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This dataset contains information on fatal police deaths in the United States. The data includes the victim's rank, name, department, date of death, and cause of death. The data spans from 1791 to the present day. This dataset will be updated on monthly basis. Data Scrapped from this website :- https://www.odmp.org/
New Version Features -> With the new web scrapper I have upgraded dataset with more information. 1) The new dataset version is "police_deaths_USA_v6.csv" and "k9_deaths_USA_v6.csv". 2) Splitted the dataset into 2 different datasets 1 for Human Unit and other for K9 Unit. 3) Check out the new web scrapper code in this file "final_scrapper_program_with_comments.ipynb". 4) Also added the correction file which is needed to adjust some data points from K9 dataset. 5) Extended data of Human Unit dataset to 13 Features. 6) Extended data of K9 Unit dataset to 14 Features.
The police_deaths dataset contains 13 variables:
1) Rank -> Rank assigned or achieved by the police throughout their tenure.
2) Name -> The name of the person.
3) Age -> Age of the person.
4) End_Of_Watch -> The death date on which the the person declared as dead.
5) Day_Of_Week -> The day of the week [Sunday, Monday, etc.].
6) Cause -> The cause of the death.
7) Department -> The department's name where the person works.
8) State -> The state where the department is situated.
9) Tour -> The Duration of there Tenure.
10) Badge -> Badge of the person.
11) Weapon -> The Weapon by which the officer has been killed.
12) Offender -> Offender / Killer this says what happened to the offender after the incident was he/she [Arrested, Killed, etc.].
13) Summary -> Summary of the police officer and also the summary of the incident of what happened ? How he/she died ?, etc.
The k9_deaths dataset contains 14 variables:
1) Rank -> Rank assigned or achieved by the K9 throughout their tenure.
2) Name -> The name of the K9.
3) Breed -> Breed of the K9.
4) Gender -> Gender of the K9.
5) Age -> Age of the K9.
6) End_Of_Watch -> The death date on which the the person declared as dead.
7) Day_Of_Week -> The day of the week [Sunday, Monday, etc.].
8) Cause -> The cause of the death.
9) Department -> The department's name where the K9 was assigned.
10) State -> The state where the department is situated.
11) Tour -> The Duration of there Tenure.
12) Weapon -> The Weapon by which the officer has been killed.
13) Offender -> Offender / Killer this says what happened to the offender after the incident was he/she [Arrested, Killed, etc.].
14) Summary -> Summary of the K9 dog and also the summary of the incident of what happened ? How he/she died ?, etc.
Acknowledgements:
The original dataset was collected by FiveThirtyEight and it contains police death data from 1791 to 2016. Here is the link -> https://data.world/fivethirtyeight/police-deaths.
The reason I made this dataset is because it had not been updated since 2016 and the scrapping script was outdated, so I decided to make a new scrapper and update the dataset till present. I got this idea from the FiveThirtyEight group and a fellow kaggler, Satoshi Datamoto, who uploaded the dataset on kaggle. Thank you for inspiration.
