To estimate national trends of crime, the FBI collects crime reports from law enforcement agencies across the country. In 2022, Delaware, the District of Columbia, and Oklahoma had perfect participation rates, with 100 percent of law enforcement agencies reporting crime data to the FBI in those states. In contrast, the state of Florida had the lowest share of law enforcement agencies who reported crime data to the FBI in the United States, at *** percent. An unreliable source? Along with being the principal investigative agency of the U.S. federal government, the FBI is also in charge of tracking crimes committed in the United States. In recent years, however, the FBI made significant changes to their crime reporting system, requiring a more detailed input on how agencies report their data. Consequently, less crime data has been reported and the FBI has come under criticism as an unreliable source on crime in the United States. In 2022, the FBI was found to rank low on trustworthiness for Americans when compared to other government agencies, further demonstrating the need for transparent and accurate data. Importance of crime rates As crime and policing data can help to analyze emerging issues and policy responses, the inaccuracy of the FBI’s crime reporting system may lead to misinformation which could be used to impact elections and the beliefs of the American public. In addition, the lack of crime data from Republican states such as Florida may prove problematic as 78 percent of Republicans said that crime was a very important issue for them in midterm elections.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 44 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

***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.

In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

The UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2022 dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.

Analysis of ‘Hate Crime Statistics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/2014-hate-crime-statisticse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

The Uniform Crime Reporting Program collects data about both single-bias and multiple-bias hate crimes. For each offense type reported, law enforcement must indicate at least one bias motivation. A single-bias incident is defined as an incident in which one or more offense types are motivated by the same bias. As of 2013, a multiple-bias incident is defined as an incident in which one or more offense types are motivated by two or more biases. Overview
In 2014, 15,494 law enforcement agencies participated in the Hate Crime Statistics Program. Of these agencies, 1,666 reported 5,479 hate crime incidents involving 6,418 offenses.
There were 5,462 single-bias incidents that involved 6,385 offenses, 6,681 victims, and 5,176 known offenders.
The 17 multiple-bias incidents reported in 2014 involved 33 offenses, 46 victims, and 16 offenders. (See Tables 1 and 12.) Source: FBI Hate Crime Statistics and more about the Hate Crime Statistics

Source: https://ucr.fbi.gov/about-us/cjis/ucr/hate-crime/2014/resource-pages/download-files

This dataset was created by Uniform Crime Reports and contains around 0 samples along with Unnamed: 13, Unnamed: 3, technical information and other features such as: - Unnamed: 12 - Unnamed: 5 - and more.

How to use this dataset

• Analyze Unnamed: 14 in relation to Unnamed: 9
• Study the influence of Unnamed: 15 on Unnamed: 4
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Uniform Crime Reports

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--- Original source retains full ownership of the source dataset ---

The UNIFORM CRIME REPORTING PROGRAM DATA: SUPPLEMENTARY HOMICIDE REPORTS, 2022 (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

In 2023, an estimated 1,21,467 violent crimes occurred in the United States. This is a decrease from the year before, when 1,256,671 violent crimes were reported. Violent crime in the United States The Federal Bureau of Investigation reported that violent crime fell nationwide in the period from 1990 to 2023. Violent crime was at a height of 1.93 million crimes in 1992, but has since reached a low of 1.15 million violent crimes in 2014. When conducting crime reporting, the FBI’s Uniform Crime Reporting Program considered murder, nonnegligent manslaughter, forcible rape, robbery and aggravated assault to be violent crimes, because they are offenses which involve force or threat of violence. In 2023, there were 19,252 reported murder and nonnegligent manslaughter cases in the United States. California ranked first on a list of U.S. states by number of murders, followed by Texas, and Florida.The greatest number of murders were committed by murderers of unknown relationship to their victim. “Girlfriend” was the fourth most common relationship of victim to offender in 2023, with a reported 568 partners murdering their girlfriends that year, while the sixth most common was “wife.” In addition, seven people were murdered by their employees and 12 people were murdered by their employers. The most used murder weapon in 2023 was the handgun, which was used in 7,1 murders that year. According to the FBI, firearms (of all types) were used in more than half of the nation’s murders. The total number of firearms manufactured in the U.S. annually has reached over 13 million units.

