In 2023, ********* property and violent crimes were reported in California - the most out of any state. Texas followed behind, with ******* reported crimes. However, as the FBI estimates national trends of crime by asking law enforcement agencies across the country to self-report their crime data, the reported number of crimes committed in each state is dependent upon whether they provided the information to the Bureau's crime reporting system. For example, the state of Florida reported only *** percent of their crime data in 2022, raising the question of whether Florida has again failed to report the majority of their crimes in 2023 and if they should be higher up on this list. As many states have neglected to report all of their crime data to the FBI in the last few years, the total numbers may not accurately represent the number of crimes committed in each state.

In 2023, property crime was the most common type of crime committed in the United States, with over 6.41 million offenses reported to the FBI. In the same year, there were around 1.22 million cases of violent crime reported to the FBI, of which there were 19,252 cases of homicide, including murder and nonnegligent manslaughter.

***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.

In 2023, a total of ******* violent crimes were committed in Texas, the most out of any U.S. state. New York followed, with ******* violent crimes committed. California, Illinois, and Michigan rounded out the top five states for violent crimes in that year.

The dataset contains year-, state-, type-of-crime- and gender-wise compiled data on the number of different types of crimes which were committed against children and the number of victims who were affected by the same crimes. The different types of crimes covered in the dataset include kidnapping and abduction crimes such as kidanapping and abduction for the purpose of murder, begging, ransom, compelling for marriage, procuration of minor girls, importation of girls from foreign countries, missing deemed as kidnapped, etc., fatal crimes such as murder, attempt to commit murder, muder with rape, abetment of suicide of child, infanticide, foeticide, trafficking and sexual crimes such buying and selling of minors for prostitution, use of children for pornography, transmiting sexual content and material involving children in sexually explicit acts, sexual assualt, penetrative sexual assault, rape, and other crimes such as child labour, child marriage, exposure, abandaonment, simple hurt, grievous hurt, insult and assualt of damage modesty, crimes under juvenile justice act and transplantation of organs act, etc.

In 2023, the violent crime rate in the United States was 363.8 cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. In addition, due to the FBI's transition to a new crime reporting system in which law enforcement agencies voluntarily submit crime reports, data may not accurately reflect the total number of crimes committed in recent years. Reported violent crime rate in the United States The United States Federal Bureau of Investigation tracks the rate of reported violent crimes per 100,000 U.S. inhabitants. In the timeline above, rates are shown starting in 1990. The rate of reported violent crime has fallen since a high of 758.20 reported crimes in 1991 to a low of 363.6 reported violent crimes in 2014. In 2023, there were around 1.22 million violent crimes reported to the FBI in the United States. This number can be compared to the total number of property crimes, roughly 6.41 million that year. Of violent crimes in 2023, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Law enforcement officers and crime clearance Though the violent crime rate was down in 2013, the number of law enforcement officers also fell. Between 2005 and 2009, the number of law enforcement officers in the United States rose from around 673,100 to 708,800. However, since 2009, the number of officers fell to a low of 626,900 officers in 2013. The number of law enforcement officers has since grown, reaching 720,652 in 2023. In 2023, the crime clearance rate in the U.S. was highest for murder and non-negligent manslaughter charges, with around 57.8 percent of murders being solved by investigators and a suspect being charged with the crime. Additionally, roughly 46.1 percent of aggravated assaults were cleared in that year. A statistics report on violent crime in the U.S. can be found here.

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.

The UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2012 dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.

The study contains cross-section data on the relationship between aggregate levels of punishment and crime rates. It examines deterrent effects of punishment on seven Federal Bureau of Investigation (FBI) index crimes: murder, rape, assault, larceny, robbery, burglary, and auto theft, committed in 1960 in 47 states of the United States (excluded were New Jersey, Alaska, and Hawaii). For each state, the data include variables for the reported crime rates for each of the seven index crimes. For each of the index crimes, there are two sanction variables included: the probability of prison commitment and the average time served by those sentenced (severity of punishment). There are 11 socioeconomic variables, including family income, income distribution, unemployment rate for urban males in the age groups 14-24 and 35-39, labor force participation rate, educational level, percentage of young males in population, percentage of non-white young males living in the population, percentage of population living in Standard Metropolitan Statistical Areas, sex ratio, and place of occurrence. The data also include per capita police expenditures for 1959 and 1960. A related data collection is PARTICIPATION IN ILLEGITIMATE ACTIVITIES: EHRLICH REVISITED, 1960 (ICPSR 8677). It provides alternative model specifications and estimations.