Tableau Visualization link :- https://public.tableau.com/app/profile/mayuresh.koli/viz/USALawEnforcementLineofDutyDeaths/main_dashboard
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TwitterThis data collection was undertaken to gather information on the extent of police officers' knowledge of search and seizure law, an issue with important consequences for law enforcement. A specially-produced videotape depicting line duty situations that uniformed police officers frequently encounter was viewed by 478 line uniformed police officers from 52 randomly-selected cities in which search and seizure laws were determined to be no more restrictive than applicable United States Supreme Court decisions. Testing of the police officers occurred in all regions as established by the Federal Bureau of Investigation, except for the Pacific region (California, Oregon, and Washington), since search and seizure laws in these states are, in some instances, more restrictive than United States Supreme Court decisions. No testing occurred in cities with populations under 10,000 because of budget limitations. Fourteen questions to which the officers responded were presented in the videotape. Each police officer also completed a questionnaire that included questions on demographics, training, and work experience, covering their age, sex, race, shift worked, years of police experience, education, training on search and seizure law, effectiveness of various types of training instructors and methods, how easily they could obtain advice about search and seizure questions they encountered, and court outcomes of search and seizure cases in which they were involved. Police department representatives completed a separate questionnaire providing department characteristics and information on search and seizure training and procedures, such as the number of sworn officers, existence of general training and the number of hours required, existence of in-service search and seizure training and the number of hours and testing required, existence of policies and procedures on search and seizure, and means of advice available to officers about search and seizure questions. These data comprise Part 1. For purposes of comparison and interpretation of the police officer test scores, question responses were also obtained from other sources. Part 2 contains responses from 36 judges from states with search and seizure laws no more restrictive than the United States Supreme Court decisions, as well as responses from a demographic and work-experience questionnaire inquiring about their age, law school attendance, general judicial experience, and judicial experience and education specific to search and seizure laws. All geographic regions except New England and the Pacific were represented by the judges. Part 3, Comparison Data, contains answers to the 14 test questions only, from 15 elected district attorneys, 6 assistant district attorneys, the district attorney in another city and 11 of his assistant district attorneys, a police attorney with expertise in search and seizure law, 24 police academy trainees with no previous police work experience who were tested before search and seizure law training, a second group of 17 police academy trainees -- some with police work experience but no search and seizure law training, 55 law enforcement officer trainees from a third academy tested immediately after search and seizure training, 7 technical college students with no previous education or training on search and seizure law, and 27 university criminal justice course students, also with no search and seizure law education or training.
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Twitter"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:
The threat column and the fleeing column are not necessarily related. For example, there is an incident in which the suspect is fleeing and at the same time turns to fire at gun at the officer. Also, attacks represent a status immediately before fatal shots by police while fleeing could begin slightly earlier and involve a chase. - body_camera: News reports have indicated an officer w...
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To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics sponsors a census of the nation's state and local law enforcement agencies, known as the Directory Survey. This census, which is conducted every four years, includes all state and local law enforcement agencies operating nationwide that are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers. As in previous years, the 2004 census collected data on the number of sworn and nonsworn personnel employed by each agency, including both full-time and part-time employees. The pay period that included September 30, 2004, was the reference date for all personnel data. Variables include personnel totals, type of government, type of agency, and whether the agency had the legal authority to hold a person beyond arraignment for 48 or more hours. Previous censuses were conducted in 1986 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1986: [UNITED STATES] [ICPSR 8696]), 1992 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1992: [UNITED STATES] [ICPSR 2266]), 1996 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1996: [UNITED STATES] [ICPSR 2260]), and 2000 (Census of State and Local Law Enforcement Agencies (CSLLEA), 2000: [United States] [ICPSR 3484]).
