Gun Violence Dataset Overview (Mass Shootings in 2024)

This dataset provides an in-depth look at mass shootings across the United States in 2024, up until October 20th, sourced from the Gun Violence Archive. It captures essential details such as incident ID, date, state, city, victims (killed and injured), and suspects involved. Additionally, geographical coordinates are included to allow for spatial analysis of gun violence trends.

Key Features of the Dataset

• Incident IDs: A unique identifier for each incident, categorized and grouped based on their range.
• Incident Date: Captures the time period over which the incidents occurred, broken down into monthly intervals.
• State and City/County: A breakdown of incidents across various states and cities, identifying regions with the most gun violence activity.
• Victims Killed and Injured: Provides a count of victims in each incident, allowing for the analysis of both fatal and non-fatal outcomes.
• Suspects Killed, Injured, and Arrested: Captures data related to suspects involved in the incidents, including their status post-incident (e.g., killed, injured, or arrested).
• Latitude and Longitude: Geographical coordinates for the locations of the incidents, enabling mapping and geospatial analysis.
• Coordinates Found: Indicates whether valid geographical coordinates were found for each incident.

This dataset is a comprehensive collection of gun violence incidents, offering insights into both the human toll and geographical spread of mass shootings in 2024. The goal of the analysis is to identify patterns, trends, and areas of concern that can inform public safety measures and policy interventions.

People with Guns Segmentation & Object Detection dataset

The dataset consists of photos depicting individuals holding guns. It specifically focuses on the segmentation of guns within these images and the detection of people holding guns.

Each image in the dataset presents a different scenario, capturing individuals from various backgrounds, genders, and age groups in different poses while holding guns.

💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on our website to buy the dataset

The dataset is an essential resource for the development and evaluation of computer vision models and algorithms in fields related to firearms recognition, security systems, law enforcement, and safety analysis.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F2497edebcdd1b7c4bc5471262bf5bd16%2FFrame%2029.png?generation=1696334547549518&alt=media" alt="">

OTHER DATASETS WITH SEGMENTATION:

• Body Segmentation - 5,300 Photos
• Bald People Segmentation Dataset
• GENERATED USA Passports Segmentation
• Vehicle Images & Segmentation
• Agricultural Image Segmentation

🧩 This is just an example of the data. Leave a request here to learn more

Dataset structure

• images - contains of original images with people holding guns
• labels - includes visualized labeling created for the original images
• annotations.xml - contains coordinates of the polygons and bounding boxes, created for the original photo

Data Format

Each image from images folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the bounding boxes and polygons. For each point, the x and y coordinates are provided.

Сlasses:

• person: person, who holds the gun, detected with a bounding box,
• gun: gun, labeled with a polygon

Example of XML file structure

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F96bbe14c80f4b494f97136f8ffdbaa44%2Fcarbon.png?generation=1696335385101390&alt=media" alt="">

People with Guns Segmentation & Detection might be made in accordance with your requirements.

🚀 You can learn more about our high-quality unique datasets here

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This study was undertaken to obtain information on the characteristics of gun ownership, gun-carrying practices, and weapons-related incidents in the United States -- specifically, gun use and other weapons used in self-defense against humans and animals. Data were gathered using a national random-digit-dial telephone survey. The respondents were comprised of 1,905 randomly-selected adults aged 18 and older living in the 50 United States. All interviews were completed between May 28 and July 2, 1996. The sample was designed to be a representative sample of households, not of individuals, so researchers did not interview more than one adult from each household. To start the interview, six qualifying questions were asked, dealing with (1) gun ownership, (2) gun-carrying practices, (3) gun display against the respondent, (4) gun use in self-defense against animals, (5) gun use in self-defense against people, and (6) other weapons used in self-defense. A "yes" response to a qualifying question led to a series of additional questions on the same topic as the qualifying question. Part 1, Survey Data, contains the coded data obtained during the interviews, and Part 2, Open-Ended-Verbatim Responses, consists of the answers to open-ended questions provided by the respondents. Information collected for Part 1 covers how many firearms were owned by household members, types of firearms owned (handguns, revolvers, pistols, fully automatic weapons, and assault weapons), whether the respondent personally owned a gun, reasons for owning a gun, type of gun carried, whether the gun was ever kept loaded, kept concealed, used for personal protection, or used for work, and whether the respondent had a permit to carry the gun. Additional questions focused on incidents in which a gun was displayed in a hostile manner against the respondent, including the number of times such an incident took place, the location of the event in which the gun was displayed against the respondent, whether the police were contacted, whether the individual displaying the gun was known to the respondent, whether the incident was a burglary, robbery, or other planned assault, and the number of shots fired during the incident. Variables concerning gun use by the respondent in self-defense against an animal include the number of times the respondent used a gun in this manner and whether the respondent was hunting at the time of the incident. Other variables in Part 1 deal with gun use in self-defense against people, such as the location of the event, if the other individual knew the respondent had a gun, the type of gun used, any injuries to the respondent or to the individual that required medical attention or hospitalization, whether the incident was reported to the police, whether there were any arrests, whether other weapons were used in self-defense, the type of other weapon used, location of the incident in which the other weapon was used, and whether the respondent was working as a police officer or security guard or was in the military at the time of the event. Demographic variables in Part 1 include the gender, race, age, household income, and type of community (city, suburb, or rural) in which the respondent lived. Open-ended questions asked during the interview comprise the variables in Part 2. Responses include descriptions of where the respondent was when he or she displayed a gun (in self-defense or otherwise), specific reasons why the respondent displayed a gun, how the other individual reacted when the respondent displayed the gun, how the individual knew the respondent had a gun, whether the police were contacted for specific self-defense events, and if not, why not.

