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.

Comprehensive crime statistics for Los Angeles County including homicides, property crime, robbery, assault, and neighborhood-by-neighborhood breakdowns with five-year trend analysis.

Comprehensive crime statistics for Los Angeles County's most dangerous neighborhoods including violent crime rates, property crime rates, gang activity, and annual victimization chances by neighborhood for 2024-2025.

This dataset contains official crime records reported in Los Angeles City from January 2020 to December 2023.

The data provides valuable information about reported crimes, including the date, area, crime details, victim information, premises, weapons used, and status.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

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Interesting Task Ideas:

1. Analyze the temporal patterns of crimes in different areas of Los Angeles City.
2. Identify the most common crimes.
3. Explore the correlation between victim age and crime types.
4. Investigate the crime rates in different areas of the city.
5. Examine the relationship between premises and specific crime codes.
6. Visualize the distribution of crimes on a map of Los Angeles City.
7. Analyze the relationship between crime status and occurrence location.
8. Use machine learning techniques to predict crime categories based on available features.

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.

As of 2020, there were ****** 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 ******.

***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.

Locations of offices providing crime prevention and support in Los Angeles CountyThis dataset is maintained through the County of Los Angeles Location Management System. The Location Management System is used by the County of Los Angeles GIS Program to maintain a single, comprehensive geographic database of locations countywide. For more information on the Location Management System, visit http://egis3.lacounty.gov/lms/.

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.

This data is transcribed from https://catalog.data.gov/dataset 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 blocks in order to maintain privacy. This data is as accurate as the data in the database.

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.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Los Angeles County, California, including incidents, statistics, demographics, and agency information.

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

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

Content

This data is collected on the basis of LAPD radio comms and Investigation done by them after the crime is reported. It contains crime data from 2020 to present(March 2024). In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified.

The Dataset includes 20 columns which includes information on areas such as - - Record Number - Date and time at which crime was reported/occurred - Victim Age,Sex, Ethnicity - Location where the crime took place - Weapon of crime - Status of the case

Acknowledgements

The data was provided by https://data.lacity.org/, y'all can find the original dataset being updated here

banner photo by Jake Blucker

Inspiration

• EDA and Visulisation of the cases
• Crime rate prediction and analysis
• Where and when is mostly the crime commited?
• What is the most common timing/date for most crimes to occur
• Most common type of crime
• In which Los Angeles Patrol Division(Area) does most crime reported?

As of 2020, there were ****** burglaries reported in Los Angeles by the Los Angeles Police Department. Within the provided time period, the greatest number of burglaries in Los Angeles were in 2010, with ****** reported.

organizations are becoming increasingly concerned with analyzing crime data to prevent future incidents and better understand the factors driving criminal behavior. One such organization, based in Los Angeles County, approached us with a request to conduct a comprehensive analysis of crime data in their area. They aimed to uncover key trends and insights that could inform strategies to enhance public safety and reduce the likelihood of future crimes.

The client's main focus was to assess how crime rates have evolved over time, particularly from 2020 to 2023, a period marked by numerous global and local challenges, including the COVID-19 pandemic and economic disruptions. They wanted to understand whether crime rates had increased, decreased, or remained stable during these years and what factors might have contributed to any observed changes. By examining the trends over this period, they hoped to identify patterns that could guide more effective crime prevention strategies in the future.

Another critical question the client posed was regarding the demographics of crime victims. Specifically, they sought to determine which ethnic groups or communities were most frequently targeted in criminal incidents. In an increasingly diverse city like Los Angeles, this information is essential for understanding whether certain populations are disproportionately affected by crime and, if so, why this might be the case. Identifying these patterns could allow for more targeted interventions to protect vulnerable communities and address underlying social or economic inequalities contributing to their higher victimization rates.

To address these questions, our analysis would involve a detailed examination of crime data from multiple sources, including law enforcement records and publicly available datasets. We would analyze the overall trends in crime rates over the specified time frame, breaking them down by type of crime, geographic location, and other relevant factors. Additionally, we would focus on victim demographics, including race, ethnicity, age, and gender, to determine if there were any noticeable disparities in victimization rates across different groups.

The results of this analysis would provide valuable insights not only for the client but also for policymakers, law enforcement agencies, and community organizations. By understanding the rate of increase or decrease in crime over recent years, we can gain a clearer picture of how crime is evolving and whether current measures are effective in curbing it. Furthermore, identifying which ethnic groups or populations are most affected by crime allows for a more equitable approach to crime prevention and public safety initiatives.

In conclusion, this analysis would serve as a crucial tool for the client and other stakeholders in Los Angeles County, helping them to make data-driven decisions that improve public safety and reduce the risk of future crimes. By focusing on both the overall trends and the specific demographics of crime victims, this comprehensive approach aims to address the root causes of crime and foster a safer, more inclusive community.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for University of California: Los Angeles (University or College) in California, including incidents, statistics, demographics, and detailed incident information.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Highway Patrol: Central Los Angeles Area Office (State Police) in California, including incidents, statistics, demographics, and detailed incident information.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for La Porte County Sheriff's Office (County) in Indiana, including incidents, statistics, demographics, and detailed incident information.