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A CSV file which is updated daily by 11am and includes crime incidents from November 1st, 2015 forward through September 2, 2025*. Homicides, rapes, robberies, aggravated assaults, burglaries, thefts, motor vehicle thefts, arsons, and drug offenses are included (based on the primary offense listed for each incident).
*Note: We want to inform our users that updates to this dataset is currently unavailable from September 3, 2025, forward. The city is actively working with our partners to restore regular data publishing and is committed to resuming daily updates as soon as possible. We appreciate your patience and understanding during this time. Our goal is to ensure the accuracy, consistency, and timeliness of the data we provide. Please check back for updates and thank you for your continued interest in open data.
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TwitterIn 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.
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Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Mohave County, AZ (DISCONTINUED) (FBITC004015) from 2004 to 2021 about Mohave County, AZ; Lake Havasu City; crime; violent crime; property crime; AZ; and USA.
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TwitterThis research involved the exploration of how the geographies of different crimes intersect with the geographies of social, economic, and demographic characteristics in Nashville, Tennessee, Portland, Oregon, and Tucson, Arizona. Violent crime data were collected from all three cities for the years 1998 through 2002. The data were geo-coded and then aggregated to block groups and census tracts. The data include variables on 28 different crimes, numerous demographic variables taken from the 2000 Census, and several land use variables.
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Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Maricopa County, AZ (DISCONTINUED) (FBITC004013) from 2004 to 2017 about Maricopa County, AZ; crime; violent crime; property crime; Phoenix; AZ; and USA.
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This map displays the boundary of Police Grid area with a label identifying the number of the grid. Labeling only occurs to the 50,000 scale level.
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FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Arizona State University: Main Campus (University or College) in Arizona, including incidents, statistics, demographics, and detailed incident information.
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Twitterhttps://www.icpsr.umich.edu/web/ICPSR/studies/26081/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/26081/terms
The purpose of the study was to conduct a process and outcome evaluation of the Homicide Clearance Project in the Phoenix, Arizona Police Department. The primary objective of the Homicide Clearance Project was to improve homicide clearance rates by increasing investigative time through the transfer of four crime scene specialists to the homicide unit. In 2004, the Phoenix Police Department received a grant from the Bureau of Justice Assistance providing support for the assignment of four crime scene specialists directly to the department's Homicide Unit. Responsibilities of the crime scene specialists were to collect evidence at homicide scenes, prepare scene reports, develop scene diagrams, and other supportive activities. Prior to the project, homicide investigators were responsible for evidence collection, which reduced the time they could devote to investigations. The crime scene specialists were assigned to two of the four investigative squads within the homicide unit. This organizational arrangement provided for a performance evaluation of the squads with crime scene specialists (experimental squads) against the performance of the other squads (comparison squads). During the course of the evaluation, research staff coded information from all homicides that occurred during the 12-month period prior to the transfers (July 1, 2003 - June 30, 2004), referred to as the baseline period, the 2-month training period (July 1, 2004 - August 31, 2004), and a 10-month test period (September 1, 2004 - June 30, 2005). Data were collected on 404 homicide cases (Part 1), 532 homicide victims and survivors (Part 2), and 3,338 records of evidence collected at homicide scenes (Part 3). The two primary sources of information for the evaluation were investigative reports from the department's records management system, called the Police Automated Computer Entry (PACE) system, and crime laboratory reports from the crime laboratory's Laboratory Information Management System (LIMS). Part 1, Part 2, and Part 3 each contain variables that measure squad type, time period, and whether six general categories of evidence were collected. Part 1 contains a total of 18 variables including number of investigators, number of patrol officers at the scene, number of witnesses, number of crime scene specialists at the scene, number of investigators collecting evidence at the scene, total number of evidence collectors, whether the case was open or closed, type of arrest, and whether the case was open or closed by arrest. Part 2 contains a total of 37 variables including victim characteristics and motives. Other variables in Part 2 include an instrumental/expressive homicide indicator, whether the case was open or closed, type of arrest, whether the case was open or closed by arrest, number of investigators, number of patrol officers at the scene, number of witnesses, and investigative time to closure. Part 3 contains a total of 46 variables including primary/secondary scene indicator, scene type, number of pieces of evidence, total time at the scene, and number of photos taken. Part 3 also includes variables that measure whether 16 specific types of evidence were found and the number of items of evidence that were collected for 13 specific evidence types.
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FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Arizona Department of Public Safety (State Police) in Arizona, including incidents, statistics, demographics, and detailed incident information.
