***Starting on March 7th, 2024, the Los Angeles Police Department (LAPD) will adopt a new Records Management System for reporting crimes and arrests. This new system is being implemented to comply with the FBI's mandate to collect NIBRS-only data (NIBRS — FBI - https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs). During this transition, users will temporarily see only incidents reported in the retiring system. However, the LAPD is actively working on generating new NIBRS datasets to ensure a smoother and more efficient reporting system. *** **Update 1/18/2024 - LAPD is facing issues with posting the Crime data, but we are taking immediate action to resolve the problem. We understand the importance of providing reliable and up-to-date information and are committed to delivering it. As we work through the issues, we have temporarily reduced our updates from weekly to bi-weekly to ensure that we provide accurate information. Our team is actively working to identify and resolve these issues promptly. We apologize for any inconvenience this may cause and appreciate your understanding. Rest assured, we are doing everything we can to fix the problem and get back to providing weekly updates as soon as possible. ** This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.
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.
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.
These data on 19th- and early 20th-century police department and arrest behavior were collected between 1975 and 1978 for a study of police and crime in the United States. Raw and aggregated time-series data are presented in Parts 1 and 3 on 23 American cities for most years during the period 1860-1920. The data were drawn from annual reports of police departments found in the Library of Congress or in newspapers and legislative reports located elsewhere. Variables in Part 1, for which the city is the unit of analysis, include arrests for drunkenness, conditional offenses and homicides, persons dismissed or held, police personnel, and population. Part 3 aggregates the data by year and reports some of these variables on a per capita basis, using a linear interpolation from the last decennial census to estimate population. Part 2 contains data for 267 United States cities for the period 1880-1890 and was generated from the 1880 federal census volume, REPORT ON THE DEFECTIVE, DEPENDENT, AND DELINQUENT CLASSES, published in 1888, and from the 1890 federal census volume, SOCIAL STATISTICS OF CITIES. Information includes police personnel and expenditures, arrests, persons held overnight, trains entering town, and population.
This dataset reflects reported incidents of crime that have occurred in the City of Chicago over the past year, minus the most recent seven days of data. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited.
The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. Any use of the information for commercial purposes is strictly prohibited. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily.
This table contains data on the rate of violent crime (crimes per 1,000 population) for California, its regions, counties, cities and towns. Crime and population data are from the Federal Bureau of Investigations, Uniform Crime Reports. Rates above the city/town level include data from city, university and college, county, state, tribal, and federal law enforcement agencies. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Ten percent of all deaths in young California adults aged 15-44 years are related to assault and homicide. In 2010, California law enforcement agencies reported 1,809 murders, 8,331 rapes, and over 95,000 aggravated assaults. African Americans in California are 11 times more likely to die of assault and homicide than Whites. More information about the data table and a data dictionary can be found in the About/Attachments section.
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.
This indicator is based on location of residence. Mortality rate has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify homicides are X85-Y09, Y87.1, and U01-U02. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Violence is a public health crisis in the US, with gun violence being a major driver. Almost three quarters of homicides involve firearms. In the US, the age-adjusted homicide rate from firearms is more than 20 times higher than in the European Union or in Australia. Significant disparities by age, sex, and race and ethnicity exist, with young adults ages 15-34 years, males, and Black individuals most disproportionately impacted. Comprehensive prevention strategies should work to address the underlying physical, social, economic, and structural conditions known to increase risk.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
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.
This data set contains count data on domestic violence homicide and intimate partner homicide incidents from the 2015 the Federal Bureau of Investigation (FBI) Supplemental Homicide Report (SHR) and population from the SHR.
Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.
THIS DATASET WAS LAST UPDATED AT 2:11 PM EASTERN ON SEPT. 7
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.
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.
To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:
To get these counts just for your state:
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.
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.
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.
Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
This study focused on the effect of economic resources and racial/ethnic composition on the change in crime rates from 1970-2004 in United States cities in metropolitan areas that experienced a large growth in population after World War II. A total of 352 cities in the following United States metropolitan areas were selected for this study: Atlanta, Dallas, Denver, Houston, Las Vegas, Miami, Orange County, Orlando, Phoenix, Riverside, San Bernardino, San Diego, Silicon Valley (Santa Clara), and Tampa/St. Petersburg. Selection was based on the fact that these areas developed during a similar time period and followed comparable development trajectories. In particular, these 14 areas, known as the "boomburbs" for their dramatic, post-World War II population growth, all faced issues relating to the rapid growth of tract-style housing and the subsequent development of low density, urban sprawls. The study combined place-level data obtained from the United States Census with crime data from the Uniform Crime Reports for five categories of Type I crimes: aggravated assaults, robberies, murders, burglaries, and motor vehicle thefts. The dataset contains a total of 247 variables pertaining to crime, economic resources, and race/ethnic composition.
Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.
