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.

According to a survey conducted in the United States in 2023, Americans aged 55 years old and above were more likely to personally own a gun than their counterparts in other age groups. At this time, ** percent of Americans aged 55 years old and over personally owned a firearm, compared to ** percent of those aged 18 to 34 years old, and ** percent of those aged between 35 and 54 years old.

In the USA, the relationship between the legal availability of guns and the firearm-related homicide rate has been debated. It has been argued that unrestricted gun availability promotes the occurrence of firearm-induced homicides. It has also been pointed out that gun possession can protect potential victims when attacked. This paper provides a first mathematical analysis of this tradeoff, with the goal to steer the debate towards arguing about assumptions, statistics, and scientific methods. The model is based on a set of clearly defined assumptions, which are supported by available statistical data, and is formulated axiomatically such that results do not depend on arbitrary mathematical expressions. According to this framework, two alternative scenarios can minimize the gun-related homicide rate: a ban of private firearms possession, or a policy allowing the general population to carry guns. Importantly, the model identifies the crucial parameters that determine which policy minimizes the death rate, and thus serves as a guide for the design of future epidemiological studies. The parameters that need to be measured include the fraction of offenders that illegally possess a gun, the degree of protection provided by gun ownership, and the fraction of the population who take up their right to own a gun and carry it when attacked. Limited data available in the literature were used to demonstrate how the model can be parameterized, and this preliminary analysis suggests that a ban of private firearm possession, or possibly a partial reduction in gun availability, might lower the rate of firearm-induced homicides. This, however, should not be seen as a policy recommendation, due to the limited data available to inform and parameterize the model. However, the model clearly defines what needs to be measured, and provides a basis for a scientific discussion about assumptions and data.

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.

In the United States in 2023, ** percent of Republicans reported that they owned at least one gun, and ** percent said that they lived in a household with a gun. In comparison, only ** percent of Democrats owned at least one gun, and ** percent lived in a gun household. Who are gun owners? In 2022, significantly more Democrats were in favor of limiting gun ownership in comparison to Republicans. On the other hand, more Republicans were in favor of protecting the right to own guns in comparison to Democrats. When examined by education level, respondents who said they only had some college, but no degree were the most likely to have said that there is at least one gun in their household. However, nearly a ******* of Americans over 18 years old said that they rarely carry a gun on their person. Republicans vs Democrats Debate The gun control debate in the United States has been a highly contested one. In light of frequent mass shootings, gun control laws have become the center of policy discussions. Democratic politicians tend to put significant emphasis on their gun control policies and are overall more in favor of stricter gun control laws and want more background checks for those who want to purchase a gun. However, Republicans tend to work in favor of gun rights.

Number and percentage of homicide victims, by type of firearm used to commit the homicide (total firearms; handgun; rifle or shotgun; fully automatic firearm; sawed-off rifle or shotgun; firearm-like weapons; other firearms, type unknown), Canada, 1974 to 2018.

The National Survey of Fishing, Hunting, and Wildlife-Associated Recreation (FHWAR) is a series conducted by the Census Bureau for the United States Department of the Interior Fish and Wildlife Service. This collection contains information regarding fishing, hunting, and other wildlife-associated activities for 1996. The survey is conducted every 5 years and includes 3 waves. Wave 1 is household-based and consists of a screener with the possibility of detailed interviews asking about a person's hunting, fishing or wildlife-watching activities and the likelihood that they will hunt, fish or watch wildlife. Wave 2 and Wave 3 are person-based, detailed interviews in which respondents were selected for the sample based on data collected from the screener in the first wave. The Sportsman and Wildlife-Watching surveys for wave 2 and 3 gathered specific information about respondents' recreational participation, including species hunted, fished, and watched; the state in which these activities occurred; number of trips taken; days of participation; and expenditures for food, lodging, transportation, and equipment. The questions asked throughout the 3 waves have been organized by topic into 3 datasets. The three datasets, (1) Screening, (2) Sportsman (Fishing and Hunting), and (3) Wildlife Watching, may contain responses from people surveyed during multiple waves. Demographic variables include sex, age, race, marital status and parental relations, education level, household income, state of residence, and type of residential area (e.g., urban or rural).

