Dataset showing reported crime counts and rates by offense category for Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington counties. Crime rates are calculated using Census estimates of each county's resident population.

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.

This map shows the total crime index in the U.S. in 2018 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.Additional Esri Resources:Esri DemographicsU.S. 2018/2023 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers

Combined Violent and Property Crime Offenses Known to Law Enforcement in Hennepin County, MN was 67.00000 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 Hennepin County, MN reached a record high of 239.00000 in January of 2004 and a record low of 64.00000 in January of 2019. 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 Hennepin County, MN - last updated from the United States Federal Reserve on July of 2025.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Big Stone County, MN was 30.00000 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 Big Stone County, MN reached a record high of 74.00000 in January of 2005 and a record low of 14.00000 in January of 2019. 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 Big Stone County, MN - last updated from the United States Federal Reserve on July of 2025.

Recognizing that violence can be an intractable problem in many communities and that there are numerous approaches to both an immediate violence problem and the range of root causes behind violence, the National Institute of Justice funded an investigation into what factors underlie violence and efforts being implemented to address those factors and potentially reduce violence at the community level. In this mixed methods study, the RAND Corporation drew on data from key informant interviews, community surveys, administrative data, and geographic data to examine specific factors that contribute to violence, as well as a range of anti-violence efforts that have been used to address violence levels in two U.S. communities: the Bullseye area of Durham, North Carolina, and the Northside (North Minneapolis) neighborhood of Minneapolis, Minnesota. Specifically, the research project aimed to answer the following questions: What are community level factors that can contribute to persistent violence? What are the key factors in both cities that distinguish high violent crime areas compared to low violent crime areas? This collection contains final analytic datasets for Durham (DS1) and Minneapolis (DS2), violent crime rate data (DS3), community survey data for Durham (DS4) and Minneapolis (DS5), and multiple datasets containing community-level contextual factors from the American Community Survey (ACS) and geographical data from the U.S. Census Bureau (2009-2018) that were used to build the final analytic datasets (DS6-DS11). Qualitative data from key informant interviews and GIS data are not available for download at this time. Access to Durham and Minneapolis community survey data is restricted.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Cook County, MN was 57.00000 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 Cook County, MN reached a record high of 173.00000 in January of 2012 and a record low of 39.00000 in January of 2018. 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 Cook County, MN - last updated from the United States Federal Reserve on July of 2025.

Mongolia MN: Intentional Homicides: Male: per 100,000 Male data was reported at 8.818 Ratio in 2016. This records a decrease from the previous number of 9.566 Ratio for 2015. Mongolia MN: Intentional Homicides: Male: per 100,000 Male data is updated yearly, averaging 11.529 Ratio from Dec 2007 (Median) to 2016, with 10 observations. The data reached an all-time high of 17.627 Ratio in 2007 and a record low of 8.818 Ratio in 2016. Mongolia MN: Intentional Homicides: Male: per 100,000 Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mongolia – Table MN.World Bank: Health Statistics. Intentional homicides, male are estimates of unlawful male homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.; ; UN Office on Drugs and Crime's International Homicide Statistics database.; ;

Lac Qui Parle County, MN - Combined Violent and Property Crime Offenses Known to Law Enforcement in Lac qui Parle County, MN was 18.00000 Known Incidents in January of 2021, according to the United States Federal Reserve. Historically, Lac Qui Parle County, MN - Combined Violent and Property Crime Offenses Known to Law Enforcement in Lac qui Parle County, MN reached a record high of 52.00000 in January of 2006 and a record low of 11.00000 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for Lac Qui Parle County, MN - Combined Violent and Property Crime Offenses Known to Law Enforcement in Lac qui Parle County, MN - last updated from the United States Federal Reserve on July of 2025.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Steele County, MN was 67.00000 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 Steele County, MN reached a record high of 213.00000 in January of 2005 and a record low of 67.00000 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 Steele County, MN - last updated from the United States Federal Reserve on June of 2025.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Lake of the Woods County, MN was 3.00000 Known Incidents in January of 2020, according to the United States Federal Reserve. Historically, Combined Violent and Property Crime Offenses Known to Law Enforcement in Lake of the Woods County, MN reached a record high of 105.00000 in January of 2007 and a record low of 3.00000 in January of 2020. 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 Lake of the Woods County, MN - last updated from the United States Federal Reserve on July of 2025.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Washington County, MN was 871.00000 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 Washington County, MN reached a record high of 1466.00000 in January of 2004 and a record low of 631.00000 in January of 2019. 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 Washington County, MN - last updated from the United States Federal Reserve on July of 2025.

