In 2023, Texas had the highest number of forcible rape cases in the United States, with 15,097 reported rapes. Delaware had the lowest number of reported forcible rape cases at 194. Number vs. rate It is perhaps unsurprising that Texas and California reported the highest number of rapes, as these states have the highest population of states in the U.S. When looking at the rape rate, or the number of rapes per 100,000 of the population, a very different picture is painted: Alaska was the state with the highest rape rate in the country in 2023, with California ranking as 30th in the nation. The prevalence of rape Rape and sexual assault are notorious for being underreported crimes, which means that the prevalence of sex crimes is likely much higher than what is reported. Additionally, more than a third of women worry about being sexually assaulted, and most sexual assaults are perpetrated by someone the victim knew.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2016). For additional details, please see the attached data dictionary in the ‘About’ section.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. 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. 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 Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

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.

Nature of sexual assault by rape or penetration experienced by adults since the age of 16 years, including breakdowns by age, sex, victim-perpetrator relationship, location and other factors. Analyses from the Crime Survey for England and Wales (CSEW).

This dataset was compiled by the Illinois Criminal Justice Information Authority (ICJIA) at the request of the Governor’s Children’s Cabinet. This data contains the population of youth ages 13-26 in each county, the total population of each county, and the number and rate of index crimes reported, with domestic violence offenses and rates reported separately for every year between 2006 and 2015.

For the purpose of this analysis the crime data was gathered from the Illinois State Police Annual report Crime in Illinois. This publication is produced by the Illinois State Police every year using the UCR data that is submitted to them by individual jurisdictions throughout the state. The accuracy of this data presented is dependent on the local jurisdictions reporting their index crime and domestic violence offenses to ISP, so it can be included in the annual report.

Therefore, if there is large decrease in number of index crimes reported in the dataset it is likely that one or more jurisdictions did not report data for that year to ISP. If there is a large increase from year to year within a county it is likely that a jurisdiction within the county, who previously had not reported crime data, did report crime data for that year. If there is no reported crime in a certain year that means no jurisdictions, or a small jurisdiction with no crime from that county reported data to the Illinois State Police. The annual Crime in Illinois reports can be found on the ISP website www.isp.state.il.us.

A direct link to that annual reports is: http://www.isp.state.il.us/crime/ucrhome.cfm#anlrpts.

The Illinois Criminal Justice Information Authority did not record the data that is expressed in the dataset. ICJIA simply used the ISP reports to compile that yearly crime data into one chart that could be provided to the Illinois Governor’s Children’s Cabinet. This data set has be critically examined to be accurate according to the annual Crime in Illinois Reports. If there are issues with the data set provided please contact the Illinois State Police or the individual jurisdictions within a specific county.

**Index offenses do not include every crime event that occurs. Prior to 2014 there were 8 index crimes reported by the Illinois State Police in their annual reports, Criminal Homicide, Rape, Robbery, Aggravated Battery/Aggravated Assault, Burglary, Theft, Motor Vehicle Theft, and Arson. In 2014 there were two new offenses added to the list of index crimes these were Human Trafficking – Commercial Sex Acts and Human Trafficking – Involuntary Servitude. These are the index crimes that are recorded in the chart provided.

**“Domestic offenses are defined as offenses committed between family or household members. Family or household members include spouses; former spouses; parents; children; foster parents; foster children; legal guardians and their wards; stepchildren; other persons related by blood (aunt, uncle, cousin) or by present or previous marriage (in-laws); persons who share, or formerly shared, a common dwelling; persons who have, or allegedly have, a child in common; persons who share, or allegedly share, a blood relationship through a child; persons who have, or have had, a dating or engagement relationship; and persons with disabilities, their personal care assistants, or care givers outside the context of an employee of a public or private care facility. Every offense that occurs, when a domestic relationship exists between the victim and offender, must be reported (Illinois State Police).”

**“Offenses reported are not limited to domestic battery and violations of orders of protection; offenses most commonly associated with domestic violence (Illinois State Police).”

The crime rate was compiled using the total population, and the index crime. The Index crime whether all crime or Domestic Violence crime was divided by the total population then multiplied by 10,000, hence crime rate per 10,000.

The sources of data are the Illinois Uniform Crime Reporting Program and the U.S. Census Bureau.

The source of the description is the Illinois State Police and their Reporting guidelines and forms.

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.

This dataset reports National Incident Based Reporting System (NIBRS) crime statistics from most Washington law enforcement agencies since 2016. The data is a "shapshot" of crime statistics as they were originally reported to the Washington Association of Sheriffs and Police Chiefs (WASPC) and the FBI. Data displayed should not be compared to statistics reported by the FBI as those statistics have been converted to the Summary Reporting System (SRS).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This project had three goals. One, to provide a more detailed description of injury evidence and biological evidence in sexual assault cases, including their timing relative to arrests. A second goal was to examine the relationship of forensic evidence to arrests. A third goal was to examine injury evidence and biological evidence in certain types of cases in which it may have had greater impact. To achieve these goals, the researchers created analysis data files that merged data from the Massachusetts Provided Sexual Crime Report, forensic evidence data from the two crime laboratories serving the state and data on arrests and criminal charges from 140 different police agencies.