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TwitterThis study was undertaken to provide current information on work and family issues from the police officer's perspective, and to explore the existence and prevalence of work and family training and intervention programs offered nationally by law enforcement agencies. Three different surveys were employed to collect data for this study. First, a pilot study was conducted in which a questionnaire, designed to elicit information on work and family issues in law enforcement, was distributed to 1,800 law enforcement officers representing 21 municipal, suburban, and rural police agencies in western New York State (Part 1). Demographic information in this Work and Family Issues in Law Enforcement (WFILE) questionnaire included the age, gender, ethnicity, marital status, highest level of education, and number of years in law enforcement of each respondent. Respondents also provided information on which agency they were from, their job title, and the number of children and step-children they had. The remaining items on the WFILE questionnaire fell into one of the following categories: (1) work and family orientation, (2) work and family issues, (3) job's influence on spouse/significant other, (4) support by spouse/significant other, (5) influence of parental role on the job, (6) job's influence on relationship with children, (7) job's influence on relationships and friendships, (8) knowledge of programs to assist with work and family issues, (9) willingness to use programs to assist with work and family issues, (10) department's ability to assist officers with work and family issues, and (11) relationship with officer's partner. Second, a Police Officer Questionnaire (POQ) was developed based on the results obtained from the pilot study. The POQ was sent to over 4,400 officers in police agencies in three geographical locations: the Northeast (New York City, New York, and surrounding areas), the Midwest (Minneapolis, Minnesota, and surrounding areas), and the Southwest (Dallas, Texas, and surrounding areas) (Part 2). Respondents were asked questions measuring their health, exercise, alcohol and tobacco use, overall job stress, and the number of health-related stress symptoms experienced within the last month. Other questions from the POQ addressed issues of concern to the Police Research and Education Project -- a sister organization of the National Association of Police Organizations -- and its membership. These questions dealt with collective bargaining, the Law Enforcement Officer's Bill of Rights, residency requirements, and high-speed pursuit policies and procedures. Demographic variables included gender, age, ethnicity, marital status, highest level of education, and number of years employed in law enforcement. Third, to identify the extent and nature of services that law enforcement agencies provided for officers and their family members, an Agency Questionnaire (AQ) was developed (Part 3). The AQ survey was developed based on information collected from previous research efforts, the Violent Crime Control and Law Enforcement Act of 1994 (Part W-Family Support, subsection 2303 [b]), and from information gained from the POQ. Data collected from the AQ consisted of whether the agency had a mission statement, provided any type of mental health service, and had a formalized psychological services unit. Respondents also provided information on the number of sworn officers in their agency and the gender of the officers. The remaining questions requested information on service providers, types of services provided, agencies' obstacles to use of services, agencies' enhancement of services, and the organizational impact of the services.
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TwitterThese data on 19th- and early 20th-century police department and arrest behavior were collected between 1975 and 1978 for a study of police and crime in the United States. Raw and aggregated time-series data are presented in Parts 1 and 3 on 23 American cities for most years during the period 1860-1920. The data were drawn from annual reports of police departments found in the Library of Congress or in newspapers and legislative reports located elsewhere. Variables in Part 1, for which the city is the unit of analysis, include arrests for drunkenness, conditional offenses and homicides, persons dismissed or held, police personnel, and population. Part 3 aggregates the data by year and reports some of these variables on a per capita basis, using a linear interpolation from the last decennial census to estimate population. Part 2 contains data for 267 United States cities for the period 1880-1890 and was generated from the 1880 federal census volume, REPORT ON THE DEFECTIVE, DEPENDENT, AND DELINQUENT CLASSES, published in 1888, and from the 1890 federal census volume, SOCIAL STATISTICS OF CITIES. Information includes police personnel and expenditures, arrests, persons held overnight, trains entering town, and population.
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TwitterThe purpose of the study was to investigate how and why injuries occur to police and citizens during use of force events. The research team conducted a national survey (Part 1) of a stratified random sample of United States law enforcement agencies regarding the deployment of, policies for, and training with less lethal technologies. Finalized surveys were mailed in July 2006 to 950 law enforcement agencies, and a total of 518 law enforcement agencies provided information on less lethal force generally and on their deployment and policies regarding conducted energy devices (CEDs) in particular. A total of 292 variables are included in the National Use of Force Survey Data (Part 1) including items about weapons deployment, force policies, training, force reporting/review, force incidents and outcomes, and conducted energy devices (CEDs). Researchers also collected agency-supplied use of force data from law enforcement agencies in Richland County, South Carolina; Miami-Dade, Florida; and Seattle, Washington; to identify individual and situational predictors of injuries to officers and citizens during use of force events. The Richland County, South Carolina Data (Part 2) include 441 use-of-force reports from January 2005 through July 2006. Part 2 contains 17 variables including whether the officer or suspect was injured, 8 measures of officer force, 3 measures of suspect resistance, the number of witnesses and officers present at each incident, and the number of suspects that resisted or assaulted officers for each incident. The Miami-Dade County, Florida Data (Part 3) consist of 762 use-of-force incidents that occurred between January 2002 and May 2006. Part 3 contains 15 variables, including 4 measures of officer force, the most serious resistance on the part of the suspect, whether the officer or suspect was injured, whether the suspect was impaired by drugs or alcohol, the officer's length of service in years, and several demographic variables pertaining to the suspect and officer. The Seattle, Washington Data (Part 4) consist of 676 use-of-force