This project sought to investigate a possible relationship between sentencing guidelines and family structure in the United States. The research team developed three research modules that employed a variety of data sources and approaches to understand family destabilization and community distress, which cannot be observed directly. These three research modules were used to discover causal relationships between male withdrawal from productive spheres of the economy and resulting changes in the community and families. The research modules approached the issue of sentencing guidelines and family structure by studying: (1) the flow of inmates into prison (Module A), (2) the role of and issues related to sentencing reform (Module B), and family disruption in a single state (Module C). Module A utilized the Uniform Crime Reporting (UCR) Program data for 1984 and 1993 (Parts 1 and 2), the 1984 and 1993 National Correctional Reporting Program (NCRP) data (Parts 3-6), the Urban Institute's 1980 and 1990 Underclass Database (UDB) (Part 7), the 1985 and 1994 National Longitudinal Survey on Youth (NLSY) (Parts 8 and 9), and county population, social, and economic data from the Current Population Survey, County Business Patterns, and United States Vital Statistics (Parts 10-12). The focus of this module was the relationship between family instability, as measured by female-headed families, and three societal characteristics, namely underclass measures in county of residence, individual characteristics, and flows of inmates. Module B examined the effects of statewide incarceration and sentencing changes on marriage markets and family structure. Module B utilized data from the Current Population Survey for 1985 and 1994 (Part 12) and the United States Statistical Abstracts (Part 13), as well as state-level data (Parts 14 and 15) to measure the Darity-Myers sex ratio and expected welfare income. The relationship between these two factors and family structure, sentencing guidelines, and minimum sentences for drug-related crimes was then measured. Module C used data collected from inmates entering the Minnesota prison system in 1997 and 1998 (Part 16), information from the 1990 Census (Part 17), and the Minnesota Crime Survey (Part 18) to assess any connections between incarceration and family structure. Module C focused on a single state with sentencing guidelines with the goal of understanding how sentencing reforms and the impacts of the local community factors affect inmate family structure. The researchers wanted to know if the aspects of locations that lose marriageable males to prison were more important than individual inmate characteristics with respect to the probability that someone will be imprisoned and leave behind dependent children. Variables in Parts 1 and 2 document arrests by race for arson, assault, auto theft, burglary, drugs, homicide, larceny, manslaughter, rape, robbery, sexual assault, and weapons. Variables in Parts 3 and 4 document prison admissions, while variables in Parts 5 and 6 document prison releases. Variables in Part 7 include the number of households on public assistance, education and income levels of residents by race, labor force participation by race, unemployment by race, percentage of population of different races, poverty rate by race, men in the military by race, and marriage pool by race. Variables in Parts 8 and 9 include age, county, education, employment status, family income, marital status, race, residence type, sex, and state. Part 10 provides county population data. Part 11 contains two different state identifiers. Variables in Part 12 describe mortality data and welfare data. Part 13 contains data from the United States Statistical Abstracts, including welfare and poverty variables. Variables in Parts 14 and 15 include number of children, age, education, family type, gender, head of household, marital status, race, religion, and state. Variables in Part 16 cover admission date, admission type, age, county, education, language, length of sentence, marital status, military status, sentence, sex, state, and ZIP code. Part 17 contains demographic data by Minnesota ZIP code, such as age categories, race, divorces, number of children, home ownership, and unemployment. Part 18 includes Minnesota crime data as well as some demographic variables, such as race, education, and poverty ratio.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Meeker County, MN was 143.00000 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 Meeker County, MN reached a record high of 371.00000 in January of 2005 and a record low of 94.00000 in January of 2018. 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 Meeker County, MN - last updated from the United States Federal Reserve on July of 2025.

Mongolia MN: Intentional Homicides: per 100,000 People data was reported at 7.200 Ratio in 2015. This records a decrease from the previous number of 7.500 Ratio for 2014. Mongolia MN: Intentional Homicides: per 100,000 People data is updated yearly, averaging 8.800 Ratio from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 15.800 Ratio in 2005 and a record low of 7.100 Ratio in 2012. Mongolia MN: Intentional Homicides: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mongolia – Table MN.World Bank: Health Statistics. Intentional homicides are estimates of unlawful homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.; ; UN Office on Drugs and Crime's International Homicide Statistics database.; Weighted average;

India Railway Crime: Value of Property Recovered data was reported at 3.100 INR mn in 2017. This records a decrease from the previous number of 47.900 INR mn for 2016. India Railway Crime: Value of Property Recovered data is updated yearly, averaging 38.100 INR mn from Mar 2011 (Median) to 2017, with 7 observations. The data reached an all-time high of 51.500 INR mn in 2012 and a record low of 3.100 INR mn in 2017. India Railway Crime: Value of Property Recovered data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB018: Railway Statistics: Railway Crime.

Financial overview and grant giving statistics of Mayo Health System Southeast Mn Region

Combined Violent and Property Crime Offenses Known to Law Enforcement in Brown County, MN was 51.00000 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 Brown County, MN reached a record high of 51.00000 in January of 2021 and a record low of 0.00000 in January of 2011. 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 Brown County, MN - last updated from the United States Federal Reserve on July of 2025.

Combined Violent and Property Crime Offenses Known to Law Enforcement in Winona County, MN was 118.00000 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 Winona County, MN reached a record high of 118.00000 in January of 2010 and a record low of 23.00000 in January of 2014. Trading Economics provides the current actual value, an historical data chart and related indicators for Combined Violent and Property Crime Offenses Known to Law Enforcement in Winona County, MN - last updated from the United States Federal Reserve on July of 2025.

India Railway Crime: Railway Protection Force: Railways Act: Amount of Fine Realized data was reported at 69.400 INR mn in 2017. This records an increase from the previous number of 63.870 INR mn for 2016. India Railway Crime: Railway Protection Force: Railways Act: Amount of Fine Realized data is updated yearly, averaging 421.200 INR mn from Mar 2011 (Median) to 2017, with 7 observations. The data reached an all-time high of 530.900 INR mn in 2014 and a record low of 63.870 INR mn in 2016. India Railway Crime: Railway Protection Force: Railways Act: Amount of Fine Realized data remains active status in CEIC and is reported by Ministry of Railways. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TB018: Railway Statistics: Railway Crime.