This study offers novel insights into mechanisms associated with sexual assault (SA) among sexual minority women (SMW). Experiences of bias and stigma contribute to lower rates of SA reporting by this population. This results in victims with unmet needs and fewer criminal prosecutions of SA perpetrators. This study used a mixed-methods approach to collect data from lesbian, bisexual, and heterosexual women to instigate changes that would improve responses from law enforcement, victim services, and anti-violence programs that serve SMW. This study comprised of three parts a: baseline survey, qualitative interview, and daily survey. Self-reported baseline questionnaires included topics like lifetime victimization (childhood sexual abuse, adult sexual aggression, and assault), discrimination, distress, mental health, alcohol use, and sexual history. The qualitative interviews focused on the most recent, and when applicable, the most salient adult sexual assault (ASA) incident. Interviews began by asking the participants to describe their ASA incidents with follow-probes asking about the victimization, perpetrator characteristics (gender and relationship to participant), and context of assault (role of alcohol or drugs and setting). Participants were also asked if they discussed the assault with anyone and their reasons for disclosure or non-disclosure. As well as short and long-term coping patterns. The daily survey asked participants about their mood, alcohol use, drinking contexts, and sexual experiences (consensual and non-consensual). This study contains demographic information such as: age, race, income, education, and BMI.

Despite the fact that most states enacted rape reform legislation by the mid-1980s, empirical research on the effect of these laws was conducted in only four states and for a limited time span following the reform. The purpose of this study was to provide both increased breadth and depth of information about the effect of the rape law changes and the legal issues that surround them. Statistical data on all rape cases between 1970 and 1985 in Atlanta, Chicago, Detroit, Houston, Philadelphia, and Washington, DC, were collected from court records. Monthly time-series analyses were used to assess the impact of the reforms on rape reporting, indictments, convictions, incarcerations, and sentences. The study also sought to determine if particular changes, or particular combinations of changes, affected the case processing and disposition of sexual assault cases and whether the effect of the reforms varied with the comprehensiveness of the changes. In each jurisdiction, data were collected on all forcible rape cases for which an indictment or information was filed. In addition to forcible rape, other felony sexual assaults that did not involve children were included. The names and definitions of these crimes varied from jurisdiction to jurisdiction. To compare the pattern of rape reports with general crime trends, reports of robbery and felony assaults during the same general time period were also obtained from the Uniform Crime Reports (UCR) from the Federal Bureau of Investigation when available. For the adjudicated case data (Parts 1, 3, 5, 7, 9, and 11), variables include month and year of offense, indictment, disposition, four most serious offenses charged, total number of charges indicted, four most serious conviction charges, total number of conviction charges, type of disposition, type of sentence, and maximum jail or prison sentence. The time series data (Parts 2, 4, 6, 8, 10, and 12) provide year and month of indictment, total indictments for rape only and for all sex offenses, total convictions and incarcerations for all rape cases in the month, for those on the original rape charge, for all sex offenses in the month, and for those on the original sex offense charge, percents for each indictment, conviction, and incarceration category, the average maximum sentence for each incarceration category, and total police reports of forcible rape in the month. Interviews were also conducted in each site with judges, prosecutors, and defense attorneys, and this information is presented in Part 13. These interviewees were asked to rate the importance of various types of evidence in sexual assault cases and to respond to a series of six hypothetical cases in which evidence of the victim's past sexual history was at issue. Respondents were also presented with a hypothetical case for which some factors were varied to create 12 different scenarios, and they were asked to make a set of judgments about each. Interview data also include respondent's title, sex, race, age, number of years in office, and whether the respondent was in office before and/or after the reform.

