement conditions, final results from both municipal court and superior court, sentence outcomes, date and outcome of arraignment, disposition, and sentence, number and type of enhancements, numbers of convictions, mistrials, acquittals, insanity pleas, and dismissals, and factors that determined the prison term. For Part 3, Oakland Community Crime Survey Data, researchers interviewed 1,930 Oakland residents from eight communities. Information was gathered from community residents on the quality of schools, shopping, and transportation in their neighborhoods, the neighborhood's racial composition, neighborhood problems, such as noise, abandoned buildings, and drugs, level of crime in the neighborhood, chances of being victimized, how respondents would describe certain types of criminals in terms of age, race, education, and work history, community involvement, crime prevention measures, the performance of the police, judges, and attorneys, victimization experiences, and fear of certain types of crimes. Demographic variables include age, sex, race, and family status. For Part 4, Oakland Police Department Survey Data, Oakland County police officers were asked about why they joined the police force, how they perceived their role, aspects of a good and a bad police officer, why they believed crime was down, and how they would describe certain beats in terms of drug availability, crime rates, socioeconomic status, number of juveniles, potential for violence, residential versus commercial, and degree of danger. Officers were also asked about problems particular neighborhoods were experiencing, strategies for reducing crime, difficulties in doing police work well, and work conditions. Demographic variables include age, sex, race, marital status, level of education, and years on the force. In Part 5, Public Defender/District Attorney Survey Data, public defenders and district attorneys were queried regarding which offenses were increasing most rapidly in Oakland, and they were asked to rank certain offenses in terms of seriousness. Respondents were also asked about the public's influence on criminal justice agencies and on the performance of cert