Note: Due to a system migration, this data will cease to update on March 14th, 2023. The current projection is to restart the updates within 30 days of the system migration, on or around April 13th, 2023Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities. The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics. Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred). Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained. Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.com Data Dictionary: INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence rooms DATE_REPORTED - the date the incident was reported to LMPD DATE_OCCURED - the date the incident actually occurred BADGE_ID - UOR_DESC - Uniform Offense Reporting code for the criminal act committed CRIME_TYPE - the crime type category NIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/view UCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime. LMPD_DIVISION - the LMPD division in which the incident actually occurred LMPD_BEAT - the LMPD beat in which the incident actually occurred PREMISE_TYPE - the type of _location in which the incident occurred (e.g. Restaurant) BLOCK_ADDRESS - the _location the incident occurred CITY - the city associated to the incident block _location ZIP_CODE - the zip code associated to the incident block _location ID - Unique identifier for internal database Contact: Crime Information Center CrimeInfoCenterDL@louisvilleky.gov

It is important for the community to understand what is – and is not – a hate crime. First and foremost, the incident must be a crime. Although that may seem obvious, most speech is not a hate crime, regardless of how offensive it may be. In addition, a hate crime is not a crime, but a possible motive for a crime.It can be difficult to establish a motive for a crime. Therefore, the classification as a hate crime is subject to change as an investigation proceeds – even as prosecutors continue an investigation. If a person is found guilty of a hate crime, the court may fine the offender up to 1½ times the maximum fine and imprison him or her for up to 1½ times the maximum term authorized for the underlying crime.While the District strives to reduce crime for all residents of and visitors to the city, hate crimes can make a particular community feel vulnerable and more fearful. This is unacceptable, and is the reason everyone must work together not just to address allegations of hate crimes, but also to proactively educate the public about hate crimes.The figures in this data align with DC Official Code 22-3700. Because the DC statute differs from the FBI Uniform Crime Reporting (UCR) and National Incident-Based Reporting System (NIBRS) definitions, these figures may be higher than those reported to the FBI.Each month, an MPD team reviews crimes that have been identified as potentially motivated by hate/bias to determine whether there is sufficient information to support that designation. The data in this document is current through the end of the most recent month.The hate crimes dataset is not an official MPD database of record and may not match details in records pulled from the official Records Management System (RMS).Unknown or blank values in the Targeted Group field may be present prior to 2016 data. As of January 2022, an offense with multiple bias categories would be reflected as such.Data is updated on the 15th of every month.

In 2023, ********* property and violent crimes were reported in California - the most out of any state. Texas followed behind, with ******* reported crimes. However, as the FBI estimates national trends of crime by asking law enforcement agencies across the country to self-report their crime data, the reported number of crimes committed in each state is dependent upon whether they provided the information to the Bureau's crime reporting system. For example, the state of Florida reported only *** percent of their crime data in 2022, raising the question of whether Florida has again failed to report the majority of their crimes in 2023 and if they should be higher up on this list. As many states have neglected to report all of their crime data to the FBI in the last few years, the total numbers may not accurately represent the number of crimes committed in each state.

The National Incident-Based Reporting System (NIBRS) is a part of the Uniform Crime Reporting Program (UCR), administered by the Federal Bureau of Investigation (FBI). NIBRS is an annual data collection that compiles information on criminal incidents and arrests reported by participating law enforcement agencies. NIBRS data as formatted by the FBI are stored as a series of single files organized by various segment levels (record types). There are six main segment levels: administrative, offense, property, victim, offender, and arrestee. Each segment level has a different length and layout. Significant computing resources are necessary to work with the data in its single-file format. In addition, the user must be knowledgeable about working with data in complex file types. The extract files version of the NIBRS files was created to simplify working with NIBRS data. Data management issues with NIBRS are significant, especially when two or more segment levels are being merged. For these reasons and the desire to facilitate the use of NIBRS data, ICPSR created the extract files. The data are not a nationally representative sample of crime in the United States.

Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov

The UNIFORM CRIME REPORTING PROGRAM DATA: PROPERTY STOLEN AND RECOVERED, UNITED STATES, 2022 file (also known as the Supplement to Return A) is collected at the agency level and includes detailed monthly data on the nature of crime and the value and type of property stolen and recovered incident to each crime. The Return A Supplement requires that a value be established for property stolen and recovered in each Crime Index category except aggravated assault. It is designed to record the value of property stolen and recovered in the following eleven classifications: Currency/notes, Jewelry and Precious Metals, Clothing and Furs, Locally Stolen Motor Vehicles, Office Equipment, Televisions/Radios, Firearms, Household Goods, Consumable Goods, Livestock, and Miscellaneous. The determination of the value of property stolen is an obligation of the investigating officer, and such information is essential to assure the completeness of a law enforcement investigative report on stolen property. The data were originally assembled by the Federal Bureau of Investigation (FBI) from reports submitted by agencies participating in the UCR. The ICPSR file was processed from Return A Supplement files provided by the FBI.

