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.

Investigator(s): Federal Bureau of Investigation Since 1930, the Federal Bureau of Investigation (FBI) has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. With the 1977 data, the title was expanded to Uniform Crime Reporting Program Data. Each year, participating law enforcement agencies contribute reports to the FBI either directly or through their state reporting programs. ICPSR archives the UCR data as five separate components: (1) summary data, (2) county-level data, (3) incident-level data (National Incident-Based Reporting System [NIBRS]), (4) hate crime data, and (5) various, mostly nonrecurring, data collections. Summary data are reported in four types of files: (a) Offenses Known and Clearances by Arrest, (b) Property Stolen and Recovered, (c) Supplementary Homicide Reports (SHR), and (d) Police Employee (LEOKA) Data (Law Enforcement Officers Killed or Assaulted). The county-level data provide counts of arrests and offenses aggregated to the county level. County populations are also reported. In the late 1970s, new ways to look at crime were studied. The UCR program was subsequently expanded to capture incident-level data with the implementation of the National Incident-Based Reporting System. The NIBRS data focus on various aspects of a crime incident. The gathering of hate crime data by the UCR program was begun in 1990. Hate crimes are defined as crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity. In September 1994, disabilities, both physical and mental, were added to the list. The fifth component of ICPSR's UCR holdings is comprised of various collections, many of which are nonrecurring and prepared by individual researchers. These collections go beyond the scope of the standard UCR collections provided by the FBI, either by including data for a range of years or by focusing on other aspects of analysis. NACJD has produced resource guides on UCR and on NIBRS data.

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.

The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_60 _100.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_100 _250.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_250 _plus.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'total_crime': total crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'total_violent _crime': total violent crime - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft - 'tot_prop _crime': total property crime - 'arson': arson

Photo by David von Diemar on Unsplash

This dataset from the FBI contains published national crime rates from 1985 to 2022.

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.

***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.

An annual publication in which the FBI provides data on the number of incidents, offenses, victims, and offenders in reported crimes that were motivated in whole or in part by a bias against the victim as perceived race, religion, sexual orientation, ethnicity, gender, disability, and gender identity.

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.

Example of crime statistics: according to the U.S. Federal Bureau of Investigation (FBI), in 2015, New York City reported about 130,000 property crimes, which included burglary, larceny, motor vehicle thefts, and arson. Meanwhile, Chicago reported about 80,000 property crimes the same year.

Alaska crime data from 2000 to present from the FBI Uniform Crime Reporting (UCR) program. Information includes data on both violent and property crime.The UCR Program's primary objective is to generate reliable information for use in law enforcement administration, operation, and management; over the years, however, the data have become one of the country’s leading social indicators. The program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.Source: US Federal Bureau of Investigation (FBI)This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: FBI UCR ProgramOffenses Known to Law Enforcement, by State by City, 2017 The FBI collects these data through the Uniform Crime Reporting (UCR) Program. Important note about rape data In 2013, the FBI’s UCR Program initiated the collection of rape data under a revised definition within the Summary Based Reporting System. The term “forcible” was removed from the offense name, and the definition was changed to “penetration, no matter how slight, of the vagina or anus with any body part or object, or oral penetration by a sex organ of another person, without the consent of the victim.” In 2016, the FBI Director approved the recommendation to discontinue the reporting of rape data using the UCR legacy definition beginning in 2017. General comment This table provides the volume of violent crime (murder and nonnegligent manslaughter, rape, robbery, and aggravated assault) and property crime (burglary, larceny-theft, and motor vehicle theft) as reported by city and town law enforcement agencies (listed alphabetically by state) that contributed data to the UCR Program. (Note: Arson is not included in the property crime total in this table; however, if complete arson data were provided, it will appear in the arson column.) Caution against ranking Readers should take into consideration relevant factors in addition to an area’s crime statistics when making any valid comparisons of crime among different locales. UCR Statistics: Their Proper Use provides more details. Methodology The data used in creating this table were from all city and town law enforcement agencies submitting 12 months of complete offense data for 2017. Rape figures, and violent crime, which rape is a part, will not be published in this table for agencies submitting rape using the UCR legacy rape definition. The rape figures, and violent crime, which rape is a part, published in this table are from only those agencies using the UCR revised rape definition as well as converted data from agencies that reported data for rape, sodomy, and sexual assault with an object via NIBRS. The FBI does not publish arson data unless it receives data from either the agency or the state for all 12 months of the calendar year. When the FBI determines that an agency’s data collection methodology does not comply with national UCR guidelines, the figure(s) for that agency’s offense(s) will not be included in the table, and the discrepancy will be explained in a footnote. Population estimation For the 2017 population estimates used in this table, the FBI computed individual rates of growth from one year to the next for every city/town and county using 2010 decennial population counts and 2011 through 2016 population estimates from the U.S. Census Bureau. Each agency’s rates of growth were averaged; that average was then applied and added to its 2016 Census population estimate to derive the agency’s 2017 population estimate.