In the United States, gun laws vary from one state to the next; whether residents need a permit or a background check to purchase a firearm, whether residents must undergo firearm training before making this purchase, and whether residents can openly carry their guns in public is dependent upon state legislation. As of January 15, 2025, ** U.S. states required background checks and/or permits for the purchase of a handgun. A further ** states had regulations on openly carrying firearms in public; however, only California, Connecticut, Florida, and Illinois had completely prohibited open carry for all firearms. In comparison, Maryland, New Jersey, and New York prohibited open carry for handguns but either did not have regulations in place or required a permit for other types of guns. A constitutional right The Second Amendment of the Constitution, which states that citizens have the right to bear arms, has made it difficult for any gun control legislation to be passed on a national level in the United States. As a result, gun control laws in the U.S. are state-based, and often differ based on political perspectives. States with strong gun laws in place, such as Massachusetts, generally experience less gun violence, however, some states with strong gun laws, such as Maryland, continue to face high rates of gun violence, which has largely been attributed to gun trafficking activity found throughout the nation. A culture of gun owners In comparison to other high-income countries with stricter gun control laws, the United States has the highest gun homicide rate at **** gun homicides per 100,000 residents. However, despite increasing evidence that easy access to firearms, whether legal or illegal, encourages higher rates of gun violence, the United States continues to foster an environment in which owning a firearm is seen as personal freedom. Almost **** of U.S. households have reported owning at least one firearm and ** percent of registered voters in the U.S. were found to believe that it was more important to protect the right of Americans to own guns, compared to ** percent who said it was more important to limit gun ownership.

THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

1) Data Introduction • The Gun Violence Dataset in US is a tabularized data set for gun violence analysis that includes the date, location, victim and suspect information, and geographic coordinates of major 2024 shootings across the U.S.

2) Data Utilization (1) Gun Violence Dataset in US has characteristics that: • Each row contains key information about the shooting, including incident-specific ID, date of occurrence, state and city/county, number of deaths and injuries, suspects (death, injury, arrest), latitude, and longitude. • Data is designed to analyze the distribution of gun incidents and the extent of damage by month and region, and spatial analysis through geographic coordinates is also possible. (2) Gun Violence Dataset in US can be used to: • Analysis of shooting trends by region: Use data by location, magnitude of damage, and time to visualize and analyze the regional and temporal distribution and risk areas of gun violence. • Establishing public safety policies and prevention strategies: Based on victim and suspect information and incident characteristics, it can be used to establish effective gun control, prevention policies, resource allocation strategies, and more.

Gun ownership in the United States is the highest in the world, and constitutionally protected by the Second Amendment to the United States Constitution. Firearms are widely used in the United States for self-defence, hunting, and recreational uses, such as target shooting.

