There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2017). For additional details, please see the attached data dictionary in the ‘About’ section.

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. 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.

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.

In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

List of every shooting incident that occurred in NYC during the current calendar year. This is a breakdown of every shooting incident that occurred in NYC during the current calendar year. This data is manually extracted every quarter and reviewed by the Office of Management Analysis and Planning before being posted on the NYPD website. Each record represents a shooting incident in NYC and includes information about the event, the location and time of occurrence. In addition, information related to suspect and victim demographics is also included. This data can be used by the public to explore the nature of police enforcement activity. Please refer to the attached data footnotes for additional information about this dataset.

Context

The NYPD Arrests Dataset (2023) consists of arrest records from the New York City Police Department for 2023. The data was sourced from NYC Public Data.

Content

Each record in the dataset includes the following fields:

• ARREST_KEY: Randomly generated persistent ID for each arrest.
• ARREST_DATE: Exact date of arrest for the reported event.
• PD_CD: Three-digit internal classification code (more granular than Key Code).
• PD_DESC: Description of the internal classification corresponding with the PD code.
• KY_CD: Three-digit internal classification code (more general category than PD code).
• OFNS_DESC: Description of internal classification corresponding with KY code (more general category than PD description).
• LAW_CODE: Law code charges corresponding to the NYS Penal Law, VTL, and other various local laws.
• LAW_CAT_CD: Level of offense: felony, misdemeanor, violation.
• ARREST_BORO: Borough of arrest. B(Bronx), S(Staten Island), K(Brooklyn), M(Manhattan), Q(Queens).
• ARREST_PRECINCT: Precinct where the arrest occurred.
• JURISDICTION_CODE: Jurisdiction responsible for arrest. Jurisdiction codes 0(Patrol), 1(Transit), and 2(Housing) represent NYPD, while codes 3 and above represent non-NYPD jurisdictions.
• AGE_GROUP: Perpetrator’s age within a category.
• PERP_SEX: Perpetrator’s sex description.
• PERP_RACE: Perpetrator’s race description.
• X_COORD_CD: Midblock X-coordinate for New York State Plane Coordinate System, Long Island Zone, NAD 83, units feet (FIPS 3104).
• Y_COORD_CD: Midblock Y-coordinate for New York State Plane Coordinate System, Long Island Zone, NAD 83, units feet (FIPS 3104).
• Latitude: Latitude coordinate for Global Coordinate System, WGS 1984, decimal degrees (EPSG 4326).
• Longitude: Longitude coordinate for Global Coordinate System, WGS 1984, decimal degrees (EPSG 4326).

Inspiration

The dataset can be used for a variety of research and analysis purposes, such as: - Crime Pattern Analysis: Investigate trends and patterns in criminal activity across different boroughs and precincts of New York City. - Law Enforcement Strategies: Examine the effectiveness of law enforcement strategies and policies based on arrest data. - Demographic Studies: Analyze the relationship between demographic factors (such as age, sex, and race of perpetrators) and arrest rates. - Geospatial Analysis: Utilize the geographic coordinates to map crime incidents and identify hotspots within the city.
- Crime Hotspot Prediction: Develop a machine learning model to predict crime hotspots.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) from 2006 to the end of last year (2015). For additional details, please see the attached data dictionary in the ‘About’ section.

This study was designed to develop crime forecasting as an application area for police in support of tactical deployment of resources. Data on crime offense reports and computer aided dispatch (CAD) drug calls and shots fired calls were collected from the Pittsburgh, Pennsylvania Bureau of Police for the years 1990 through 2001. Data on crime offense reports were collected from the Rochester, New York Police Department from January 1991 through December 2001. The Rochester CAD drug calls and shots fired calls were collected from January 1993 through May 2001. A total of 1,643,828 records (769,293 crime offense and 874,535 CAD) were collected from Pittsburgh, while 538,893 records (530,050 crime offense and 8,843 CAD) were collected from Rochester. ArcView 3.3 and GDT Dynamap 2000 Street centerline maps were used to address match the data, with some of the Pittsburgh data being cleaned to fix obvious errors and increase address match percentages. A SAS program was used to eliminate duplicate CAD calls based on time and location of the calls. For the 1990 through 1999 Pittsburgh crime offense data, the address match rate was 91 percent. The match rate for the 2000 through 2001 Pittsburgh crime offense data was 72 percent. The Pittsburgh CAD data address match rate for 1990 through 1999 was 85 percent, while for 2000 through 2001 the match rate was 100 percent because the new CAD system supplied incident coordinates. The address match rates for the Rochester crime offenses data was 96 percent, and 95 percent for the CAD data. Spatial overlay in ArcView was used to add geographic area identifiers for each data point: precinct, car beat, car beat plus, and 1990 Census tract. The crimes included for both Pittsburgh and Rochester were aggravated assault, arson, burglary, criminal mischief, misconduct, family violence, gambling, larceny, liquor law violations, motor vehicle theft, murder/manslaughter, prostitution, public drunkenness, rape, robbery, simple assaults, trespassing, vandalism, weapons, CAD drugs, and CAD shots fired.