The dataset that I have created through web scraping using BeautifulSoup library in Python provides a comprehensive overview of the legality of firearms across various countries. It contains detailed information on the laws and regulations governing firearms possession, use, and ownership. The dataset also includes data on the number of deaths resulting from firearm incidents, including suicides, accidents, and police shootings. In addition, the dataset provides insights into the number of firearms owned by citizens, whether they are registered or unregistered. The information is compiled from reliable sources such as Wikipedia, Wisevoter, GunPolicy, and WorldPopulationReview, ensuring that the dataset is both comprehensive and accurate. This dataset is an invaluable resource for researchers, policymakers, and others who are interested in studying the prevalence and impact of firearms on society. With its comprehensive coverage of firearm laws and incidents across various countries, this dataset offers valuable insights into the complex issue of gun control and can be used to inform policy decisions aimed at reducing the negative impact of firearms on individuals and communities.

The dataset I have created can be used for various technical applications such as machine learning and data analytics. For example, researchers and developers can use this dataset to train machine learning algorithms to identify patterns and correlations between firearm laws and incidents. This can help in developing predictive models to forecast firearm-related incidents and aid in policymaking. Data analytics techniques can also be applied to the dataset to identify trends and patterns in the data, helping researchers to gain a better understanding of the complex issues surrounding firearms. Overall, the dataset I have created offers a wealth of information on firearms laws and incidents, and its potential applications extend beyond research to include policy and decision-making in various fields.

*******Links used:******* - Wikipedia - WiseVoter - GunPolicy - WorldPopulationReview

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 study examined spatial and temporal features of crime guns in Pittsburgh, Pennsylvania, in order to ascertain how gun availability affected criminal behavior among youth, whether the effects differed between young adults and juveniles, and whether that relationship changed over time. Rather than investigating the general prevalence of guns, this study focused only on those firearms used in the commission of crimes. Crime guns were defined specifically as those used in murders, assaults, robberies, weapons offenses, and drug offenses. The emphasis of the project was on the attributes of crime guns and those who possess them, the geographic sources of those guns, the distribution of crime guns over neighborhoods in a city, and the relationship between the prevalence of crime guns and the incidence of homicide. Data for Part 1, Traced Guns Data, came from the City of Pittsburgh Bureau of Police. Gun trace data provided a detailed view of crime guns recovered by police during a two-year period, from 1995 to 1997. These data identified the original source of each crime gun (first sale to a non-FFL, i.e., a person not holding a Federal Firearms License) as well as attributes of the gun and the person possessing the gun at the time of the precipitating crime, and the ZIP-code location where the gun was recovered. For Part 2, Crime Laboratory Data, data were gathered from the local county crime laboratory on guns submitted by Pittsburgh police for forensic testing. These data were from 1993 to 1998 and provided a longer time series for examining changes in crime guns over time than the data in Part 1. In Parts 3 and 4, Stolen Guns by ZIP-Code Data and Stolen Guns by Census Tract Data, data on stolen guns came from the local police. These data included the attributes of the guns and residential neighborhoods of owners. Part 3 contains data from 1987 to 1996 organized by ZIP code, whereas Part 4 contains data from 1993 to 1996 organized by census tract. Part 5, Shots Fired Data, contains the final indicator of crime gun prevalence for this study, which was 911 calls of incidents involving shots fired. These data provided vital information on both the geographic location and timing of these incidents. Shots-fired incidents not only captured varying levels of access to crime guns, but also variations in the willingness to actually use crime guns in a criminal manner. Part 6, Homicide Data, contains homicide data for the city of Pittsburgh from 1990 to 1995. These data were used to examine the relationship between varying levels of crime gun prevalence and levels of homicide, especially youth homicide, in the same city. Part 7, Pilot Mapping Application, is a pilot application illustrating the potential uses of mapping tools in police investigations of crime guns traced back to original point of sale. NTC. It consists of two ArcView 3.1 project files and 90 supporting data and mapping files. Variables in Part 1 include date of manufacture and sale of the crime gun, weapon type, gun model, caliber, firing mechanism, dealer location (ZIP code and state), recovery date and location (ZIP code and state), age and state of residence of purchaser and possessor, and possessor role. Part 2 also contains gun type and model, as well as gun make, precipitating offense, police zone submitting the gun, and year the gun was submitted to the crime lab. Variables in Parts 3 and 4 include month and year the gun was stolen, gun type, make, and caliber, and owner residence. Residence locations are limited to owner ZIP code in Part 3, and 1990 Census tract number and neighborhood name in Part 4. Part 5 contains the date, time, census tract and police zone of 911 calls relating to shots fired. Part 6 contains the date and census tract of the homicide incident, drug involvement, gang involvement, weapon, and victim and offender ages. Data in Part 7 include state, county, and ZIP code of traced guns, population figures, and counts of crime guns recovered at various geographic locations (states, counties, and ZIP codes) where the traced guns first originated in sales by an FFL to a non-FFL individual. Data for individual guns are not provided in Part 7.

