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.

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.

Texas was the state with the highest number of registered weapons in the United States in 2024, with 1,136,732 firearms. Rhode Island, on the other hand, had the least, with 4,895 registered firearms. Gun laws in the United States Gun ownership in the U.S. is protected by the 2nd Amendment of the Constitution, which allows citizens to own firearms and form a militia if necessary. Outside of the 2nd Amendment, gun laws in the U.S. vary from state to state, and gun owners are subject to the laws of the state they are currently in, not necessarily the state they live in. For example, if concealed carry is allowed in a gun owner’s state of residence but not in the state they are traveling in, the owner is subject to the law of the state they are traveling in. Civilian-owned firearms The United States is estimated to have the highest rate of civilian-owned firearms in the world, more than double that of Yemen, which has the second-highest gun ownership rate. Unfortunately, along with high gun ownership rates comes a higher number of homicides by firearm, which was about 13,529 homicides in 2023.

The dataset is sourced and edited from
data.world

Description is given as below:

Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Cause of Death with U.S. - Mexico Border Regions 1999-2019 on CDC WONDER Online Database, released in 2020. Data are from the Multiple Cause of Death Files, 1999-2019, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. U.S. - Mexico border counties has been demarcated as the 44 counties that are located within 100 kilometers (62 miles) defined under the 1983 La Paz Agreement. Accessed at http://wonder.cdc.gov/ucd-border.html on Nov 6, 2021 12:22:30 AM

Query Parameters: Title: Gun Deaths by County MCD - ICD-10 Codes: W32 (Handgun discharge); W33 (Rifle, shotgun and larger firearm discharge); W34 (Discharge from other and unspecified firearms); X72 (Intentional self-harm by handgun discharge); X73 (Intentional self-harm by rifle, shotgun and larger firearm discharge); X74 (Intentional self-harm by other and unspecified firearm discharge); X93 (Assault by handgun discharge); X94 (Assault by rifle, shotgun and larger firearm discharge); X95 (Assault by other and unspecified firearm discharge); Y22 (Handgun discharge, undetermined intent); Y23 (Rifle, shotgun and larger firearm discharge, undetermined intent); Y24 (Other and unspecified firearm discharge, undetermined intent); Y35.0 (Legal intervention involving firearm discharge)

Group By: Year; County Show Totals: True Show Zero Values: False Show Suppressed: False Standard Population: 2000 U.S. Std. Population Calculate Rates Per: 100,000 Rate Options: Default intercensal populations for years 2001-2009 (except Infant Age Groups)

picture sourced from peterplit

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.

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.

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.

Context

Mass Shootings in the United States of America (1966-2017)

The US has witnessed 398 mass shootings in last 50 years that resulted in 1,996 deaths and 2,488 injured. The latest and the worst mass shooting of October 2, 2017 killed 58 and injured 515 so far. The number of people injured in this attack is more than the number of people injured in all mass shootings of 2015 and 2016 combined.

The average number of mass shootings per year is 7 for the last 50 years that would claim 39 lives and 48 injured per year.

Content

Geography: United States of America

Time period: 1966-2017

Unit of analysis: Mass Shooting Attack

Dataset: The dataset contains detailed information of 398 mass shootings in the United States of America that killed 1996 and injured 2488 people.

Variables: The dataset contains Serial No, Title, Location, Date, Summary, Fatalities, Injured, Total Victims, Mental Health Issue, Race, Gender, and Lat-Long information.

Acknowledgements

I’ve consulted several public datasets and web pages to compile this data.

Some of the major data sources include Wikipedia, Mother Jones, Stanford, USA Today and other web sources.

Inspiration

With a broken heart, I like to call the attention of my fellow Kagglers to use Machine Learning and Data Sciences to help me explore these ideas:

• How many people got killed and injured per year?

• Visualize mass shootings on the U.S map

• Is there any correlation between shooter and his/her race, gender

• Any correlation with calendar dates? Do we have more deadly days, weeks or months on average

• What cities and states are more prone to such attacks

• Can you find and combine any other external datasets to enrich the analysis, for example, gun ownership by state

• Any other pattern you see that can help in prediction, crowd safety or in-depth analysis of the event

• How many shooters have some kind of mental health problem? Can we compare that shooter with general population with same condition

Mass Shootings Dataset Ver 3

This is the new Version of Mass Shootings Dataset. I've added eight new variables:

Incident Area (where the incident took place), Open/Close Location (Inside a building or open space) Target (possible target audience or company), Cause (Terrorism, Hate Crime, Fun (for no obvious reason etc.) Policeman Killed (how many on duty officers got killed) Age (age of the shooter) Employed (Y/N) Employed at (Employer Name) Age, Employed and Employed at (3 variables) contain shooter details

Mass Shootings Dataset Ver 4

Quite a few missing values have been added

Mass Shootings Dataset Ver 5

Three more recent mass shootings have been added including the Texas Church shooting of November 5, 2017

I hope it will help create more visualization and extract patterns.

Keep Coding!

