***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.

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.

In a world of increasing crime, many organizations are interested in examining incident details to learn from and prevent future crime. Our client, based in Los Angeles County, was interested in this exact thing. They asked us to examine the data to answer several questions; among them, what was the rate of increase or decrease in crime from 2020 to 2023, and which ethnicity or group of people were targeted the most.

Our data was collected from Kaggle.com at the following link:

https://www.kaggle.com/datasets/nathaniellybrand/los-angeles-crime-dataset-2020-present

It was cleaned, examined for further errors, and the analysis performed using RStudio. The results of this analysis are in the attached PDF entitled: "crime_data_analysis_report." Please feel free to review the results as well as follow along with the dataset on your own machine.

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.

Effective March 7, 2024, the Los Angeles Police Department (LAPD) implemented a new Records Management System aligning with the FBI's National Incident-Based Reporting System (NIBRS) requirements. This switch, part of a nationwide mandate, enhances the granularity and specificity of crime data. You can learn more about NIBRS on the FBI's website here: https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs NIBRS is more comprehensive than the previous Summary Reporting System (SRS) used in the Uniform Crime Reporting (UCR) program. Unlike SRS, which grouped crimes into general categories, NIBRS collects detailed information for each incident, including multiple offenses, offenders, and victims when applicable. This detail-rich format may give the impression of increased crime levels due to its broader capture of criminal activity, but it actually provides a more accurate and nuanced view of crime in our community. This change sets a new baseline for crime reporting, reflecting incidents in the City of Los Angeles starting from March 7, 2024. With NIBRS, each criminal incident may reflect multiple offenses, resulting in more robust data than before. This may change the appearance of crime frequency, as multiple offenses per incident are reported individually.

The purpose of this data collection was to investigate the effects of crime rates, city characteristics, and police departments' financial resources on felony case attrition rates in 28 cities located in Los Angeles County, California. Demographic data for this collection were obtained from the 1983 COUNTY AND CITY DATA BOOK. Arrest data were collected directly from the 1980 and 1981 CALIFORNIA OFFENDER BASED TRANSACTION STATISTICS (OBTS) data files maintained by the California Bureau of Criminal Statistics. City demographic variables include total population, minority population, population aged 65 years or older, number of female-headed families, number of index crimes, number of families below the poverty level, city expenditures, and police expenditures. City arrest data include information on number of arrests disposed and number of males, females, blacks, and whites arrested. Also included are data on the number of cases released by police, denied by prosecutors, and acquitted, and data on the number of convicted cases given prison terms.

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.

This collection presents survey data from 12 cities in the United States regarding criminal victimization, perceptions of community safety, and satisfaction with local police. Participating cities included Chicago, IL, Kansas City, MO, Knoxville, TN, Los Angeles, CA, Madison, WI, New York, NY, San Diego, CA, Savannah, GA, Spokane, WA, Springfield, MA, Tucson, AZ, and Washington, DC. The survey used the current National Crime Victimization Survey (NCVS) questionnaire with a series of supplemental questions measuring the attitudes in each city. Respondents were asked about incidents that occurred within the past 12 months. Information on the following crimes was collected: violent crimes of rape, robbery, aggravated assault, and simple assault, personal crimes of theft, and household crimes of burglary, larceny, and motor vehicle theft. Part 1, Household-Level Data, covers the number of household respondents, their ages, type of housing, size of residence, number of telephone lines and numbers, and language spoken in the household. Part 2, Person-Level Data, includes information on respondents' sex, relationship to householder, age, marital status, education, race, time spent in the housing unit, personal crime and victimization experiences, perceptions of neighborhood crime, job and professional demographics, and experience and satisfaction with local police. Variables in Part 3, Incident-Level Data, concern the details of crimes in which the respondents were involved, and the police response to the crimes.

This study was conducted in 1979 at the Social Science Research Institute, University of Southern California, and explores the relationship between neighborhood change and crime rates between the years 1950 and 1976. The data were aggregated by unique and consistently-defined spatial areas, referred to as dummy tracts or neighborhoods, within Los Angeles County. By combining United States Census data and administrative data from several state, county, and local agencies, the researchers were able to develop measures that tapped the changing structural and compositional aspects of each neighborhood and their interaction with the patterns of juvenile delinquency. Some of the variables included are annual income, home environment, number of crimes against persons, and number of property crimes.

This study investigates rates of serious crime for selected public housing developments in Washington, DC, Phoenix, Arizona, and Los Angeles, California, for the years 1986 to 1989. Offense rates in housing developments were compared to rates in nearby areas of private housing as well as to city-wide rates. In addition, the extent of law enforcement activity in housing developments as represented by arrests was considered and compared to arrest levels in other areas. This process allowed both intra-city and inter-city comparisons to be made. Variables cover study site, origin of data, year of event, offense codes, and _location of event. Los Angeles files also include police division.

