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

In 2023, around 3,640.56 violent crimes per 100,000 residents were reported in Oakland, California. This made Oakland the most dangerous city in the United States in that year. Four categories of violent crimes were used: murder and non-negligent manslaughter; forcible rape; robbery; and aggravated assault. Only cities with a population of at least 200,000 were considered.

This table contains data on the rate of violent crime (crimes per 1,000 population) for California, its regions, counties, cities and towns. Crime and population data are from the Federal Bureau of Investigations, Uniform Crime Reports. Rates above the city/town level include data from city, university and college, county, state, tribal, and federal law enforcement agencies. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Ten percent of all deaths in young California adults aged 15-44 years are related to assault and homicide. In 2010, California law enforcement agencies reported 1,809 murders, 8,331 rapes, and over 95,000 aggravated assaults. African Americans in California are 11 times more likely to die of assault and homicide than Whites. More information about the data table and a data dictionary can be found in the About/Attachments section.

In 2025, Pietermaritzburg in South Africa ranked as the world's most dangerous city with a crime rate of 82 per 100,000 inhabitants. Five of the 10 cities with the highest crime rates worldwide are found in South Africa. The list does not include countries where war and conflict exist. South Africa dominates crime statistics When looking at crime rates, among the 10 most dangerous cities in the world, half of them are found in South Africa. The country is struggling with extremely high levels of inequality, and is struggling with high levels of crime and power outages, harming the country's economy and driving more people into unemployment and poverty. Crime in Latin America On the other hand, when looking at murder rates, Latin America dominates the list of the world's most dangerous countries. Violence in Latin America is caused in great part by drug trafficking, weapons trafficking, and gang wars.

In the 2024/25 reporting year, West Yorkshire Police reported a crime rate of 114.5 crimes per 1,000 population, the highest crime rate among the provided police force areas whose territories include large cities. Greater Manchester Police reported a crime rate of 108.2 crimes per 1,000 population and had the second-highest crime rate during this year.

Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2024.

In 2023, the state with the highest crime rate in the United States per 100,000 inhabitants was New Mexico. That year, the crime rate was ******** crimes per 100,000 people. In comparison, New Hampshire had the lowest crime rate at ****** crimes per 100,000 people. Crime rate The crime rate in the United States has generally decreased over time. There are several factors attributed to the decrease in the crime rate across the United States. An increase in the number of police officers and an increase in income are some of the reasons for a decrease in the crime rate. Unfortunately, people of color have been disproportionately affected by crime rates, as they are more likely to be arrested for a crime versus a white person. Crime rates regionally The District of Columbia had the highest rate of reported violent crimes in the United States in 2023 per 100,000 inhabitants. The most common crime clearance type in metropolitan counties in the United States in 2020 was murder and non-negligent manslaughter. The second most dangerous city in the country in 2020 was Detroit. Detroit has faced severe levels of economic and demographic declines in the past years. Not only has the population decreased, the city has filed for bankruptcy. Despite the median household income increasing, the city still struggles financially.

This map shows a comparable measure of crime in the United States. The crime index compares the average local crime level to that of the United States as a whole. An index of 100 is average. A crime index of 120 indicates that crime in that area is 20 percent above the national average.The crime data is provided by Applied Geographic Solutions, Inc. (AGS). AGS created models using the FBI Uniform Crime Report databases as the primary data source and using an initial range of about 65 socio-economic characteristics taken from the 2000 Census and AGS’ current year estimates. The crimes included in the models include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. The total crime index incorporates all crimes and provides a useful measure of the relative “overall” crime rate in an area. However, these are unweighted indexes, meaning that a murder is weighted no more heavily than a purse snatching in the computations. The geography depicts states, counties, Census tracts and Census block groups. An urban/rural "mask" layer helps you identify crime patterns in rural and urban settings. The Census tracts and block groups help identify neighborhood-level variation in the crime data.------------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

This dataset reflects reported incidents of crime that have occurred in the City of Chicago over the past year, minus the most recent seven days of data. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited.

The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. Any use of the information for commercial purposes is strictly prohibited. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily.

Comprehensive crime statistics for Orange County including homicides, violent crime, property crime, and city-by-city breakdowns with five-year trend analysis.

The Part 1 crime rate captures incidents of homicide, rape, aggravated assault, robbery, burglary, larceny, and auto theft that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police Department Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

The World Crime Index 2023 dataset provides records of crime rankings for cities worldwide, along with associated information on their respective countries. This dataset is focused on the year 2023 and includes the following columns:

• Rank: The ranking of a city based on its crime index, with lower numbers indicating higher crime rates.
• City: The name of the city for which crime data is reported.
• Country: The country to which the city belongs.
• Crime Index: A numerical value representing the overall level of crime in a city, with higher values indicating higher crime rates.
• Safety Index: An index indicating the general level of safety in a city, derived from factors such as infrastructure, healthcare, and political stability.