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The Tempe Police Department prides itself in its continued efforts to reduce harm within the community and is providing this dataset on hate crime incidents that occur in Tempe.This data compares hate crimes in the City of Tempe and the State of Arizona. The data source is from the Federal Bureau of Investigation (FBI) and the Department of Justice (DOJ) at both the national and state level: FBIhttps://www.fbi.gov/services/cjis/ucr/publications#Hate-Crime%20StatisticsDOJhttps://www.justice.gov/hatecrimes/facts-and-statisticsInformation about Tempe Police Department's collection and reporting process for possible hate crimes is included in the story map Projecting Our Community form Hate at https://storymaps.arcgis.com/stories/a963e97ca3494bfc8cd66d593eebabafAdditional InformationSource: Federal Bureau of Investigation (FBI) and the Department of Justice (DOJ) https://www.fbi.gov/services/cjis/ucr/publications#Hate-Crime%20Statistics, https://www.justice.gov/hatecrimes/facts-and-statisticsContact: Angelique BeltranContact E-Mail: angelique_beltran@tempe.govData Source Type: TabularPreparation Method: Data extracted from sources, reformatted in Excel and uploaded.Publish Frequency: AnnualPublish Method: ManualData Dictionary
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TwitterThis dataset provides the crime clearance rate nationally and for the City of Tempe. An overall clearance rate is developed as part of the Department’s report for the Federal Bureau of Investigation (FBI) Uniform Crime Report (UCR) Program. The statistics in the UCR Program are based on reports the Tempe Police Department officially submits to the Arizona Department of Public Safety (DPS).In the UCR Program, there are two ways that a law enforcement agency can report that an offense is cleared:(1) cleared by arrest or solved for crime reporting purposes, or(2) cleared by exceptional means.An offense is cleared by arrest, or solved for crime reporting purposes, when three specific conditions have been met. The three conditions are that at least one person has been: (1) arrested; (2) charged with the commission of the offense; and (3) turned over to the court for prosecution.In some situations, an agency may be prevented from arresting and formally charging an offender due to factors outside of the agency's control. In these cases, an offense can be cleared by exceptional means, if the following four conditions are met: (1) identified the offender; (2) gathered enough evidence to support an arrest, make a charge, and turn over the offender to the court for prosecution; (3) identified offender’s exact location so that suspect can immediately be taken into custody; and (4) encountered a circumstance outside law enforcement"s control that prohibits arresting, charging and prosecuting the offender.The UCR clearance rate is one tool for helping the police to understand and assess success at investigating crimes. However, these rates should be interpreted with an understanding of the unique challenges faced in reporting and investigating crimes. Clearance rates for a given year may be greater than 100% because a clearance is reported for the year the clearance occurs, which may not be the same year that the crime occurred. Often, investigations may take months or years, resulting in cases being cleared years after the actual offense. Additionally, there may be delays in the reporting of crimes, which would push the clearance of the case out beyond the year it happened.This page provides data for the Violent Cases Clearance Rate performance measure. The performance measure dashboard is available at 1.12 Violent Cases Clearance Rate.Additional InformationSource: Tempe Police Department (TPD) Versadex Records Management System (RMS) submitted to Arizona Department of Public Safety (AZ DPS), which submits data to the Federal Bureau of Investigation (FBI)Contact (author): Contact E-Mail (author): Contact (maintainer): Brooks LoutonContact E-Mail (maintainer): Brooks_Louton@tempe.govData Source Type: ExcelPreparation Method: Drawn from the Annual FBI Crime In the United States PublicationPublish Frequency: AnnuallyPublish Method: ManualData Dictionary
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TwitterFinancial overview and grant giving statistics of Arizona Crime Prevention Assn
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Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Pinal County, AZ (DISCONTINUED) (FBITC004021) from 2004 to 2021 about Pinal County, AZ; crime; violent crime; property crime; Phoenix; AZ; and USA.
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Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Gila County, AZ (DISCONTINUED) (FBITC004007) from 2004 to 2020 about Gila County, AZ; crime; violent crime; property crime; AZ; and USA.
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TwitterFinancial overview and grant giving statistics of Arizona Crime Victim Rights Law Group
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FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Maricopa County, Arizona, including incidents, statistics, demographics, and agency information.
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This study investigates rates of serious crime for selected public housing developments in Washington, DC, Phoenix, Arizona, and Los Angeles, California, for the years 1986 to 1989. Offense rates in housing developments were compared to rates in nearby areas of private housing as well as to city-wide rates. In addition, the extent of law enforcement activity in housing developments as represented by arrests was considered and compared to arrest levels in other areas. This process allowed both intra-city and inter-city comparisons to be made. Variables cover study site, origin of data, year of event, offense codes, and location of event. Los Angeles files also include police division.
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Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Apache County, AZ (DISCONTINUED) (FBITC004001) from 2004 to 2015 about Apache County, AZ; crime; violent crime; property crime; AZ; and USA.
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Graph and download economic data for Combined Violent and Property Crime Offenses Known to Law Enforcement in Graham County, AZ (DISCONTINUED) (FBITC004009) from 2006 to 2020 about Graham County, AZ; crime; violent crime; property crime; AZ; and USA.
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Combined Violent and Property Crime Offenses Known to Law Enforcement in Coconino County, AZ was 307.00000 Known Incidents in January of 2021, according to the United States Federal Reserve. Historically, Combined Violent and Property Crime Offenses Known to Law Enforcement in Coconino County, AZ reached a record high of 701.00000 in January of 2005 and a record low of 307.00000 in January of 2021. 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 Coconino County, AZ - last updated from the United States Federal Reserve on November of 2025.
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A CSV file which is updated daily by 11am and includes crime incidents from November 1st, 2015 forward through September 2, 2025*. Homicides, rapes, robberies, aggravated assaults, burglaries, thefts, motor vehicle thefts, arsons, and drug offenses are included (based on the primary offense listed for each incident).
*Note: We want to inform our users that updates to this dataset is currently unavailable from September 3, 2025, forward. The city is actively working with our partners to restore regular data publishing and is committed to resuming daily updates as soon as possible. We appreciate your patience and understanding during this time. Our goal is to ensure the accuracy, consistency, and timeliness of the data we provide. Please check back for updates and thank you for your continued interest in open data.