!!!WARNING~~~This dataset has a large number of flaws and is unable to properly answer many questions that people generally use it to answer, such as whether national hate crimes are changing (or at least they use the data so improperly that they get the wrong answer). A large number of people using this data (academics, advocates, reporting, US Congress) do so inappropriately and get the wrong answer to their questions as a result. Indeed, many published papers using this data should be retracted. Before using this data I highly recommend that you thoroughly read my book on UCR data, particularly the chapter on hate crimes (https://ucrbook.com/hate-crimes.html) as well as the FBI's own manual on this data. The questions you could potentially answer well are relatively narrow and generally exclude any causal relationships. ~~~WARNING!!!For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 10 release notes:Adds 2022 dataVersion 9 release notes:Adds 2021 data.Version 8 release notes:Adds 2019 and 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last UCR hate crime data they release. Changes .rda file to .rds.Version 7 release notes:Changes release notes description, does not change data.Version 6 release notes:Adds 2018 dataVersion 5 release notes:Adds data in the following formats: SPSS, SAS, and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Adds data for 1991.Fixes bug where bias motivation "anti-lesbian, gay, bisexual, or transgender, mixed group (lgbt)" was labeled "anti-homosexual (gay and lesbian)" prior to 2013 causing there to be two columns and zero values for years with the wrong label.All data is now directly from the FBI, not NACJD. The data initially comes as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. All work to clean the data and save it in various file formats was also done in R. Version 4 release notes: Adds data for 2017.Adds rows that submitted a zero-report (i.e. that agency reported no hate crimes in the year). This is for all years 1992-2017. Made changes to categorical variables (e.g. bias motivation columns) to make categories consistent over time. Different years had slightly different names (e.g. 'anti-am indian' and 'anti-american indian') which I made consistent. Made the 'population' column which is the total population in that agency. Version 3 release notes: Adds data for 2016.Order rows by year (descending) and ORI.Version 2 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The Hate Crime data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains information about hate crimes reported in the United States. Please note that the files are quite large and may take some time to open.Each row indicates a hate crime incident for an agency in a given year. I have made a unique ID column ("unique_id") by combining the year, agency ORI9 (the 9 character Originating Identifier code), and incident number columns together. Each column is a variable related to that incident or to the reporting agency. Some of the important columns are the incident date, what crime occurred (up to 10 crimes), the number of victims for each of these crimes, the bias motivation for each of these crimes, and the location of each crime. It also includes the total number of victims, total number of offenders, and race of offenders (as a group). Finally, it has a number of columns indicating if the victim for each offense was a certain type of victim or not (e.g. individual victim, business victim religious victim, etc.). The only changes I made to the data are the following. Minor changes to column names to make all column names 32 characters or fewer (so it can be saved in a Stata format), made all character values lower case, reordered columns. I also generated incident month, weekday, and month-day variables from the incident date variable included in the original data.

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 13 release notes:Adds 2022 dataVersion 12 release notes:Adds 2021 data.Version 11 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last SHR data they release. Changes .rda file to .rds.Version 10 release notes:Changes release notes description, does not change data.Version 9 release notes:Adds 2019 data.Version 8 release notes:Adds 2018 data.Changes source of data for years 1985-2018 to be directly from the FBI. 2018 data was received via email from the FBI, 2016-2017 is from the FBI who mailed me a DVD, and 1985-2015 data is from the FBI's Crime Data Explorer site (https://crime-data-explorer.fr.cloud.gov/downloads-and-docs).Adds .csv version of the data.Makes minor changes to value labels for consistency and to fix grammar. Version 7 release notes:Changes project name to avoid confusing this data for the ones done by NACJD.Version 6 release notes:Adds 2017 data.Version 5 release notes:Adds 2016 data.Standardizes the "group" column which categorizes cities and counties by population.Arrange rows in descending order by year and ascending order by ORI. Version 4 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. Version 3 Release Notes:Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Change column names for relationship variables from offender_n_relation_to_victim_1 to victim_1_relation_to_offender_n to better indicate that all relationship are victim 1's relationship to each offender. Reorder columns.This is a single file containing all data from the Supplementary Homicide Reports from 1976 to 2018. The Supplementary Homicide Report provides detailed information about the victim, offender, and circumstances of the murder. Details include victim and offender age, sex, race, ethnicity (Hispanic/not Hispanic), the weapon used, circumstances of the incident, and the number of both offenders and victims. Years 1976-1984 were downloaded from NACJD, while more recent years are from the FBI. All files came as ASCII+SPSS Setup files and were cleaned using R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors, have terminology be the same across years). The following is the summary of the Supplementary Homicide Report copied from ICPSR's 2015 page for the data.The Uniform Crime Reporting Program Data: Supplementary Homicide Reports (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

SANDAG provides an annual report on crime in the San Diego region. This dataset contains data from the 2009 through 2022 editions of the report. Data for 2023 is converted from California Incident Based Reporting System (CIBRS) data provided by SANDAG. Additional data comes from Arjis and DOJ OpenJustice. Some data for previous years reports is updated with new editions. "San Diego County" includes all cities and unincorporated areas in San Diego County. "Sheriff - Total" includes the contract cities and the unincorporated area served by the San Diego County Sheriff's Department. California and United States data come from the FBI's Annual Crime Reports.

