This map shows a comparable measure of crime in the United States. The crime index compares the average local crime level to that of the United States as a whole. An index of 100 is average. A crime index of 120 indicates that crime in that area is 20 percent above the national average.The crime data is provided by Applied Geographic Solutions, Inc. (AGS). AGS created models using the FBI Uniform Crime Report databases as the primary data source and using an initial range of about 65 socio-economic characteristics taken from the 2000 Census and AGS’ current year estimates. The crimes included in the models include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. The total crime index incorporates all crimes and provides a useful measure of the relative “overall” crime rate in an area. However, these are unweighted indexes, meaning that a murder is weighted no more heavily than a purse snatching in the computations. The geography depicts states, counties, Census tracts and Census block groups. An urban/rural "mask" layer helps you identify crime patterns in rural and urban settings. The Census tracts and block groups help identify neighborhood-level variation in the crime data.------------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

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.

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.

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.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Los Angeles County, CA was 21159.00000 Known Incidents in January of 2020, according to the United States Federal Reserve. Historically, Combined Violent and Property Crime Offenses Known to Law Enforcement in Los Angeles County, CA reached a record high of 28300.00000 in January of 2007 and a record low of 20493.00000 in January of 2014. Trading Economics provides the current actual value, an historical data chart and related indicators for Combined Violent and Property Crime Offenses Known to Law Enforcement in Los Angeles County, CA - last updated from the United States Federal Reserve on June of 2025.

As of 2020, there were 28,882 violent crimes reported in Los Angeles by the Los Angeles Police Department. Within the provided time period, the highest number of robberies was reported in 2017, at 30,507.

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.

Percent of adults (18+ years old) who reported considering their neighborhood to be safe from crime Data Source: 2011 & 2015 Los Angeles County Health Survey; Office of Health Assessment and Epidemiology, Los Angeles County Department of Public Health. FAQS 1) What is the Los Angeles County Health Survey (LACHS)? The Los Angeles County Health Survey is a population based telephone survey that provides information concerning the health of Los Angeles County residents. The data are used for assessing health-related needs of the population, for program planning and policy development, and for program evaluation. The relatively large sample size allows users to obtain health indicator data for large demographic subgroups and across geographic regions of the County, including Service Planning Areas and Health Districts. Produced by Los Angeles County Department of Public Health, Office of Health Assessment and Epidemiology (OHAE) www.publichealth.lacounty.gov/ha 2) What are the sample sizes of the 2011 and 2015 LACHS? Estimates are based on self-reported data by random samples of 8,036 (from 2011 survey) and 8,008 (from 2015 survey) Los Angeles County adults, representative of the adult population in Los Angeles County. 3) What does the 95% CI mean? The 95% confidence intervals (CI) represent the variability in the estimate due to sampling; the actual prevalence in the population, 95 out of 100 times sampled, would fall within the range provided. 4) What is the prevalence and confidence intervals (CIs) for Los Angeles County and Los Angeles City? Findings for the County of Los Angeles: (84.1%; 95% CI=81.8-86.5)Findings for the City of Los Angeles: (79.9%; 95% CI=75.9-84.0) Note:For purposes of confidentiality, Community Plan Area results with cell sizes less than 5 are not reported and are excluded from the map display. "Field Name" = Field Definition “CPA_NUM” = Unique identifier for each Community Plan Area "NAME_ALF" = the 35 Community Plan Areas, LAX Plan Area, and the Port of Los Angeles Plan Area "Percent" = percentage of adults (18+ years old) whose reported considering their neighborhood to be safe from crime "Stable_est" = (Yes) the estimate is statistically stable (relative standard error ≤ 30%) (No) the estimate is statistically unstable (relative standard error >30%) and therefore may not be appropriate to use for planning or policy purposes "LowerCL" = the lower 95% confidence limit represents the lower margin of error that occurs with statistical sampling "UpperCL" = the upper 95% confidence limit represents the upper margin of error that occurs in statistical sampling