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Gun Plain township. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Gun Plain township. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Gun Plain township, the median household income stands at $126,667 for householders within the 25 to 44 years age group, followed by $99,718 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $41,492.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Plain township median household income by age. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Gun Plain township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Gun Plain township, the median income for all workers aged 15 years and older, regardless of work hours, was $53,731 for males and $29,536 for females.

These income figures highlight a substantial gender-based income gap in Gun Plain township. Women, regardless of work hours, earn 55 cents for each dollar earned by men. This significant gender pay gap, approximately 45%, underscores concerning gender-based income inequality in the township of Gun Plain township.

- Full-time workers, aged 15 years and older: In Gun Plain township, among full-time, year-round workers aged 15 years and older, males earned a median income of $69,698, while females earned $61,513, resulting in a 12% gender pay gap among full-time workers. This illustrates that women earn 88 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the township of Gun Plain township.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Gun Plain township.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Plain township median household income by race. You can refer the same here

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.

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

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.

https://www.youtube.com/watch?v=A8syQeFtBKc

Context

The Stanford Mass Shootings in America (MSA) is a dataset released under Creative Commons Attribution 4.0 international license by the Stanford Geospatial Center. While not an exhaustive collection of mass shootings, it is a high-quality dataset ranging from 1966 to 2016 with well-defined methodology, definitions and source URLs for user validation.

This dataset can be used to validate other datasets, such as us-mass-shootings-last-50-years, which contains more recent data, or conduct other analysis, as more information is provided.

Content

This dataset contains data by the MSA project both from it's website and from it's Github account. The difference between the two sources is only on the data format (i.e. .csv versus .geojson for the data, or .csv versus .pdf for the dictionary).

• mass_shooting_events_stanford_msa_release_06142016
  • Contains a nonexaustive list of US Mass Shootings from 1966 to 2016 in both .csv and .geojson formats.
• dictionary_stanford_msa_release_06142016
  • Contains the data dictionary in .csv and .pdf formats. Note the .pdf format provides an easier way to visualize sub-fields.

Note the data was reproduced here without any modifications other than file renaming for clarity, the content is the same as in the source.

The following sections are reproduced from the dataset creators website. For more details, please see the source.

Project background

The Stanford Mass Shootings of America (MSA) data project began in 2012, in reaction to the mass shooting in Sandy Hook, CT. In our initial attempts to map this phenomena it was determined that no comprehensive collection of these incidents existed online. The Stanford Geospatial Center set out to create, as best we could, a single point repository for as many mass shooting events as could be collected via online media. The result was the Stanford MSA.

What the Stanford MSA is

The Stanford MSA is a data aggregation effort. It is a curated set of spatial and temporal data about mass shootings in America, taken from online media sources. It is an attempt to facilitate research on gun violence in the US by making raw data more accessible.

What the Stanford MSA is not

The Stanford MSA is not a comprehensive, longitudinal research project. The data collected in the MSA are not investigated past the assessment for inclusion in the database. The MSA is not an attempt to answer specific questions about gun violence or gun laws.

The Stanford Geospatial Center does not provide analysis or commentary on the contents of this database or any derivatives produced with it.

Data collection methodology

The information collected for the Stanford MSA is limited to online resources. An initial intensive investigation was completed looking back over existing online reports to fill in the historic record going back to 1966. Contemporary records come in as new events occur and are cross referenced against a number of online reporting sources. In general a minimum of three corroborating sources are required to add the full record into the MSA (as many as 6 or 7 sources may have been consulted in many cases). All sources for each event are listed in the database.

Due to the time involved in vetting the details of any new incident, there is often a 2 to 4 week lag between a mass shooting event and its inclusion in the public release database.

It is important to note the records in the Stanford MSA span a time from well before the advent of online media reporting, through its infancy, to the modern era of web based news and information resources. Researchers using this database need to be aware of the reporting bias these changes in technology present. A spike in incidents for recent years is likely due to increased online reporting and not necessarily indicative of the rate of mass shootings alone. Researchers should look at this database as a curated collection of quality checked data regarding mass shootings, and not an exhaustive research data set itself. Independent verification and analysis will be required to use this data in examining trends in mass shootings over time.

Definition of Mass Shooting

The definition of mass shooting used for the Stanford database is 3 or more shooting victims (not necessarily fatalities), not including the shooter. The shooting must not be identifiably gang, drug, or organized crime related.

Acknowledgements

The Stanford Mass Shootings in America (MSA) is a dataset released under [Creative Commons Attribution 4.0 int...