THIS DATASET WAS LAST UPDATED AT 8:11 PM EASTERN ON SEPT. 30

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.

This dataset shows actual locations of newsstands throughout New York City, with actual contact information, however I've added a few columns of fake data representing sales of magazines at that newsstand. the numbers are randomly generated, and fake.

This dataset provides highly detailed (Block Level) views of various demographics for Manhattan, New York city. this dataset includes information on age, race, sex, income, housing, and various other attributes. This data comes from the 2000 Us Census and was joined to the Census Tiger line files to create the output. enjoy!

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) from 2006 to the end of last year (2015). For additional details, please see the attached data dictionary in the ‘About’ section.

This file shows bars and clubs in the New York City MSA. locations were pulled from multiple data sources. This isn't a full listing of bars in the NYC area, but all bars do have a user rating with them. This dataset has been migrated from our Geocommons platform, and lacks a description from the original posting user. This is not a Fortiusone provided dataset. Please keep this in mind, and make of the dataset what you will. Thank you for visiting Finder!

Under New York State’s Hate Crime Law (Penal Law Article 485), a person commits a hate crime when one of a specified set of offenses is committed targeting a victim because of a perception or belief about their race, color, national origin, ancestry, gender, religion, religious practice, age, disability, or sexual orientation, or when such an act is committed as a result of that type of perception or belief. These types of crimes can target an individual, a group of individuals, or public or private property. DCJS submits hate crime incident data to the FBI’s Uniform Crime Reporting (UCR) Program. Information collected includes number of victims, number of offenders, type of bias motivation, and type of victim.

This data set contains New York City Police Department provided domestic violence incident data for calendar years 2020, 2021 and 2022. In addition, ENDGBV obtained through Open Data the number of shooting incidents for calendar years 2020, 2021 and 2022. The data includes counts of the number of domestic violence incidents, shooting incidents and the number of expected domestic violence incidents and shooting incidents by: race (American Indian/Alaska Native, Asian/Pacific Islander, Black, and White) and sex (male, female) for New York City, each borough (Bronx, Brooklyn, Manhattan, Queens and Staten Island). It also provides the count and rate of domestic violence and shooting incidents by police precinct. The expected number of domestic violence incidents and shooting incidents were calculated by taking the total number of actual domestic violence and shooting incidents for a given geography (New York City, the Bronx, Brooklyn, Manhattan, Queens and Staten Island) and proportioning them by demographic breakdown of the geographic area.

The objectives of this study were (1) to compare long-term patterns of violent crime for mentally disordered patients and for prison inmates, and (2) to evaluate the predictive validity of a diagnosis of schizophrenia for subsequent arrests for violent crimes. For purposes of this data collection, violent crimes were defined as including murder, manslaughter, rape, assault, kidnapping, and sodomy. The study analyzed individual state mental hospital patients and inmates of state prisons in New York State over a 20-year span. In the process of obtaining information regarding the individuals, three different areas were focused on: hospital, incarceration, and arrest histories. Variables for hospital histories include inpatient hospitalizations, admission and discharge dates, legal status for all state hospitals through 1988, primary diagnosis for target and most recent admissions, and placements in New York State Department of Correctional Services mental hospitals. Incarceration history variables include time spent in adult state prisons, incarcerations through 1988, and dates of release (including re-entry to community on parole, outright release, or escape). Arrest histories include information on the subject's first adult arrest through 1988 (only the most serious charge for each incident is recorded) and out-of-state arrests, when available. Demographic variables include age, race, and date of birth.

In 2023, the state with the highest crime rate in the United States per 100,000 inhabitants was New Mexico. That year, the crime rate was ******** crimes per 100,000 people. In comparison, New Hampshire had the lowest crime rate at ****** crimes per 100,000 people. Crime rate The crime rate in the United States has generally decreased over time. There are several factors attributed to the decrease in the crime rate across the United States. An increase in the number of police officers and an increase in income are some of the reasons for a decrease in the crime rate. Unfortunately, people of color have been disproportionately affected by crime rates, as they are more likely to be arrested for a crime versus a white person. Crime rates regionally The District of Columbia had the highest rate of reported violent crimes in the United States in 2023 per 100,000 inhabitants. The most common crime clearance type in metropolitan counties in the United States in 2020 was murder and non-negligent manslaughter. The second most dangerous city in the country in 2020 was Detroit. Detroit has faced severe levels of economic and demographic declines in the past years. Not only has the population decreased, the city has filed for bankruptcy. Despite the median household income increasing, the city still struggles financially.

Content

Daily inmates in custody with attributes (custody level, mental health designation, race, gender, age, leagal status, sealed status, security risk group membership, top charge, and infraction flag). This data set excludes Sealed Cases. Resulting summaries may differ slightly from other published statistics.

Context

This is a dataset hosted by the City of New York. The city has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York City using Kaggle and all of the data sources available through the City of New York organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Fredrik Öhlander on Unsplash
Unsplash Images are distributed under a unique Unsplash License.