In 2024, Colima in Mexico ranked as the world's most dangerous city with a homicide rate of 140 per 100,000 inhabitants. Seven of the 10 cities with the highest murder rates worldwide are all found in Mexico. The list does not include countries where war and conflict exist. Latin America dominate murder statistics Except for Mandela Bay, all the cities on the list are found in Latin America. Latin America also dominate the list of the world's most dangerous countries. Violence in Latin America is caused in great part by drug trafficking, weapons trafficking, and gang wars. Crime in South Africa Mandela Bay in South Africa is the only city outside Latin America among the 10 most dangerous cities worldwide. The country is struggling with extremely high levels of inequality, and is struggling with high levels of crime and power outages, harming the country's economy and driving more people into unemployment and poverty.

In 2022, the New Orleans-Metairie, LA metro area recorded the highest homicide rate of U.S. cities with a population over 250,000, at 27.1 homicides per 100,000 residents, followed by the Memphis, TN-MS-AR metro area. However, homicide data was not recorded in all U.S. metro areas, meaning that there may be some cities with a higher homicide rate.

St. Louis

St. Louis, which had a murder and nonnegligent manslaughter rate of 11.6 in 2022, is the second-largest city by population in Missouri. It is home to many famous treasures such as the St. Louis Cardinals baseball team, Washington University in St. Louis, the Saint Louis Zoo, and the renowned Gateway Arch. It is home to many corporations such as Monsanto, Arch Coal, and Emerson Electric. The economy of St. Louis is centered around business and healthcare, and in addition is home to ten Fortune 500 companies.

Crime in St. Louis

Despite all of this, St. Louis suffers from high levels of crime and violence. As of 2023, it was listed as the seventh most dangerous city in the world as a result of their extremely high murder rate. Not only does St. Louis have one of the highest homicide rates in the United States, it also reports one of the highest numbers of violent crimes. In spite of high crime levels, the GDP of the St. Louis metropolitan area has been increasing since 2001.

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 Mexican city of Colima was the most deadly city in the world, with a murder rate of 140.32 per 100,000 inhabitants. 7 out of the top 10 cities with over 250,000 habitants and the highest homicide rates were located in Mexico.

Colima was the city in Mexico that led the ranking of highest homicide rates in 2023. The city had a murder rate of approximately 140.32 per 100,000 inhabitants, followed by Ciudad Obregón, with a homicide rate of 117.83. That year, those two cities had the highest homicide rates not only in Mexico, but in Latin America and the Caribbean.

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2023.

In 2024, six of the eight Brazilian cities with the highest homicide rates were in the Northeast. Feira da Santana led the ranking of the most violent city in Brazil, with a murder rate of 55.63 per 100,000 inhabitants. It was followed followed by Recife, with a homicide rate of more than 41 per 100,000 inhabitants. In Latin America and the Caribbean, Feira da Santana was the 22nd most deadly city.

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 data comes from the police department and includes crime data sorted by offense. To respect the privacy of juvenile offenses and witnesses the data has been generalized to the hundred block of the event. Cases involving juvenile related data has been removed. The data is updated weekly.

Saint Kitts and Nevis saw a murder rate of 65 per 100,000 inhabitants, making it the most dangerous country for this kind of crime worldwide as of 2023. Interestingly, El Salvador, which long had the highest global homicide rates, has dropped out of the top 20 after a high number of gang members have been incarcerated. Meanwhile, Celaya in Mexico was the most dangerous city for murders. Violent conflicts worldwide Notably, these figures do not include deaths that resulted from war or a violent conflict. While there is a persistent number of conflicts worldwide, resulting casualties are not considered murders. Partially due to this reason, homicide rates in Latin America are higher than those in Afghanistan or Syria. A different definition of murder in these circumstances could change the rate significantly in some countries. Causes of death Also noteworthy is that murders are usually not random events. In the United States, the circumstances of murders are most commonly arguments, followed by narcotics incidents and robberies. Additionally, murders are not a leading cause of death. Heart diseases, strokes and cancer pose a greater threat to life than violent crime.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. 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. 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 Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

This dataset contains detailed information on homicides in eight United States cities: Philadelphia, Newark, Chicago, St. Louis, Memphis, Dallas, Oakland, and "Ashton" (a representative large western city). Detailed characteristics for each homicide victim include time and date of homicide, age, gender, race, place of birth, marital status, living arrangement, occupation, socioeconomic status (SES), employment status, method of assault, location where homicide occurred, relationship of victim to offender, circumstances surrounding death, precipitation or resistance of victim, physical evidence collected, victim's drug history, victim's prior criminal record, and number of offenders identified. Data on up to two offenders and three witnesses are also available and include the criminal history, justice system disposition, and age, sex, and race of each offender. Information on the age, sex, and race of each witness also was collected, as were data on witness type (police informant, child, eyewitness, etc.). Finally, information from the medical examiner's records including results of narcotics and blood alcohol tests of the victim are provided.