Source: https://www.kaggle.com/datasets/nidzsharma/us-mass-shootings-19822023

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13190980%2F56c639fee11c268267f9cf4ece33cf6a%2Fnewplot%20(6).png?generation=1680562776580204&alt=media" alt="">

Data columns:

• 0 case
• 1 location
• 2 date
• 3 summary
• 4 fatalities
• 5 injured
• 6 total_victims
• 7 location.1
• 8 age_of_shooter
• 9 prior_signs_mental_health_issues - Cleaned
• 10 mental_health_details - Cleaned
• 11 weapons_obtained_legally
• 12 where_obtained
• 13 weapon_type
• 14 weapon_details
• 15 race - cleaned
• 16 gender - cleaned
• 17 latitude - filled from location with Google Maps API
• 18 longitude - filled from location with Google Maps API
• 19 type
• 20 year - retrieved from date column
• 21 quarter - retrieved from date column
• 22 half - retrieved from date column
• 23 month_name - retrieved from date column
• 24 day_of_week - retrieved from date column
• 25 age_group - "Teenage", "Early Adulthood", "Middle Adulthood", "Old Age"
• 26 decade - retrieved from date
• 27 name - retrieved from splitting summary
• 28 current_age - retrieved from splitting summary
• 29 description - retrieved from splitting summary

The State Firearm Database catalogs the presence or absence of 134 firearm safety laws in 14 categories covering the 26-year period from 1991 to 2019. The classification system categorizes state firearm provisions using a methodology that both captures differences and maintains a level of comparability between states. Because of this, the database is not the most detailed nor the most comprehensive record of all state firearm policies. Other resources may provide users with a deeper understanding of individual provisions, while this database serves as an efficient way to compare the broad scope of state firearm laws across the country. These provisions covered 14 aspects of state policies, including regulation of the process by which firearm transfers take place, ammunition, firearm possession, firearm storage, firearm trafficking, and liability of firearm manufacturers. In addition, descriptions of the criteria used to code each provision have been provided so that there is transparency in how various law exemptions, exceptions, and other nuances were addressed.

Context

1 in 4 mass shooting victims were children and teens. In the years between 2009 and 2020, the horrific scenes of mass shootings have haunted the nation’s collective conscience.US states with weaker gun laws and higher gun ownership rates have higher rates of mass shootings. Mass shooting is defined as any incident in which four or more people are shot and killed, excluding the shooter. The number of mass shootings that plague this country is far too high, and the counts are just a small fraction of the lives left forever changed after the tragedy of a mass shooting. So here is the data for list of mass shootings in United States from 2018 - 2022.

Content

This dataset has five csv files of years 2018 - 2022. Each data contains following attributes - Date : The date on which the mass shooting incident happened - State : The state where the incident took place - Dead : total number of people died in mass shooting - Injured: total number of people who got injured in mass shooting- - Total : total of dead and injured people - Description : description/short report of the incident which may include information like gender/place etc. Data for 2022 Mass shootings will be updated every 15 days!

Acknowledgements

This data was scraped from https://en.wikipedia.org/wiki/List_of_mass_shootings_in_the_United_States using BeautifulSoup.

Image banner by Wall Street Journal

Inspiration

• EDA and Viz.
• Which state has highest number of mass shootings
• Contextual analysis of the description column
• Trend of mass shooting in past years
• Number of people killed/injured on an average in a month.

Check out my other works

• Datasets
• Notebooks

Context

The Gun Violence Archive is an online archive of gun violence incidents collected from over 2,000 media, law enforcement, government and commercial sources daily in an effort to provide near-real time data about the results of gun violence. GVA in an independent data collection and research group with no affiliation with any advocacy organization.

Content

This dataset includes files that separate gun violence incidents by category, including deaths and injuries of children and teens, and a collection of mass shootings.

Inspiration

• What has been the trend of gun violence in the past few years?
• What states have the highest incidents per capita per year? How has this metric changed over time?
• Are officer involved shootings on the rise? Where are they most concentrated? Do they correlate with the rates of accidental deaths and mass shootings?

Acknowledgements

This dataset is owned by the Gun Violence Archive, and can be accessed in its original form here.