incidents that occurred between December 1, 2005, as 15 variables, including 3 measures of officer force, whether the suspect or officer was injured, whether the suspect was impaired by drugs or alcohol, whether the suspect used, or threatened to use, physical force against the officer(s), and several demographic variables relating to the suspect and officer(s). The researchers obtained use of force survey data from several large departments representing different types of law enforcement agencies (municipal, county, sheriff's department) in different states. The research team combined use of force data from multiple agencies into a single dataset. This Multiagency Use of Force Data (Part 5) includes 24,928 use-of-force incidents obtained from 12 law enforcement agencies from 1998 through 2007. Part 5 consists a total of 21 variables, including the year the incident took place, demographic variables relating to the suspect, the type of force used by the officer, whether the suspect or officer was injured, and 5 measures of the department's policy regarding the use of CEDs and pepper spray. Lastly, longitudinal data were also collected for the Orlando, Florida and Austin, Texas police departments. The Orlando, Florida Longitudinal Data (Part 6) comprise 4,222 use-of-force incidents aggregated to 108 months -- a 9 year period from 1998 through 2006. Finally, the Austin, Texas Longitudinal Data (Part 7) include 6,596 force incidents aggregated over 60 months- a 5 year period from 2002 through 2006. Part 6 and Part 7 are comprised of seven variables documenting whether a Taser was implemented, the number of suspects and officers injured in a month, the number of force incidents per month, and the number of CEDs uses per month.
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License information was derived automatically
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.
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TwitterThis survey covered the 2004-2005 academic year and collected data from law enforcement agencies using sworn police officers and those using only non-sworn security officers. Agencies serving 4-year United States universities and colleges with a fall 2004 enrollment of 2,500 or more, and those serving 2-year public colleges with a fall 2004 enrollment of 10,000 or more were surveyed. United States military academies and for-profit institutions were excluded. Data were collected in conjunction with the 2004 BJS Census of State and Local Law Enforcement Agencies. The survey instrument was patterned after the BJS Law Enforcement Management and Administrative Statistics survey. Data were collected describing campus law enforcement agencies, including personnel, expenditures and pay, operations, equipment, computers and information systems, policies, and special programs. BJS conducted an earlier survey of campus law enforcement agencies, covering the 1994-1995 school year. Users can access the data collection from the ICPSR Web site (ICPSR 6846).
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
This information will not be updated while the Cincinnati Police Department undergoes transfer to a new data management system.
Data Description: This data represents documented assaults on officers. Assaults on Officers may be defined as the assault of duly sworn city, university and college, county, state, tribal, and federal law enforcement officers. Incidents that are identified as an assault on an officer can include but are not limited to crimes such as aggravated assault, robbery, theft, vandalism, targeted assault (knowingly harming and officer), and recklessly harming an officer.
Data Creation: This data is recorded using the City's Record Management System (RMS) that stores agency-wide data about law enforcement operations.
Data Created By: The source of this data is the Cincinnati Police Department.
Refresh Frequency: This information will not be updated while the Cincinnati Police Department undergoes transfer to a new data management system.
CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/mrju-z9ui
Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.
Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).
Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad
Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.
DISCLAIMER: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.
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This survey was undertaken to learn more about how often and under what circumstances police-public contact becomes problematic. The Bureau of Justice Statistics (BJS) initiated surveys of the public on their interactions with police in 1996 with the first Police-Public Contact Survey, a pretest among a nationally representative sample of 6,421 persons aged 12 or older. That initial version of the questionnaire revealed that about 20 percent of the public had direct, face-to-face contact with a police officer at least once during the year preceding the survey. At that time, the principal investigator estimated that about 1 in 500 residents, or about a half million people, who had an encounter with a police officer also experienced either a threat of force or the actual use of force by the officer. The current survey, an improved version of the 1996 Police-Public Contact Survey, was fielded as a supplement to the National Crime Victimization Survey (ICPSR 6406) during the last six months of 1999. A national sample nearly 15 times as large as the pretest sample in 1996 was used. The 1999 survey yielded nearly identical estimates of the prevalence and nature of contacts between the public and the police. This survey, because of its much larger sample size, permits more extensive analysis of demographic differences in police contacts than the 1996 pretest. In addition, it added a new and more detailed set of questions about traffic stops by police, the most frequent reason given for contact with police. Variables in the dataset cover type of contact with police, including whether it was face-to-face, initiated by the police or the citizen, whether an injury to the officer or the citizen resulted from the contact, crimes reported, and police use of force. Demographic variables supplied for the citizens include gender, race, and Hispanic origin.