By 1996 it became apparent that the Los Angeles county jails faced a serious overcrowding problem. Two possible solutions to the problem were to build more jail capacity or to divert a greater number of incoming inmates to community-based, intermediate sanctions. The research team for this study was asked to review a 1996 profile of inmates in the Los Angeles jail system and to determine how many of them might have been good candidates for intermediate sanctions such as electronic monitoring, work release, house arrest, and intensive supervision. The researchers selected a sample of 1,000 pre-adjudicated (or unconvicted) inmates from the total census of inmates in jail custody on January 15, 1996, to study in more detail. Of the 1,000 offenders, the researchers were able to obtain jail and recidivism data for two years for 931 inmates. For each of these offenders, information on their prior criminal history, current offense, and subsequent recidivism behavior was obtained from official records maintained by several county agencies, including pretrial services, sheriff's department, probation, and courts. Demographic variables include date of birth, race, and gender. Prior criminal history variables for each prior adult arrest include type of filing charge, case disposition, type of sentence and sentence length imposed, and total number of prior juvenile petitions sustained. Current offense variables include arrest date, crime type for current arrest, crime charge, type and date of final case disposition, and sentence type and length, if convicted. Strike information collected includes number of strikes and the offense that qualified as a strike. Jail custody variables include the jail entry and exit data for the current offense and the reason for release, if released. Lastly, two-year follow-up variables include the date, type, and disposition of each subsequent arrest between January 15, 1996, and January 15, 1998.

Part 1 crimes, as defined by the Federal Bureau of Investigation (FBI), are:

Criminal Homicide Forcible Rape Robbery Aggravated Assault Burglary Larceny Theft Grand Theft Auto Arson

Part 2 crimes, as defined by the Federal Bureau of Investigation (FBI), are:

Forgery Fraud And NSF Checks Sex Offenses Felonies Sex Offenses Misdemeanors Non-Aggravated Assaults Weapon Laws Offenses Against Family Narcotics Liquor Laws Drunk / Alcohol / Drugs Disorderly Conduct Vagrancy Gambling Drunk Driving Vehicle / Boat Vehicle / Boating Laws Vandalism Warrants Receiving Stolen Property Federal Offenses without Money Federal Offenses with Money Felonies Miscellaneous Misdemeanors Miscellaneous

Note About Date Fields:By default, the cloud database assumes all date fields are provided in UTC time zone. As a result, the system attempts to convert to the local time zone in your browser resulting in dates that appear differently than the source file. For example, a user viewing the data in PST will see times that are 8 hours behind. For an example of how dates are displayed, see the example below: Source & Download File Online Database Table Display (Example for PST User)

3/18/2023 8:07:00 AM PST 3/18/2023 8:07:00 AM UTC 3/18/2023 12:07:00 AM DATA DICTIONARY:

Field  Name
Field Description


LURN_SAK
System assigned number for the case


Incident Date
Date the crime incident occurred


Incident Reported Date
Date the crime was reported to LASD


Category
Incident crime category


Stat Code
A three digit numerical coding system to identify the primary crime category for an incident


Stat Code Desc
The definition of the statistical code number


Address
The street number, street name, state and zip where the incident occurred


Street
The street number and street name where the incident occurred


City
The city where the incident occurred


Zip
The zip code of the location where the incident occurred


Incident ID
The URN #, or Uniform Report Number, is a unique # assigned to every criminal and noncriminal incident


Reporting District
A geographical area defined by LASD which is within a city or unincorporated area where the incident occurred


Sequential (per Station)
Each incident for each station is issued a unique sequence # within a given year


Gang Related
Indicates if the crime incident was gang related


Unit ID
ORI # is a number issued by the FBI for every law enforcement agency


Unit Name
Station Name


Longitude
Longitude (as plotted on the nearest half block street segment)


Latitude
Latitude (as plotted on the nearest half block street segment)


Part Category
Part I Crime or Part II Crime indicator

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.

This dataset provides geographically filtered data from LASD: https://lasd.org/transparency/part1and2crimedata/

The information has not been altered in any way.

Incident Date = Date the crime incident occurred Incident Reported Date = Date the crime was reported to LASD Category = Incident crime category Stat = A three digit numerical coding system to identify the primary crime category for an incident Stat Desc = The definition of the statistical code number Address (last two digits of # rounded to 00) = The street number, street name, state and zip where the incident occurred Street (last two digits of # rounded to 00) = The street number and street name where the incident occurred City = The city where the incident occurred Zip = The zip code of the location where the incident occurred Incident ID = The URN #, or Uniform Report Number, is a unique # assigned to every criminal and noncriminal incident Reporting District = A geographical area defined by LASD which is within a city or unincorporated area where the incident occurred Seq = Each incident for each station is issued a unique sequence # within a given year Gang Related = Indicates if the crime incident was gang related (column added 08/02/2012) Unit ID = ORI # is a number issued by the FBI for every law enforcement agency Unit Name = Station Name Longitude (truncated to 3 decimals, equivalent to half-block rounding) (column added 01/04/2021) Latitude (truncated to 3 decimals, equivalent to half-block rounding) (column added 01/04/2021) Part Category = Part I Crime or Part II Crime indicator (replaced DELETED column 01/04/2021)

As of 2020, there were 1,983 rapes reported in Los Angeles. Within the provided time period, the highest number of rapes reported was in 2018, at 2,528.

Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Orange County, CA (DISCONTINUED) (FBITC006059) from 2004 to 2020 about Orange County, CA; crime; violent crime; property crime; Los Angeles; CA; and USA.

This data collection documents an evaluation of the Los Angeles County Sheriff's Regimented Inmate Diversion (RID) program conducted with male inmates who were participants in the program during September 1990-August 1991. The evaluation was designed to determine whether county-operated boot camp programs for male inmates were feasible and cost-effective. An evaluation design entailing both process and impact components was undertaken to fully assess the overall effects of the RID program on offenders and on the county jail system. The process component documented how the RID program actually operated in terms of its selection criteria, delivery of programs, length of participation, and program completion rates. Variables include demographic/criminal data (e.g., race, date of birth, arrest charge, bail and amount, sentence days, certificates acquired, marital status, employment status, income), historical state and county arrest data (e.g., date of crime, charge, disposition, probation time, jail time, type of crime), boot camp data (e.g., entry into and exit from boot camp, reason for exit, probation dates, living conditions, restitution order), drug history data (e.g., drug used, frequency, method), data on drug tests, and serious incidence data. The impact data were collected on measures of recidivism, program costs, institutional behavior, and RID's effect on jail crowding.

This evaluation was developed and implemented by the Los Angeles District Attorney's Office to examine the effectiveness of specialized prosecutorial activities in dealing with the local problem of rising gang violence, in particular the special gang prosecution unit Operation Hardcore. One part of the evaluation was a system performance analysis. The purposes of this system performance analysis were (1) to describe the problems of gang violence in Los Angeles and the ways that incidents of gang violence were handled by the Los Angeles criminal justice system, and (2) to document the activities of Operation Hardcore and its effect on the criminal justice system's handling of the cases prosecuted by that unit. Computer-generated listings from the Los Angeles District Attorney's Office of all individuals referred for prosecution by local police agencies were used to identify those individuals who were subsequently prosecuted by the District Attorney. Data from working files on all cases prosecuted, including copies of police, court, and criminal history records as well as information on case prosecution, were used to describe criminal justice handling. Information from several supplementary sources was also included, such as the automated Prosecutors Management Information System (PROMIS) maintained by the District Attorney's Office, and court records from the Superior Court of California in Los Angeles County, the local felony court.

The purpose of the study was to investigate the role and impact of forensic science evidence on the criminal justice process. The study utilized a prospective analysis of official record data that followed criminal cases in five jurisdictions (Los Angeles County, California; Indianapolis, Indiana; Evansville, Indiana; Fort Wayne, Indiana; and South Bend, Indiana) from the time of police incident report to final criminal disposition. The data were based on a random sample of the population of reported crime incidents between 2003 and 2006, stratified by crime type and jurisdiction. A total of 4,205 cases were sampled including 859 aggravated assaults, 1,263 burglaries, 400 homicides, 602 rapes, and 1,081 robberies. Descriptive and impact data were collected from three sources: police incident and investigation reports, crime lab reports, and prosecutor case files. The data contain a total of 175 variables including site, crime type, forensic variables, criminal offense variables, and crime dispositions variables.

Collection of these data was undertaken in order to develop offender classification criteria that could be used to identify career criminals for priority prosecution. In addition to the crime records obtained from official sources and defendants' self- reports, information about prosecutors' discretionary judgments on sampled cases was obtained from interviews of prosecutors and case review forms completed by attorneys. Respondent and nonrespondent files, taken from official court records, contain information on current and past records of offenses committed, arrests, dispositions, sentences, parole and probation histories, substance abuse records, juvenile court appearances, criminal justice practitioners' assessments, and demographic characteristics. The prosecutor interview files contain variables relating to prosecutors' opinions on the seriousness of the defendant's case, subjective criteria used to decide suitability for prosecution, and case status at intake stage. Information obtained from prosecutors' case review forms include defendants' prior records and situational variables related to the charged offenses. The self-report files contain data on the defendants' employment histories, substance abuse and criminal records, sentence and confinement histories, and basic socioeconomic characteristics.

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.

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).