The share of American households owning at least one firearm has remained relatively steady since 1972, hovering between ** percent and ** percent. In 2024, about ** percent of U.S. households had at least one gun in their possession. Additional information on firearms in the United States Firearms command a higher degree of cultural significance in the United States than any other country in the world. Since the inclusion of the right to bear arms in the Second Amendment to the Constitution of the United States, firearms have held symbolic power beyond their already obvious material power. Despite many Americans being proud gun-owners, a large movement exists within the country in opposition to the freedom afforded to those in possession of these potentially deadly weapons. Those opposed to current gun regulation have sourced their anger from the large number of deaths due to firearms in the country, as well as the high frequency of gun violence apparent in comparison to other developed countries. Furthermore, the United States has fallen victim to a number of mass shootings in the last two decades, most of which have raised questions over the ease at which a person can obtain a firearm. Although this movement holds a significant position in the public political discourse of the United States, meaningful change regarding the legislation dictating the ownership of firearms has not occurred. Critics have pointed to the influence possessed by the National Rifle Association through their lobbying of public officials. The National Rifle Association also lobbies for the interests of firearm manufacturing in the United States, which has continued to rise since a fall in the early 2000s.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study constructed a comprehensive, longitudinal dataset of all counties nested within U.S. States from 1970 to 2012. The study's main purpose was to facilitate research that would further understanding on firearm legislation and its impacts on violence. This comprehensive data collection effort included information on firearm legislation implemented across U.S. States over time in combination with multiple measures of firearm-related violence and injury. Moreover, to better understand the conditions under which firearm legislation is more or less effective, incorporation of county characteristics allowed for examination of whether the effectiveness of state-level firearm legislation depends upon particular characteristics of counties. The researchers conducted a secondary analysis utilizing a variety of archived external government and census sources. The Study's Dataset Include two Stata Files: CJRC_firearms_research.dta (95 Variables, 129,027 Cases) state_law_data.dta (19 Variables, 2,168 Cases)

The State Alcohol-Related Firearm Statutes (SARFS) dataset was developed to analyze statutes that aim to prevent or regulate firearm access by individuals who are either acutely intoxicated or have alcohol misuse history (“alcohol-related firearm laws”) from all 50 states and to examine their impact on firearm-related injuries and mortality. This dataset contains numerical variables that describe enactment, amendment, and repeal (if applicable) of alcohol-related firearm laws during the years of 2010 to 2023.The methods used to perform the original legal research followed a pre-published protocol: Silver D, Bae J, Macinko J. Protocol for creating a dataset of US state alcohol-related firearm laws 2000–2022. PLoS one. 2024 Mar 7;19(3):e029924. In brief, the most up-to-date version of statutes were collected from Westlaw, a proprietary online legal research database, beginning with the following broad search terms applied to the entirety of the state statutory codes: [(influence intoxicat! drunk! alcohol) /50 firearm] and [(influence intoxicat! drunk! alcohol) /50 gun]. Utilizing the legislative history summary provided by Westlaw and its historical database, any bills that enacted, amended, or repealed the statutes from 2010 to 2023 as well as court decisions enjoining the laws from going into effect (temporary or permanent) were also obtained. All texts were reviewed and key provisions were coded as separate variables. Each calendar year constitutes a separate sheet in the file, containing variables representing the laws as of that time of 50 states. Any substantive modifications of existing laws were coded as new events with their effective dates specified. Additional Westlaw research was conducted to retrieve penalties and other relevant factors.

"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...

State-level firearm suicide proxy (FSS) for household gun ownership 1949-2020. Unlike most gun prevalence measures that are representative at the national or regional level, this proxy represents household gun ownership trends at the state level and is not reliant on self-reported data that are prone to social desirability bias. This extended proxy represents the longest-ranging dataset of state-level gun ownership rates to date. This dataset also includes historic data on firearm homicide and homicide counts and rates per 100,000 residents.

Firearms background checks for the USA for 2012 (Jan-Nov) and since 1999.These statistics represent the number of firearm background checks initiated through the NICS. They do not represent the number of firearms sold. NICS is used by Federal Firearms Licensees (FFLs) to instantly determine whether a prospective buyer is eligible to buy firearms or explosives. Before ringing up the sale, cashiers call in a check to the FBI or to other designated agencies to ensure that each customer does not have a criminal record or isn't otherwise ineligible to make a purchase. More than 100 million such checks have been made in the last decade, leading to more than 700,000 denials. More information on NICS - http://www.fbi.gov/about-us/cjis/nics Some really useful informations such as the rate of checks per 1000 people. All data is provided by state. Downloaded from the Guardian Datablog - http://www.guardian.co.uk/news/datablog/2012/dec/17/how-many-guns-us and then joined to USA States data http://geocommons.com/overlays/21424. Gun data originally from FBI http://www.fbi.gov/about-us/cjis/nics. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-12-17 and migrated to Edinburgh DataShare on 2017-02-21.