FBI Uniform Crime Reporting (UCR) Homicide (Murder and Non-Negligent Manslaughter) victims in the CMPD jurisdiction. Murder and Non-Negligent Manslaughter is defined by the FBI as, "The willful (non-negligent) and illegal (non-justified) killing of one person by another." This dataset is updated nightly and includes geographic coordinates and the NPA (Neighborhood Profile Area) for each homicide (murder) victim when available.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. 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. 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 are updated daily. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

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 that spans two centuries on homicides per capita for the city of Los Angeles. 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. 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. Data were derived from multiple sources, including Los Angeles court records, as well as annual reports of the coroner and daily newspapers. Part 1 (Annual Homicides and Related Data) variables include Los Angeles County annual counts of homicides, counts of female victims, method of killing such as drowning, suffocating, or strangling, and the homicide rate. Part 2 (Individual Homicide Data) variables include the date and place of the murder, the age, sex, race, and place of birth of the offender and victim, type of weapon used, and source of data.

Abstract (en): The research team collected data on homicide, robbery, and assault offending from 1984-2006 for youth 13 to 24 years of age in 91 of the 100 largest cities in the United States (based on the 1980 Census) from various existing data sources. Data on youth homicide perpetration were acquired from the Supplementary Homicide Reports (SHR) and data on nonlethal youth violence (robbery and assault) were obtained from the Uniform Crime Reports (UCR). Annual homicide, robbery, and assault arrest rates per 100,000 age-specific populations (i.e., 13 to 17 and 18 to 24 year olds) were calculated by year for each city in the study. Data on city characteristics were derived from several sources including the County and City Data Books, SHR, and the Vital Statistics Multiple Cause of Death File. The research team constructed a dataset representing lethal and nonlethal offending at the city level for 91 cities over the 23-year period from 1984 to 2006, resulting in 2,093 city year observations. The purpose of this study was to estimate temporal trends in youth violence rates variation across 91 of the 100 largest cities in the United States from 1984-2006, and to model city-specific explanatory predictors influencing these trends. In order to estimate trends in homicide offending for youth 13 to 24 years of age in 91 of the 100 largest cities in the United States from 1984-2006, data for youth homicide were acquired from the Supplementary Homicide Report (SHR), a component of the FBI's Uniform Crime Reporting Program (UCR). Measures of youth arrests for the nonlethal violent crimes of robbery and assault were acquired from UCR city arrest data for the same time period. Annual homicide, robbery, and assault arrest rates per 100,000 age-specific (i.e., 13 to 17 and 18 to 24 year olds) population were calculated by year for each city in the study. Annual homicide rates were calculated through a conventional procedure: annual incidents in a specific city, divided by the age-specific population of that city, multiplied by 100,000. Partial reporting during the time period resulted in dropping 9 cities from the homicide data and 10 cities from the robbery and assault data. Data on city-level characteristics including measures of structural disadvantage, drug market activities, gang presence-activity, and firearm availability were derived from the County and City Data Books, SHR, and the Vital Statistics Multiple Cause of Death File, respectively. Missing data came from two sources; failure to report in homicide and some of the Census collections, and lack of data for specific years, mainly in Census data, between major data collection points like the Decennial Census and the Mid-decade estimates from Census related sources. Missing data in the homicide measures were addressed using an Iterative Chain equation procedure to conduct Multiple Imputation. Variables from the original source used in the multiple imputation procedure included age of victim, race, ethnicity, gender, seven available measures of homicide circumstances, and city population size. Extrapolation methods were used to adjust for missing data in the robberies and assaults by age, and in the census and economic data sources. To estimate a missing year between two reported values, the missing year was estimated to be mid-way between the two observed years on either side of the missing year. Longer gaps involved further averaging and allocating according to the number of years missing; these estimates amount to maximum likelihood estimates of the missing years or in the case of the robberies and assaults, months as well. The study contains a total of 39 variables including city name, year, crime rate variables, and city characteristics variables. Crime rate variables include imputed and non-imputed homicide rate variables for juveniles aged 13 to 17, young adults aged 18 to 24, and adults aged 25 and over. Other crime variables include the number of imputed and non-imputed homicides as well as the robbery rate and assault rate for juveniles and young adults. City characteristics variables include population, poverty rates, percentage of African Americans, percentage of female-headed households, percentage of residents unemployed, percentage of residents receiving public assistance, home-ownership rates, gang presence and activity, and alcohol outlet density. None. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of dis...

THIS DATASET WAS LAST UPDATED AT 8:10 PM EASTERN ON MARCH 24

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.

In 2023, around 3,640.56 violent crimes per 100,000 residents were reported in Oakland, California. This made Oakland the most dangerous city in the United States in that year. Four categories of violent crimes were used: murder and non-negligent manslaughter; forcible rape; robbery; and aggravated assault. Only cities with a population of at least 200,000 were considered.

The average for 2017 based on 23 countries was 2.3 homicides per 100,000 people. The highest value was in the Philippines: 8.4 homicides per 100,000 people and the lowest value was in Japan: 0.2 homicides per 100,000 people. The indicator is available from 1990 to 2017. Below is a chart for all countries where data are available.

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: All businesses identified as victims in CPD data have been removed from this dataset.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.