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TwitterThis study sought to examine community policing from a street-level officer's point of view. Active community police officers and sheriff's deputies from law enforcement agencies were interviewed about their opinions, experiences with, and attitudes toward community policing. For the study 90 rank-and-file community policing officers from 30 law enforcement agencies throughout the United States were selected to participate in a 40- to 60-minute telephone interview. The survey was comprised of six sections, providing information on: (1) demographics, including the race, gender, age, job title, highest level of education, and union membership of each respondent, (2) a description of the community policing program and daily tasks, with questions regarding the size of the neighborhood in terms of geography and population, work with citizens and community leaders, patrol methods, activities with youth/juveniles, traditional police duties, and agency and supervisor support of community policing, (3) interaction between community policing and non-community policing officers, (4) hours, safety, and job satisfaction, (5) police training, and (6) perceived effectiveness of community policing.
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To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics periodically sponsors a census of the nation's state and local law enforcement agencies. This census, known as the Directory Survey, gathers data on 49 primary state law enforcement agencies and all sheriffs' departments, local police departments, and special police agencies (state or local) that are publicly funded and employ at least one sworn officer with general arrest powers. The 1996 Directory Survey collected data on the number of sworn and nonsworn personnel employed by each agency, including both full-time and part-time employees. Within the full-time sworn category, data were collected from all agencies on the number who were uniformed officers with regularly assigned duties that included responding to calls for service. For agencies with at least 10 full-time sworn officers, the number whose primary duties were related to investigations, court operations, or jail operations was also obtained. This data collection, compiled in June 1996, represents the third such census, with the first occurring in 1986 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1986: [UNITED STATES] [ICPSR 8696]) and the second in 1992 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1992: [UNITED STATES] [ICPSR 2266]). Variables include personnel totals, type of government, type of agency, and whether the agency had the legal authority to hold a person beyond arraignment for 48 or more hours.
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TwitterOn a typical day in the United States, police officers make more than 50,000 traffic stops. The Stanford Open Policing Project team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Their goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.
If you'd like to see data regarding other states, please go to https://www.kaggle.com/stanford-open-policing.
This dataset includes over 1 gb of stop data from Ohio. Please see the data readme for the full details of the available fields.
This dataset was kindly made available by the Stanford Open Policing Project. If you use it for a research publication, please cite their working paper: E. Pierson, C. Simoiu, J. Overgoor, S. Corbett-Davies, V. Ramachandran, C. Phillips, S. Goel. (2017) “A large-scale analysis of racial disparities in police stops across the United States”.
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This data collection investigates the ways in which police use reports of drug-related crimes provided by residents of high drug/crime areas and how willing residents of these areas are to report such crimes to the police. Structured interviews were conducted by telephone with police representatives in most of the nation's 50 largest cities and in person with residents and police officers in high drug/crime districts in each of four major cities: Newark, Chicago, El Paso, and Philadelphia. Police department representatives were queried about the usefulness of citizen reports, reasons for citizens' reluctance to make reports, how the rate of citizen reports could be improved, and how citizen reports worked with other community crime prevention strategies. Residents were asked about their tenure in the neighborhood, attitudes toward the quality of life in the neighborhood, major social problems facing the neighborhood, and quality of city services such as police and fire protection, garbage collection, and public health services. Additional questions were asked about the amount of crime in the neighborhood, the amount of drug use and drug-related crime, and the fear of crime. Basic demographic information such as sex, race, and language in which the interview was conducted is also provided.
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The UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2020 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.
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TwitterSadly, 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.