Effective March 7, 2024, the Los Angeles Police Department (LAPD) implemented a new Records Management System aligning with the FBI's National Incident-Based Reporting System (NIBRS) requirements. This switch, part of a nationwide mandate, enhances the granularity and specificity of crime data. You can learn more about NIBRS on the FBI's website here: https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs NIBRS is more comprehensive than the previous Summary Reporting System (SRS) used in the Uniform Crime Reporting (UCR) program. Unlike SRS, which grouped crimes into general categories, NIBRS collects detailed information for each incident, including multiple offenses, offenders, and victims when applicable. This detail-rich format may give the impression of increased crime levels due to its broader capture of criminal activity, but it actually provides a more accurate and nuanced view of crime in our community. This change sets a new baseline for crime reporting, reflecting incidents in the City of Los Angeles starting from March 7, 2024. With NIBRS, each criminal incident may reflect multiple offenses, resulting in more robust data than before. This may change the appearance of crime frequency, as multiple offenses per incident are reported individually.

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.

Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates).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.

The purpose of this data collection was to investigate the possible increase in gang involvement within cocaine and "rock" cocaine trafficking. Investigators also examined the relationships among gangs, cocaine trafficking, and increasing levels of violence. They attempted to determine the effects of increased gang involvement in cocaine distribution in terms of the location of an incident, the demographic profiles of suspects, and the level of firearm use. They also looked at issues such as whether the connection between gangs and cocaine trafficking yielded more drug-related violence, how the connection between gangs and cocaine trafficking affected police investigative processes such as intra-organizational communication and the use of special enforcement technologies, what kinds of working relationships were established between narcotics units and gang control units, and what the characteristics were of the rock trafficking and rock house technologies of the dealers. Part 1 (Sales Arrest Incident Data File) contains data for the cocaine sales arrest incidents. Part 2 (Single Incident Participant Data File) contains data for participants of the cocaine sales arrest incidents. Part 3 (Single Incident Participant Prior Arrest Data File) contains data for the prior arrests of the participants in the cocaine arrest incidents. Part 4 (Multiple Event Incident Data File) contains data for multiple event incidents. Part 5 (Multiple Event Arrest Incident Data File) contains data for arrest events in the multiple event incidents. Part 6 (Multiple Event Incident Participant Data File) contains data for the participants of the arrest events. Part 7 (Multiple Event Incident Prior Arrest Data File) contains data for the prior arrest history of the multiple event participants. Part 8 (Homicide Incident Data File) contains data for homicide incidents. Part 9 (Homicide Incident Suspect/Victim Data File) contains data for the suspects and victims of the homicide incidents. Major variables characterizing the various units of observation include evidence of gang involvement, presence of drugs, presence of a rock house, presence of firearms or other weapons, presence of violence, amount of cash taken as evidence, prior arrests, and law enforcement techniques.

These data were prepared in conjunction with a project using Bureau of Labor Statistics data (not provided with this collection) and the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program data to examine the relationship between unemployment and violent crime. Three separate time-series data files were created as part of this project: a national time series (Part 1), a state time series (Part 2), and a time series of data for 12 selected cities: Baltimore, Buffalo, Chicago, Columbus, Detroit, Houston, Los Angeles, Newark, New York City, Paterson (New Jersey), and Philadelphia (Part 3). Each data file was constructed to include 82 monthly time series: 26 series containing the number of Part I (crime index) offenses known to police (excluding arson) by weapon used, 26 series of the number of offenses cleared by arrest or other exceptional means by weapon used in the offense, 26 series of the number of offenses cleared by arrest or other exceptional means for persons under 18 years of age by weapon used in the offense, a population estimate series, and three date indicator series. For the national and state data, agencies from the 50 states and Washington, DC, were included in the aggregated data file if they reported at least one month of information during the year. In addition, agencies that did not report their own data (and thus had no monthly observations on crime or arrests) were included to make the aggregated population estimate as close to Census estimates as possible. For the city time series, law enforcement agencies with jurisdiction over the 12 central cities were identified and the monthly data were extracted from each UCR annual file for each of the 12 agencies. The national time-series file contains 82 time series, the state file contains 4,083 time series, and the city file contains 963 time series, each with 228 monthly observations per time series. The unit of analysis is the month of observation. Monthly crime and clearance totals are provided for homicide, negligent manslaughter, total rape, forcible rape, attempted forcible rape, total robbery, firearm robbery, knife/cutting instrument robbery, other dangerous weapon robbery, strong-arm robbery, total assault, firearm assault, knife/cutting instrument assault, other dangerous weapon assault, simple nonaggravated assault, assaults with hands/fists/feet, total burglary, burglary with forcible entry, unlawful entry-no force, attempted forcible entry, larceny-theft, motor vehicle theft, auto theft, truck and bus theft, other vehicle theft, and grand total of all actual offenses.