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.

BackgroundGun violence has shortened the average life expectancy of Americans, and better knowledge about the root causes of gun violence is crucial to its prevention. While some empirical evidence exists regarding the impacts of social and economic factors on violence and firearm homicide rates, to the author’s knowledge, there has yet to be a comprehensive and comparative lagged, multilevel investigation of major social determinants of health in relation to firearm homicides and mass shootings.Methods and findingsThis study used negative binomial regression models and geolocated gun homicide incident data from January 1, 2015, to December 31, 2015, to explore and compare the independent associations of key state-, county-, and neighborhood-level social determinants of health—social mobility, social capital, income inequality, racial and economic segregation, and social spending—with neighborhood firearm-related homicides and mass shootings in the United States, accounting for relevant state firearm laws and a variety of state, county, and neighborhood (census tract [CT]) characteristics. Latitude and longitude coordinates on firearm-related deaths were previously collected by the Gun Violence Archive, and then linked by the British newspaper The Guardian to CTs according to 2010 Census geographies. The study population consisted of all 74,134 CTs as defined for the 2010 Census in the 48 states of the contiguous US. The final sample spanned 70,579 CTs, containing an estimated 314,247,908 individuals, or 98% of the total US population in 2015. The analyses were based on 13,060 firearm-related deaths in 2015, with 11,244 non-mass shootings taking place in 8,673 CTs and 141 mass shootings occurring in 138 CTs. For area-level social determinants, lag periods of 3 to 17 years were examined based on existing theory, empirical evidence, and data availability. County-level institutional social capital (levels of trust in institutions), social mobility, income inequality, and public welfare spending exhibited robust relationships with CT-level gun homicide rates and the total numbers of combined non-mass and mass shooting homicide incidents and non-mass shooting homicide incidents alone. A 1–standard deviation (SD) increase in institutional social capital was linked to a 19% reduction in the homicide rate (incidence rate ratio [IRR] = 0.81, 95% CI 0.73–0.91, p

Shooting ranges have experienced a surge in popularity across the United States, becoming a cornerstone of the recreational and competitive shooting industry. Recent years have seen attendance climb steadily, underpinned by a deep-rooted US gun culture, rising gun ownership rates and a broader acceptance of shooting as a mainstream hobby. The industry’s commentum is also driven by growing participation in disciplines ranging from handgun and rifle shooting to dynamic 3-gun competitions. Meanwhile, ranges have proven resilient, adapting to shifts in regulatory environments and keeping pace with consumer demand even as state and federal lawmakers debate tighter gun controls. Over the last five years, revenue grew at a CAGR of 11.9% to $5.8 billion, including a climb of 0.6% in 2025. Over the past few years, shooting ranges have outperformed many other leisure sectors, fueled by the resurgence in recreational interest and cyclical spikes driven by changes in gun regulations. Major legislative moves, whether successful or not, have often prompted increased firearm sales and range attendance, as enthusiasts hurried to purchase and train before new rules took effect. This period also saw a sharp uptick in first-time shooters and a notable broadening of the customer base, including women and younger demographics. Robust consumer spending and elevated gun ownership have sustained this expansion, while the climb in hunting and renewed interest in shooting as a skill-building activity added further momentum. Range operators responded by diversifying offerings, investing in new technology and increasing training opportunities to capture and retain this growing clientele. Looking ahead, shooting ranges will climb slowly because of persistent regulatory and demographic challenges. Although the current administration may reconsider or scale back some Biden-era controls, potentially easing compliance in certain states, overall expansion will likely remain cautious. Continued military and law enforcement training funding will support baseline demand, but operators must manage rising supply costs, changing population dynamics and evolving public attitudes. As businesses aim to attract younger participants and more women, they invest in technology upgrades, virtual training programs and enhanced safety protocols. Over the next few years, the industry will evolve gradually, with slow growth driven by innovation and a focus on broadening its appeal. Through the end of 2030, revenue is expected to climb at a CAGR of 0.9% to $6.1 billion.

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

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