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This study developed interval-level measurement scales for evaluating police officer performance during real or simulated deadly force situations. Through a two-day concept mapping focus group, statements were identified to describe two sets of dynamics: the difficulty (D) of a deadly force situation and the performance (P) of a police officer in that situation. These statements were then operationalized into measurable Likert-scale items that were scored by 291 use of force instructors from more than 100 agencies across the United States using an online survey instrument. The dataset resulting from this process contains a total of 685 variables, comprised of 312 difficulty statement items, 278 performance statement items, and 94 variables that measure the demographic characteristics of the scorers.
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TwitterInvestigator(s): Bureau of Justice Statistics In 1995, to determine the nature of law enforcement services provided on campus, the Bureau of Justice Statistics (BJS) surveyed four-year institutions of higher education in the United States with 2,500 or more students. This survey describes nearly 600 of these campus law enforcement agencies in terms of their personnel, expenditures and pay, operations, equipment, computers and information systems, policies, and special programs. The survey was based on the BJS Law Enforcement Management and Administrative Statistics (LEMAS) program, which collected similar data from a national sample of state and local law enforcement agencies.
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TwitterChicago Police district station locations and contact information.
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This dataset contains information on fatal police deaths in the United States. The data includes the victim's rank, name, department, date of death, and cause of death. The data spans from 1791 to the present day. This dataset will be updated on monthly basis. Data Scrapped from this website :- https://www.odmp.org/
New Version Features -> With the new web scrapper I have upgraded dataset with more information. 1) The new dataset version is "police_deaths_USA_v6.csv" and "k9_deaths_USA_v6.csv". 2) Splitted the dataset into 2 different datasets 1 for Human Unit and other for K9 Unit. 3) Check out the new web scrapper code in this file "final_scrapper_program_with_comments.ipynb". 4) Also added the correction file which is needed to adjust some data points from K9 dataset. 5) Extended data of Human Unit dataset to 13 Features. 6) Extended data of K9 Unit dataset to 14 Features.
The police_deaths dataset contains 13 variables:
1) Rank -> Rank assigned or achieved by the police throughout their tenure.
2) Name -> The name of the person.
3) Age -> Age of the person.
4) End_Of_Watch -> The death date on which the the person declared as dead.
5) Day_Of_Week -> The day of the week [Sunday, Monday, etc.].
6) Cause -> The cause of the death.
7) Department -> The department's name where the person works.
8) State -> The state where the department is situated.
9) Tour -> The Duration of there Tenure.
10) Badge -> Badge of the person.
11) Weapon -> The Weapon by which the officer has been killed.
12) Offender -> Offender / Killer this says what happened to the offender after the incident was he/she [Arrested, Killed, etc.].
13) Summary -> Summary of the police officer and also the summary of the incident of what happened ? How he/she died ?, etc.
The k9_deaths dataset contains 14 variables:
1) Rank -> Rank assigned or achieved by the K9 throughout their tenure.
2) Name -> The name of the K9.
3) Breed -> Breed of the K9.
4) Gender -> Gender of the K9.
5) Age -> Age of the K9.
6) End_Of_Watch -> The death date on which the the person declared as dead.
7) Day_Of_Week -> The day of the week [Sunday, Monday, etc.].
8) Cause -> The cause of the death.
9) Department -> The department's name where the K9 was assigned.
10) State -> The state where the department is situated.
11) Tour -> The Duration of there Tenure.
12) Weapon -> The Weapon by which the officer has been killed.
13) Offender -> Offender / Killer this says what happened to the offender after the incident was he/she [Arrested, Killed, etc.].
14) Summary -> Summary of the K9 dog and also the summary of the incident of what happened ? How he/she died ?, etc.
Acknowledgements:
The original dataset was collected by FiveThirtyEight and it contains police death data from 1791 to 2016. Here is the link -> https://data.world/fivethirtyeight/police-deaths.
The reason I made this dataset is because it had not been updated since 2016 and the scrapping script was outdated, so I decided to make a new scrapper and update the dataset till present. I got this idea from the FiveThirtyEight group and a fellow kaggler, Satoshi Datamoto, who uploaded the dataset on kaggle. Thank you for inspiration.
Tableau Visualization link :- https://public.tableau.com/app/profile/mayuresh.koli/viz/USALawEnforcementLineofDutyDeaths/main_dashboard