This dataset shows the incomes of residents. The data is part of the Census Transportation Planning Package (CTPP), and is the result of a cooperative effort between various groups including the State Departments of Transportation, U.S. Census Bureau, and the Federal Highway Administration. The data is a special tabulation of responses from households completing the decennial census long form. The data was collected in 2000 and is shown at tract level. This data can be found at http://www.transtats.bts.gov/Fields.asp?Table_ID=1338.

The objective of this study was to examine the observable offending patterns of recent and past drug offenders to assess the crime control potential associated with recent increases in the incarceration of drug offenders. The periods examined were 1986 (representing the second half of the 1980s, when dramatic shifts toward increasing incarceration of drug offenders first became evident), and 1990 (after escalating sentences were well under way). Convicted offenders were the focus, since these cases are most directly affected by changes in imprisonment policies, particularly provisions for mandatory prison terms. Offending patterns of convicted and imprisoned drug offenders were contrasted to patterns of convicted robbers and burglars, both in and out of prison. The researchers used data from the National Judicial Reporting Program (NJRP), sponsored by the U.S. Department of Justice, Bureau of Justice Statistics (BJS), for information on the court processing of individual felony convictions. The National Association of Criminal Justice Planners (NACJP), which maintains data for the approximately 50 counties included in the NJRP, was contracted to determine the counties to be sampled (Los Angeles County and Maricopa County in Arizona were chosen) and to provide individual criminal histories. Variables include number of arrests for robbery, violent crimes, property crimes, and other felonies, number of drug arrests, number of misdemeanor arrests, rate of violent, property, robbery, weapons, other felony, drug, and misdemeanor arrests, offense type (drug trafficking, drug possession, robbery, and burglary), total number of incarcerations, total number of convictions, whether sentenced to prison, jail, or probation, incarceration sentence in months, sex, race, and age at sampled conviction, and age at first arrest (starting at age 17).

The Community Health and Equity Index was developed by Raimi + Associates to compare health conditions, vulnerabilities, and cumulative burdens across the City of Los Angeles. The Index standardizes demographic, socio-economic, health conditions, land use, transportation, food environment, crime, and pollution burden variables, and then averages them together, yielding a score on a scale of 0-100. Lower values indicate better community health.Variables used in the index include: Hardship Index, Life Expectancy, Health Variables (Heart Disease Mortality, Emergency Department Visits for Heart Attacks, Respiratory Disease Mortality, Diabetes Mortality, Stroke Mortality, Childhood Obesity, Percentage of Low Birth Weight Infants, Number of Emergency Department Visits for Asthma for Under 17 and 18+ age groups), Walkability Index, Complete Communities Index (amenities and establishments serving the community), Transportation Index, Modified Retail Food Environment Index, Crime Rate (Violent Crimes, Property Crimes), and Pollution Burden (Pollution Exposure, Environmental Effects).Variables were assigned weights and averaged together. Weights were assigned based on the weights used in the 2013 Health Atlas. For more information, see page 181 of the 2013 Health Atlas, which is available as a PDF on the Los Angeles City Planning website, https://planning.lacity.gov.

The Justice Equity Need Index (JENI), by Advancement Project California, offers a means to map out the disparate burden that criminalization and a detention-first justice model place on specific communities. The index includes the following indicators:System Involvement: The system-involved population by ZIP Code results in direct needs for justice equity, as measured by adult and youth probation. Indicators: Adult Probation (per 1,000 people); Youth Probation (per 1,000 people) Inequity Drivers: Root inequities across communities that contribute to racial and economic disparities as seen in incarceration and policing. Indicators: Black, Latinx, AIAN, and NHPI Percentages of Population (average percentile); Unemployment Rate (%); Population aged 25+ without a High School Diploma (%); Population below 200% of the Federal Poverty Level (%); Violent Crime Rate (per 1,000 people) Criminalization Risk: Conditions where the criminal justice system has historically taken a detention-first, prevention-last approach. Indicators: Mental Health Hospitalizations (per 1,000 people); Substance Use-Related Hospitalizations (per 1,000 people); Homelessness Rate (per 1,000 people) Learn more at https://www.catalystcalifornia.org/campaign-tools/maps-and-data/justice-equity-need-index.Supervisorial Districts, SPAs, and CSAs determined by ZIP Code centroid.