This dataset enables data scientists to analyze and compare crime rankings across cities and countries, providing insights into the relative safety levels of different locations in the year 2023. By leveraging this dataset, researchers can conduct exploratory data analysis, perform comparative studies, and identify potential trends and patterns in crime rates globally for the specified year.

This project was designed to isolate the effects that individual crimes have on wage rates and housing prices, as gauged by individuals' and households' decisionmaking preferences changing over time. Additionally, this project sought to compute a dollar value that individuals would bear in their wages and housing costs to reduce the rates of specific crimes. The study used multiple decades of information obtained from counties across the United States to create a panel dataset. This approach was designed to compensate for the problem of collinearity by tracking how housing and occupation choices within particular locations changed over the decade considering all amenities or disamenities, including specific crime rates. Census data were obtained for this project from the Integrated Public Use Microdata Series (IPUMS) constructed by Ruggles and Sobek (1997). Crime data were obtained from the Federal Bureau of Investigation's Uniform Crime Reports (UCR). Other data were collected from the American Chamber of Commerce Researchers Association, County and City Data Book, National Oceanic and Atmospheric Administration, and Environmental Protection Agency. Independent variables for the Wages Data (Part 1) include years of education, school enrollment, sex, ability to speak English well, race, veteran status, employment status, and occupation and industry. Independent variables for the Housing Data (Part 2) include number of bedrooms, number of other rooms, building age, whether unit was a condominium or detached single-family house, acreage, and whether the unit had a kitchen, plumbing, public sewers, and water service. Both files include the following variables as separating factors: census geographic division, cost-of-living index, percentage unemployed, percentage vacant housing, labor force employed in manufacturing, living near a coastline, living or working in the central city, per capita local taxes, per capita intergovernmental revenue, per capita property taxes, population density, and commute time to work. Lastly, the following variables measured amenities or disamenities: average precipitation, temperature, windspeed, sunshine, humidity, teacher-pupil ratio, number of Superfund sites, total suspended particulate in air, and rates of murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, violent crimes, and property crimes.

The city in Romania with the highest crime index was Constanta with ****, it was followed by Craiova, with an index value of ****. These values are high, given that the higher the index value, the higher the level of crime. Nevertheless, theses values are way above the overall crime index in Romania, which by 2024 increased to *****.

The violent crime rate indicator includes both the total number of violent crime incidents per year in Champaign County, and the number of violent crime incidents per 100,000 people per year in Champaign County. “Violent crimes” are those counted in the following categories in the Illinois State Police’s annual Crime in Illinois report: Criminal Homicide, Criminal Sexual Assault (Rape), Robbery, Aggravated Assault, and Aggravated Battery. The incidence of violent crime is an integral part of understanding the safety of a given community.

Both the total number of offenses in Champaign County and the rate per 100,000 population were significantly lower in 2021 than at the start of the measured time period, 1996. The most recent rise in both of these figures was in 2019-2020, before falling again in 2021. The year with the lowest number of total offenses and the rate per 100,000 population in the study period was 2015; both measures are slightly higher since then.

This data is sourced from the Illinois State Police’s annually released Crime in Illinois: Annual Uniform Crime Report, available on the Uniform Crime Report Index Offense Explorer.

Sources: Illinois State Police. (2021). Crime in Illinois: Annual Uniform Crime Report 2021. Illinois State Police. (2020). Crime in Illinois: Annual Uniform Crime Report 2020. Illinois State Police. (2019). Crime in Illinois: Annual Uniform Crime Report 2019. Illinois State Police. (2018). Crime in Illinois: Annual Uniform Crime Report 2018. Illinois State Police. (2017). Crime in Illinois: Annual Uniform Crime Report 2017.Illinois State Police. (2016). Crime in Illinois: Annual Uniform Crime Report 2016. Illinois State Police. (2015). Crime in Illinois: Annual Uniform Crime Report 2015. Illinois State Police. (2014). Crime in Illinois: Annual Uniform Crime Report 2014.; Illinois State Police. (2012). Crime in Illinois: Annual Uniform Crime Report 2012.; Illinois State Police. (2011). Crime in Illinois: Annual Uniform Crime Report 2010-2011.; Illinois State Police. (2009). Crime in Illinois: Annual Uniform Crime Report 2009.; Illinois State Police. (2007). Crime in Illinois: Annual Uniform Crime Report 2007.; Illinois State Police. (2005). Crime in Illinois: Annual Uniform Crime Report 2005.; Illinois State Police. (2003). Crime in Illinois: Annual Uniform Crime Report 2003.; Illinois State Police. (2001). Crime in Illinois: Annual Uniform Crime Report 2001.; Illinois State Police. (1999). Crime in Illinois: Annual Uniform Crime Report 1999.; Illinois State Police. (1997). Crime in Illinois: Annual Uniform Crime Report 1997.