Collected from the FBI Crime database stats and put into a .csv format perfect for loading in Python Pandas. Using for an assignment for my students so I figured why not share.

Context

The Uniform Crime Reporting (UCR) Program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.

Today, four annual publications, Crime in the United States, National Incident-Based Reporting System, Law Enforcement Officers Killed and Assaulted, and Hate Crime Statistics are produced from data received from over 18,000 city, university/college, county, state, tribal, and federal law enforcement agencies voluntarily participating in the program. The crime data are submitted either through a state UCR Program or directly to the FBI’s UCR Program.

This dataset focuses on the crime rates and law enforcement employment data in the state of California.

Content

Crime and law enforcement employment rates are separated into individual files, focusing on offenses by enforcement agency, college/university campus, county, and city. Categories of crimes reported include violent crime, murder and nonnegligent manslaughter, rape, robbery, aggravated assault, property crime, burglary, larceny-theft, motor vehicle damage, and arson. In the case of rape, data is collected for both revised and legacy definitions. In some cases, a small number of enforcement agencies switched definition collection sometime within the same year.

Acknowledgements

This dataset originates from the FBI UCR project, and the complete dataset for all 2015 crime reports can be found here.

Inspiration

• What are the most common types of crimes in California? Are there certain crimes that are more common in a particular place category, such as a college/university campus, compared to the rest of the state?
• How does the number of law enforcement officers compare to the crime rates of a particular area? Is the ratio similar throughout the state, or do certain campuses, counties, or cities have a differing rate?
• How does the legacy vs. refined definition of rape differ, and how do the rape counts compare? If you pulled the same data from FBI datasets for previous years, can you see a difference in rape rates over time?

Federal Bureau of Investigation, Department of Justice - Extraction of crime related data from the FBI's Uniform Crime Reporting (UCR) Program

Hate crime incidents reached the highest levels ever in the United States. The FBI's Crime Data Explorer (CDE) aims to provide transparency, create easier access, and expand awareness of criminal, and noncriminal, law enforcement data sharing; improve accountability for law enforcement; and provide a foundation to help shape public policy with the result of a safer nation. Use the CDE to discover available data through visualizations, download data in .csv format, and other large data files. https://cde.ucr.cjis.gov/LATEST/webapp/#/pages/home

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs’ departments. DCJS compiles these reports as New York’s official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred.

The UNIFORM CRIME REPORTING PROGRAM DATA: SUPPLEMENTARY HOMICIDE REPORTS, 2020 (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 2021, the San Diego Police Department began reporting to the FBI’s National Incident-Based Reporting System (NIBRS) for statistics. NIBRS collects data on all crimes reported to law enforcement agencies, not just the highest charges within those crimes. Crime categories in NIBRS include crimes against Persons (i.e., assault, homicide, etc.), Property (i.e., burglary, theft, robbery, etc.), and Society (i.e., alcohol and drug offenses, weapon offenses, gambling, etc.). These new categories are a shift from the older FBI reporting style (UCR Summary) of simply reporting violent and property crime counts. For the most part, SDPD’s crime reporting will follow the NIBRS categories now. Historical data will still be posted to the Annual Crime Reports website. This dataset comprises of Crime Offense Data extracted from the San Diego Police Department’s Records Management System and includes information such as the date/time of the reported offense, offense category, underlying code sections, and the hundred block address where the incident occurred. This data is dynamic as records are updated daily and may change or be deleted as police investigations proceed. Records range from January 2020 – Present. The SDPD Neighborhood Crime Summary Dashboard visualizes this dataset. For more information on NIBRS reporting guidelines please refer to the FBI’s 2021.1 National Incident-Based Reporting System User Manual. For national NIBRS data, you can visit the FBI’s Crime Data Explorer.

Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 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 counties the agency is in. The population column is the sum of the three population columns. Thanks to Mike Maltz for the suggestion!Fixes bug in the crosswalk data that is merged to this file that had the incorrect FIPS code for Clinton, Tennessee (ORI = TN00101). Thanks for Brooke Watson for catching this bug!Adds a last_month_reported column which says which month was reported last. This is actually how the FBI defines number_of_months_reported so is a more accurate representation of that. Removes the number_of_months_reported variable as the name is misleading. You should use the last_month_reported or the number_of_months_missing (see below) variable instead.Adds a number_of_months_missin