In 2023, murder and manslaughter charges had the highest crime clearance rate in the United States, with 57.8 percent of all cases being cleared by arrest or so-called exceptional means. Motor vehicle theft cases had the lowest crime clearance rate, at 8.2 percent. What is crime clearance? Within the U.S. criminal justice system, criminal cases can be cleared (or closed) one of two ways. The first is through arrest, which means that at least one person has either been arrested, charged with an offense, or turned over to the court for prosecution. The second way a case can be closed is through what is called exceptional means, where law enforcement must have either identified the offender, gathered enough evidence to arrest, charge, and prosecute someone, identified the offender’s exact location, or come up against a circumstance outside the control of law enforcement that keeps them from arresting and prosecuting the offender. Crime in the United States Despite what many people may believe, crime in the United States has been on the decline. Particularly in regard to violent crime, the violent crime rate has almost halved since 1990, meaning that the U.S. is safer than it was almost 30 years ago. However, due to the FBI's recent transition to a new crime reporting system in which law enforcement agencies voluntarily report crime data, it is possible that figures do not accurately reflect the total amount of crime in the country.

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 20 release notes:Adds 2022 dataVersion 19 release notes:Starting in year 2018 I used the "card_actual_type" to identify missing months rather than using the "card_actual_pt" column. As noted in previous release notes, a change by the FBI starting in 2018 led to the "card_actual_type" to always say that this month is reported. The "card_actual_type" appears to be unchanged so can be used to actually measure months missing. The tradeoff is that pre-2018 the "card_actual_type" and the "card_actual_pt" columns did not always agree so could have different values. Still, I consider the ability to measure months missing at all to be worth this tradeoff. Version 18 release notes:Adds data for 2021.Version 17 release notes:Adds data for 2020.Please note that the FBI has retired UCR data ending in 2020 data so this will be the last Offenses Known and Clearances by Arrest data they release. Changes .rda files to .rds. Please note that in 2020 the card_actual_pt variable always returns that the month was reported. This causes 2020 to report that all months are reported for all agencies because I use the card_actual_pt variable to measure how many months were reported. This variable is almost certainly incorrect since it is extremely unlikely that all agencies suddenly always report. However, I am keeping this incorrect value to maintain a consistent definition of how many months are missing (measuring missing months through card_actual_type, for example, gives different results for previous years so I don't want to change this). Version 16 release notes:Changes release notes description, does not change data.Version 15 release notes:Adds data for 2019.Please note that in 2019 the card_actual_pt variable always returns that the month was reported. This causes 2019 to report that all months are reported for all agencies because I use the card_actual_pt variable to measure how many months were reported. This variable is almost certainly incorrect since it is extremely unlikely that all agencies suddenly always report. However, I am keeping this incorrect value to maintain a consistent definition of how many months are missing (measuring missing months through card_actual_type, for example, gives different results for previous years so I don't want to change this). Version 14 release notes:Adds arson data from the UCR's Arson dataset. This adds just the arson variables about the number of arson incidents, not the complete set of variables in that dataset (which include damages from arson and whether structures were occupied or not during the arson.As arson is an index crime, both the total index and the index property columns now include arson offenses. The "all_crimes" variables also now include arson.Adds a arson_number_of_months_missing column indicating how many months were not reporting (i.e. missing from the annual data) in the arson data. In most cases, this is the same as the normal number_of_months_missing but not always so please check if you intend to use arson data.Please note that in 2018 the card_actual_pt variable always returns that the month was reported. This causes 2018 to report that all months are reported for all agencies because I use the card_actual_pt variable to measure how many months were reported. This variable is almost certainly incorrect since it is extremely unlikely that all agencies suddenly always report. However, I am keeping this incorrect value to maintain a consistent definition of how many months are missing (measuring missing months through card_actual_type, for example, gives different results for previous years so I don't want to change this).For some reason, a small number of agencies (primarily federal agencies) had the same ORI number in 2018 and I removed these duplicate agencies. Version 13 release notes: Adds 2018 dataNew Orleans (ORI = LANPD00) data had more unfounded crimes than actual crimes in 2018 so unfounded columns for 2018 are all NA. Version 12 release notes: Adds population 1-3 columns - if an agency is in multiple counties, these variables show the population in the county with the most people in that agency in it (population_1), second largest county (population_2), and third largest county (population_3). Also adds county 1-3 columns which identify which c