Crime data from years prior to the current one. The data included in this dataset has been reviewed and approved by a Milwaukee Police Department supervisor and the Milwaukee Police Department’s Records Management Division. This approval process can take a few weeks from the reported date of the crime. For preliminary crime data, please visit the Milwaukee Police Department’s Crime Maps and Statistics dashboard at https://city.milwaukee.gov/police/Information-Services/Crime-Maps-and-Statistics.

Wisconsin Incident Based Report (WIBR) Group A Offenses.

The Crime Data represents incident level data defined by Wisconsin Incident Based Reporting System (WIBRS) codes. WIBRS reporting is a crime reporting standard and can not be compared to any previous UCR report. Therefore, the Crime Data may reflect:

• Information not yet verified by further investigation
• Preliminary crime classifications that may be changed at a later date based upon further investigation
• Information that may include mechanical or human error

Neither the City of Milwaukee nor the Milwaukee Police Department guarantee (either express or implied) the accuracy, completeness, timeliness, or correct sequencing of the Crime Data. The City of Milwaukee and the Milwaukee Police Department shall have no liability for any error or omission, or for the use of, or the results obtained from the use of the Crime Data. In addition, the City of Milwaukee and the Milwaukee Police Department caution against using the Crime Data to make decisions/comparisons regarding the safety of or the amount of crime occurring in a particular area. When reviewing the Crime Data, the site user should consider that:

• The information represents only police services where a report was made and does not include other calls for police service
• The information does not reflect or certify "safe" or "unsafe" areas
• The information will sometimes reflect where the crime was reported versus where the crime occurred

The use of the Crime Data indicates the site user's unconditional acceptance of all risks associated with the use of the Crime Data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page. XY fields in data is in projection Wisconsin State Plane South NAD27 (WKID 32054).

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.

Violent Crime in CA

Regional, County, City/Town Rates 2006-2010

By Health [source]

About this dataset

This dataset contains information on the rate of violent crime across California - its regions, counties, cities and towns. The data was collected as part of a larger effort by the Office of Health Equity to better understand public health indicators and ensure equitable outcomes for all.

The numbers reflect more than just a problem in California communities - it reflects a problem with unequal access to resources and opportunity across race, ethnicities and geographies. African Americans in California are 11 times more likely to die from assault or homicide compared to white Californians. Similarly, certain regions report higher crime rates than others at the county level- indicating underlying issues with poverty or institutionalized inequality.

Law enforcement agencies teamed up with the Federal Bureau of Investigations’ Uniform Crime Reports to collect this data table which includes details such as reported number of violent crimes (numerator), population size (denominator), rate per 1,000 population (ratex1000) confidence intervals (LL_95CI & UL_95CI ) standard errors & relative standard errors (se & rse) as well as ratios between city/town rates vs state rates (RR_city2state). Additionally, each record is classified according to region name/code and race/ethnicity code/name , giving researchers further insight into these troubling statistics at both macro and micro levels.

Armed with this information we can explore new ways identify inequitable areas and begin looking for potential solutions that combat health disparities within our communities like never before!

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How to use the dataset

The data is presented with twenty columns providing various segments within each row including:

• Crime definition
• Race/ethnicity code
• Region code
• Geographic area identifier
• Numerator and Denominator values of population
• Standard Error and 95% Confidence Intervals
• Relatvie Standard Error (RSE) value

• Ratios related to city/towns rate to state rate

  The information provided can be used for a variety of applications such as creating visualizations or developing predictive models. It is important to note that rates are expressed per 1,000 population for their respective geographic area during each period noted by the report year field within the dataset. Additionally CA_decile column may be useful in comparing counties due numerical grading system identifying a region’s percentile ranking when compared to other counties within the current year’s entire dataset as well as ratios present under RR_city2state which presents ratio comparison between city/town rate and state rate outside given geographic area have made this an extremely valuable dataset for further analysis

Research Ideas

• Developing a crime prediction and prevention program that uses machine learning models to identify criminal hotspots and direct resources to those areas
• Exploring the connection between race/ethnicity and rates of violence in California
• Creating visualizations and interactive maps to display types of violent crime across different counties within California

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: Violent_Crime_Rate_California_2006-2010-DD.csv

File: rows.csv | Column name | Description ...

The city states of Berlin, Hamburg and Bremen were the states with the three highest crime rates in Germany in 2024, while the federal state of Bavaria had the lowest. Urban areas generally have higher crime rates than rural ones, making it difficult to compare Germany's three city states with the much larger federal states, which typically cover quite large areas. The federal state with the highest crime rate was Bremen at 14,998 crimes per 100 thousand people, compared with the German average of 6,995.