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

Abstract (en): These data were collected using the National Electronic Injury Surveillance System (NEISS), the primary data system of the United States Consumer Product Safety Commission (CPSC). CPSC began operating NEISS in 1972 to monitor product-related injuries treated in United States hospital emergency departments (EDs). In June 1992, the National Center for Injury Prevention and Control (NCIPC), within the Centers for Disease Control and Prevention, established an interagency agreement with CPSC to begin collecting data on nonfatal firearm-related injuries to monitor the incidence and characteristics of persons with nonfatal firearm-related injuries treated in United States hospital EDs over time. This dataset represents all nonfatal firearm-related injuries (i.e., injuries associated with powder-charged guns) and all nonfatal BB and pellet gun-related injuries reported through NEISS from 1993 through 2000. The cases consist of initial ED visits for treatment of the injuries. Cases were reported even if the patients subsequently died. Secondary visits and transfers from other hospitals were excluded. Information is available on injury diagnosis, firearm type, use of drugs or alcohol, criminal incident, and locale of the incident. Demographic information includes age, sex, and race of the injured person. United States hospitals providing emergency services. Stratified probability sample of all United States hospitals that had at least six beds and provided 24-hour emergency services. There were four hospital size strata (defined as very large, large, medium, and small, based on the number of annual ED visits) and one children's hospital stratum. From 1993 through 1996, there were 91 NEISS hospital EDs in the sample. In 1997, the sampling frame was updated so that from 1997 through 1999, the sample included 101 NEISS hospital EDs. In 2000, one NEISS hospital dropped of the system so there were 100 NEISS hospital EDs in the sample. In 1997, CPSC collected firearm-related cases using the "old" and "new" NEISS hospital samples for a 9-month period. This dataset includes data from the "new" sample. The overlapping "old" sample is not included. Comparisons of weighted estimates based on the "old" and "new" samples indicated a difference of about 1 percent in the overall national estimate using these samples. The characteristics of firearm-related cases from these two overlapping samples were also very similar. 2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.2003-09-16 The 2000 data have been added to the cumulative data. The codebook and SAS and SPSS data definition statements have been updated to reflect these changes.2002-09-19 The 1999 data have been added to the cumulative data and a variable was removed. The codebook and data definition statements have been updated to reflect these changes.2001-05-18 The 1998 data have been added to this study, and the codebook has been updated to reflect these changes. Funding insitution(s): United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Injury Prevention and Control. United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics.

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs’ departments. DCJS compiles these reports as New York’s official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Firearm counts are derived from taking the number of violent crimes which involve a firearm. Population data are provided every year by the FBI, based on US Census information. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred. DCJS posts preliminary data in the spring and final data in the fall.

Context

There's currently a lack of large and easily-accessible amounts of detailed data on gun violence.

Content

This project aims to change that; we make a record of more than 260k gun violence incidents, with detailed information about each incident, available in CSV format. We hope that this will make it easier for data scientists and statisticians to study gun violence and make informed predictions about future trends.

The CSV file contains data for all recorded gun violence incidents in the US between January 2013 and March 2018, inclusive.

Acknowledgements

Where did you get the data?

The data was downloaded from gunviolencearchive.org. From the organization's description:

Gun Violence Archive (GVA) is a not for profit corporation formed in 2013 to provide free online public access to accurate information about gun-related violence in the United States. GVA will collect and check for accuracy, comprehensive information about gun-related violence in the U.S. and then post and disseminate it online.

How did you get the data?

Because GVA limits the number of incidents that are returned from a single query, and because the website's "Export to CSV" functionality was missing crucial fields, it was necessary to obtain this dataset using web scraping techniques.

Stage 1: For each date between 1/1/2013 and 3/31/2018, a Python script queried all incidents that happened at that particular date, then scraped the data and wrote it to a CSV file. Each month got its own CSV file, with the exception of 2013, since not many incidents were recorded from then.

Stage 2: Each entry was augmented with additional data not directly viewable from the query results page, such as participant information, geolocation data, etc.

Stage 3: The entries were sorted in order of increasing date, then merged into a single CSV file.

Inspiration

I believe there are plenty of ways this dataset can be put to good use. If you have an interesting idea or feel like messing around with the data, then go for it.

I was originally inspired to compile it in the wake of the Parkland shooting and the mass media coverage that followed. Reports like this and this showed that Nikolas Cruz had exhibited plenty of warning signs on social media before the shooting; what if we could build a machine learning system that preemptively detected such signs?