The SGBV & Dynamics of Conflict dataset is comprised of SGBV reports for seven conflict-affected country cases, allowing the study to meet the following criteria: 1) representation of the five different types of conflict; 2) cases in the top 20 for conflict deaths/attacks during the 2010–2020 period and, 3) inclusion of cases from different global regions (Asia, Latin America, Africa and the Middle East).Using the codebook on this page, SGBV reports are analysed across three years in each of the following countries: Central African Republic (one-sided [rebel-led] violence), Colombia (state-based violence), Myanmar (one-sided [state-led] violence), Nigeria (terrorism), Philippines (one-sided violence [terrorism]), South Sudan (fragile), and Syria (non-state-based and state-based violence).Data is collected from the content of open-source reports, both official (government and inter-governmental) and unofficial (non-governmental and media) following guidance of the Office of the ICC Prosecutor (2014: 22) and the Office of the High Commissioner for Human Rights (OHCHR 2014a) on the sources of information that may be taken into account and designated as official (government and international organization reports) versus unofficial (media and civil society or non-government organization reports) when building a profile of SGBV reports.A report is coded when at least one listed SGBV crime is mentioned. Two sources were used to collect reports: the UN document reference site UNHCR RefWorld; and Factiva, a DowJones news aggregator site. We specifically code a report in RefWorld when any of the words ‘rape raping raped rapes gender sexual’ were mentioned and in Factiva with the code work ‘sex crimes’.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study includes data collected with the purpose of creating an integrated dataset that would allow researchers to address significant, policy-relevant gaps in the literature--those that are best answered with cross-jurisdictional data representing a wide array of economic and social factors. The research addressed five research questions: What is the impact of gentrification and suburban diversification on crime within and across jurisdictional boundaries? How does crime cluster along and around transportation networks and hubs in relation to other characteristics of the social and physical environment? What is the distribution of criminal justice-supervised populations in relation to services they must access to fulfill their conditions of supervision? What are the relationships among offenders, victims, and crimes across jurisdictional boundaries? What is the increased predictive power of simulation models that employ cross-jurisdictional data?

***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.

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This dataset represents the concatenated version of the NCVS on a collection year basis for 1992-2018. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred. For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 37297.

Note: Due to the RMS change for CPS, this data set stops on 6/2/2024. For records beginning on 6/3/2024, please see the dataset at this link: https://data.cincinnati-oh.gov/safety/Reported-Crime-STARS-Category-Offenses-/7aqy-xrv9/about_data

The combined data will be available by 3/10/2025 at the linke above.

Data Description: This data represents reported Crime Incidents in the City of Cincinnati. Incidents are the records, of reported crimes, collated by an agency for management. Incidents are typically housed in a Records Management System (RMS) that stores agency-wide data about law enforcement operations. This does not include police calls for service, arrest information, final case determination, or any other incident outcome data.

Data Creation: The Cincinnati Police Department's (CPD) records crime incidents in the City through Records Management System (RMS) that stores agency-wide data about law enforcement operations.

Data Created By: The source of this data is the Cincinnati Police Department.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/8eaa-xrvz

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

This site is part of a network of digital infrastructure built by Code for Africa (CfA) as a free open source software for use by human rights defending organisations. Reuse it to empower your own communities. CfA is Africa's largest non-profit civic technology and open data catalyst, with labs across the continent. CfA content on this site is released under a Creative Commons 4.0 International License. Refer to our attributions page for attributions of other work on the site.

Context

Introduction: The dataset used for this experiment is real and authentic. The dataset is acquired from UCI machine learning repository website [13]. The title of the dataset is ‘Crime and Communities’. It is prepared using real data from socio-economic data from 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crimedata from the 1995 FBI UCR [13]. This dataset contains a total number of 147 attributes and 2216 instances.

The per capita crimes variables were calculated using population values included in the 1995 FBI data (which differ from the 1990 Census values).

Content

The variables included in the dataset involve the community, such as the percent of the population considered urban, and the median family income, and involving law enforcement, such as per capita number of police officers, and percent of officers assigned to drug units. The crime attributes (N=18) that could be predicted are the 8 crimes considered 'Index Crimes' by the FBI)(Murders, Rape, Robbery, .... ), per capita (actually per 100,000 population) versions of each, and Per Capita Violent Crimes and Per Capita Nonviolent Crimes)

predictive variables : 125 non-predictive variables : 4 potential goal/response variables : 18

Acknowledgements

http://archive.ics.uci.edu/ml/datasets/Communities%20and%20Crime%20Unnormalized

U. S. Department of Commerce, Bureau of the Census, Census Of Population And Housing 1990 United States: Summary Tape File 1a & 3a (Computer Files),

U.S. Department Of Commerce, Bureau Of The Census Producer, Washington, DC and Inter-university Consortium for Political and Social Research Ann Arbor, Michigan. (1992)

U.S. Department of Justice, Bureau of Justice Statistics, Law Enforcement Management And Administrative Statistics (Computer File) U.S. Department Of Commerce, Bureau Of The Census Producer, Washington, DC and Inter-university Consortium for Political and Social Research Ann Arbor, Michigan. (1992)

U.S. Department of Justice, Federal Bureau of Investigation, Crime in the United States (Computer File) (1995)

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Data available in the dataset may not act as a complete source of information for identifying factors that contribute to more violent and non-violent crimes as many relevant factors may still be missing.

However, I would like to try and answer the following questions answered.

1. Analyze if number of vacant and occupied houses and the period of time the houses were vacant had contributed to any significant change in violent and non-violent crime rates in communities

2. How has unemployment changed crime rate(violent and non-violent) in the communities?

3. Were people from a particular age group more vulnerable to crime?

4. Does ethnicity play a role in crime rate?

5. Has education played a role in bringing down the crime rate?