By City of Chicago [source]
This dataset is a compilation of reported crimes that have taken place in the City of Chicago over the past year, and provides an invaluable insight into the criminal activity occurring within our city. Featuring more than 65,000 records of data, it contains information on the date of each incident, its location (down to the block level), type of crime committed (determined by FBI Crime Classification Codes) and whether or not an arrest has been made in connection with each crime. As this dataset reveals detailed information on crime incidents which may lead to personal identification, addresses are masked beyond block level and specific locations are not disclosed.
For additional questions regarding this dataset, please do not hesitate to reach out to The Research & Development Division at 312.745.6071 or RandDchicagopolice.com who will be more than happy to help answer any inquiries you may have about our data findings! All visualized maps should be considered approximate however—it is prohibited for any attempts to derive specific addresses from them as accuracy cannot be guaranteed with regards to mechanical or human error when collecting this data over time. So come join us as we explore a year's worth of criminal activities throughout Chicago!
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This guide will provide an overview on how to use this dataset to analyze patterns or draw conclusions about crime incidents in and around Chicago.
Secondly, become familiar with columns names which appear at top most row of your opened file which helps you understand what kind of data is stored at each column such as - CASE# - Unique identifier for the crime incident., DATE OF OCCURRENCE - Date when crime incident occurred , BLOCK - Block where event took place , LOCATION DESCRIPTION- Description of location where incident happened . Through these columns name you can easily recognize what kind of data exists within that record/row. That’s why it’s important to get familiar with them first before diving into raw datasets because they’ll help make exploring and understanding large sets easier later on when we go further into illustrating charts & graphs using programs such as Tableau & Power BI or even spreadsheets (Excel). After understanding column names its time to explore further by digging deeper into each record/row and apply filters if required e.g below $100 value will show only those rows having value less than 100 thus it will filter entire dataset according to your requirement. Lastly analyse collected datasets either Visually through plotting graphs with help tableau software OR By using Mathematical mathematical equations based on research questions such as finding out average values after applying sum/avg functions from respective cells etc
- Creating a visualization mapping tool to help visualize the types of crimes and their locations over time within Chicago.
- An analysis tool for city officials or police departments so they can understand correlations between crime type, geography, and other factors like weather changes or economic downturns in order to develop long-term plans for crime prevention.
- Developing an AI model that would be able to predict what areas may be more vulnerable for certain types of crimes or even predict crimes ahead of time based on the data from this dataset
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: crimes-one-year-prior-to-present-1.csv | Column name | Description | |:-------------------------|:------------------------------------------------------------------------------| | CASE# | Unique identifier for each crime incident (String) | | BLOCK | Block where the crime incident occurred (String) | | LOCATION DESCRIPTION | Description of where an incident took place (String) | | ARREST | Indicates if an arrest was made in connection with a crime incident (Boolean) | | DOMESTIC | Indicates if a reported incident is domestic related (Boolean) | | BEAT ...
Crime Open Database is a database of 16 million offenses from 10 of the largest United States cities over 11 years and more than 60 offense types. Open crime data were obtained from each city, having been published in multiple incompatible formats. The data were processed to harmonize geographic co-ordinates, dates and times, offense categories and location types, as well as adding census and other geographic identifiers. The resulting database allows the wider study of spatio-temporal patterns of crime across multiple US cities, allowing greater understanding of variations in the relationships between crime and place across different settings, as well as facilitating replication of research.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.
These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study integrated neighborhood-level data on robbery and burglary gathered from local police agencies across the United States, foreclosure data from RealtyTrac (a real estate information company), and a wide variety of social, economic, and demographic control variables from multiple sources. Using census tracts to approximate neighborhoods, the study regressed 2009 neighborhood robbery and burglary rates on foreclosure rates measured for 2007-2008 (a period during which foreclosure spiked dramatically in the nation), while accounting for 2007 robbery and burglary rates and other control variables that captured differences in social, economic, and demographic context across American neighborhoods and cities for this period. The analysis was based on more than 7,200 census tracts in over 60 large cities spread across 29 states. Core research questions were addressed with a series of multivariate multilevel and single-level regression models that accounted for the skewed nature of neighborhood crime patterns and the well-documented spatial dependence of crime. The study contains one data file with 8,198 cases and 99 variables.
Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2024.
***Starting on March 7th, 2024, the Los Angeles Police Department (LAPD) will adopt a new Records Management System for reporting crimes and arrests. This new system is being implemented to comply with the FBI's mandate to collect NIBRS-only data (NIBRS — FBI - https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs). During this transition, users will temporarily see only incidents reported in the retiring system. However, the LAPD is actively working on generating new NIBRS datasets to ensure a smoother and more efficient reporting system. *** **Update 1/18/2024 - LAPD is facing issues with posting the Crime data, but we are taking immediate action to resolve the problem. We understand the importance of providing reliable and up-to-date information and are committed to delivering it. As we work through the issues, we have temporarily reduced our updates from weekly to bi-weekly to ensure that we provide accurate information. Our team is actively working to identify and resolve these issues promptly. We apologize for any inconvenience this may cause and appreciate your understanding. Rest assured, we are doing everything we can to fix the problem and get back to providing weekly updates as soon as possible. ** This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.