This study of violent incidents among middle- and high-school students focused not only on the types and frequency of these incidents, but also on their dynamics -- the locations, the opening moves, the relationship between the disputants, the goals and justifications of the aggressor, the role of third parties, and other factors. For this study, violence was defined as an act carried out with the intention, or perceived intention, of physically injuring another person, and the "opening move" was defined as the action of a respondent, antagonist, or third party that was viewed as beginning the violent incident. Data were obtained from interviews with 70 boys and 40 girls who attended public schools with populations that had high rates of violence. About half of the students came from a middle school in an economically disadvantaged African-American section of a large southern city. The neighborhood the school served, which included a public housing project, had some of the country's highest rates of reported violent crime. The other half of the sample were volunteers from an alternative high school attended by students who had committed serious violations of school rules, largely involving illegal drugs, possession of handguns, or fighting. Many students in this high school, which is located in a large city in the southern part of the Midwest, came from high-crime areas, including public housing communities. The interviews were open-ended, with the students encouraged to speak at length about any violent incidents in school, at home, or in the neighborhood in which they had been involved. The 110 interviews yielded 250 incidents and are presented as text files, Parts 3 and 4. The interview transcriptions were then reduced to a quantitative database with the incident as the unit of analysis (Part 1). Incidents were diagrammed, and events in each sequence were coded and grouped to show the typical patterns and sub-patterns in the interactions. Explanations the students offered for the violent-incident behavior were grouped into two categories: (1) "justifications," in which the young people accepted responsibility for their violent actions but denied that the actions were wrong, and (2) "excuses," in which the young people admitted the act was wrong but denied responsibility. Every case in the incident database had at least one physical indicator of force or violence. The respondent-level file (Part 2) was created from the incident-level file using the AGGREGATE procedure in SPSS. Variables in Part 1 include the sex, grade, and age of the respondent, the sex and estimated age of the antagonist, the relationship between respondent and antagonist, the nature and location of the opening move, the respondent's response to the opening move, persons present during the incident, the respondent's emotions during the incident, the person who ended the fight, punishments imposed due to the incident, whether the respondent was arrested, and the duration of the incident. Additional items cover the number of times during the incident that something was thrown, the respondent was pushed, slapped, or spanked, was kicked, bit, or hit with a fist or with something else, was beaten up, cut, or bruised, was threatened with a knife or gun, or a knife or gun was used on the respondent. Variables in Part 2 include the respondent's age, gender, race, and grade at the time of the interview, the number of incidents per respondent, if the respondent was an armed robber or a victim of an armed robbery, and whether the respondent had something thrown at him/her, was pushed, slapped, or spanked, was kicked, bit, or hit with a fist or with something else, was beaten up, was threatened with a knife or gun, or had a knife or gun used on him/her.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Gun Barrel City. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Gun Barrel City. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2022

In terms of income distribution across age cohorts, in Gun Barrel City, the median household income stands at $81,849 for householders within the 45 to 64 years age group, followed by $66,847 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $64,527.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Barrel City median household income by age. You can refer the same here

The Washington Post spent a year determining how many children have been affected by school shootings, beyond just those killed or injured. To do that, reporters attempted to identify every act of gunfire at a primary or secondary school during school hours since the Columbine High massacre on April 20, 1999. Using Nexis, news articles, open-source databases, law enforcement reports, information from school websites, and calls to schools and police departments, The Post reviewed more than 1,000 alleged incidents, but counted only those that happened on campuses immediately before, during or just after classes. Shootings at after-hours events, accidental discharges that caused no injuries to anyone other than the person handling the gun, and suicides that occurred privately or posed no threat to other children were excluded. Gunfire at colleges and universities, which affects young adults rather than kids, also was not counted. After finding more than 200 incidents of gun violence that met The Post’s criteria, reporters organized them in a database for analysis. Because the federal government does not track school shootings, it’s possible that the database does not contain every incident that would qualify. To calculate how many children were exposed to gunfire in each school shooting, The Post relied on enrollment figures and demographic information from the U.S. Education Department, including the Common Core of Data and the Private School Universe Survey. The analysis used attendance figures from the year of the shooting for the vast majority of the schools. Credits: Research and Reporting: John Woodrow Cox, Steven Rich and Allyson Chiu Production and Presentation: John Muyskens and Monica Ulmanu Per the terms of the Creative Commons license, CISER notes that: 1. the license for this dataset is attached as the files license.htm and license.pdf. A brief version of the Creative Commons license is also included but users should familiarize themselves with the full license before using. 2. the licensed material is located at https://github.com/washingtonpost/data-school-shootings 3. Several of the files have been modified from the format presented at the above url including creating pdf versions of the documentation files and adding SAS, Stata, and SPSS versions through the use of StatTransfer 13. 4. These adapted versions of the original files are also released through the same Creative Commons license as the original with the same license elements.

Number of homicide victims, by method used to commit the homicide (total methods used; shooting; stabbing; beating; strangulation; fire (burns or suffocation); other methods used; methods used unknown), Canada, 1974 to 2024.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Gun Barrel City: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 71(2.74%) households where the householder is under 25 years old, 510(19.66%) households with a householder aged between 25 and 44 years, 1,035(39.90%) households with a householder aged between 45 and 64 years, and 978(37.70%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the city of Gun Barrel City, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Barrel City median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Gun Plain township: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 54(2.37%) households where the householder is under 25 years old, 538(23.59%) households with a householder aged between 25 and 44 years, 988(43.31%) households with a householder aged between 45 and 64 years, and 701(30.73%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the township of Gun Plain township, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Gun Plain township median household income by age. You can refer the same here