Note: Due to a system migration, this data will cease to update on March 14th, 2023. The current projection is to restart the updates within 30 days of the system migration, on or around April 13th, 2023Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities. The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics. Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred). Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained. Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.com Data Dictionary: INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence rooms DATE_REPORTED - the date the incident was reported to LMPD DATE_OCCURED - the date the incident actually occurred BADGE_ID - UOR_DESC - Uniform Offense Reporting code for the criminal act committed CRIME_TYPE - the crime type category NIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/view UCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime. LMPD_DIVISION - the LMPD division in which the incident actually occurred LMPD_BEAT - the LMPD beat in which the incident actually occurred PREMISE_TYPE - the type of _location in which the incident occurred (e.g. Restaurant) BLOCK_ADDRESS - the _location the incident occurred CITY - the city associated to the incident block _location ZIP_CODE - the zip code associated to the incident block _location ID - Unique identifier for internal database Contact: Crime Information Center CrimeInfoCenterDL@louisvilleky.gov

India crime rate per 100K population for 2021 was 2.94, a 0.86% increase from 2020.

<ul style='margin-top:20px;'>

<li>India crime rate per 100K population for 2020 was <strong>2.91</strong>, a <strong>0.53% decline</strong> from 2019.</li>
<li>India crime rate per 100K population for 2019 was <strong>2.93</strong>, a <strong>2.24% decline</strong> from 2018.</li>
<li>India crime rate per 100K population for 2018 was <strong>2.99</strong>, a <strong>1.16% decline</strong> from 2017.</li>
</ul>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.

For this data collection, offenders confined to prison were surveyed to examine the utility of deterrence theory variables as predictors of differential desistance from serious property crimes. The investigators also examined subjects' "criminal calculus," that is, their expectations of the likely gains and losses of further criminal behavior and the conditions under which they likely would commit further crimes. Specifically, the data explored whether decisions to commit crime are based on assessment of potential returns from alternate courses of action and the risk of legal sanctions. Sixty repeat offenders who had served one or more prison sentences were asked about their history of criminal activity, reasons for committing crimes, expectations of future criminal activities, and likely consequences of committing crimes. Data were collected in pre-release interviews in 1987 and 1988 as part of a larger study. Variables include age, education, age at first arrest, alcohol and drug use as a juvenile, as a young adult, and as a mature adult, past crimes, willingness to commit specific property crimes, reasons for being willing or unwilling to commit specific property crimes, expectations of arrest subsequent to actual crimes committed, and the likelihood of future criminal activity.

Suburb-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to police in that respective financial year. The Family and Domestic Abuse-related offences datasets are a subset of this, in that a separate file is presented for these offences that were flagged as being of a family and domestic abuse nature for that financial year. Consequently the two files for the same financial year must not be added together.

Chicago Crime Incident Data

65,000+ Records of Arrests, Locations, and Descriptions

By City of Chicago [source]

About this dataset

This dataset is a compilation of reported crimes that have taken place in the City of Chicago over the past year, and provides an invaluable insight into the criminal activity occurring within our city. Featuring more than 65,000 records of data, it contains information on the date of each incident, its location (down to the block level), type of crime committed (determined by FBI Crime Classification Codes) and whether or not an arrest has been made in connection with each crime. As this dataset reveals detailed information on crime incidents which may lead to personal identification, addresses are masked beyond block level and specific locations are not disclosed.

For additional questions regarding this dataset, please do not hesitate to reach out to The Research & Development Division at 312.745.6071 or RandDchicagopolice.com who will be more than happy to help answer any inquiries you may have about our data findings! All visualized maps should be considered approximate however—it is prohibited for any attempts to derive specific addresses from them as accuracy cannot be guaranteed with regards to mechanical or human error when collecting this data over time. So come join us as we explore a year's worth of criminal activities throughout Chicago!

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How to use the dataset

This guide will provide an overview on how to use this dataset to analyze patterns or draw conclusions about crime incidents in and around Chicago.

Secondly, become familiar with columns names which appear at top most row of your opened file which helps you understand what kind of data is stored at each column such as - CASE# - Unique identifier for the crime incident., DATE OF OCCURRENCE - Date when crime incident occurred , BLOCK - Block where event took place , LOCATION DESCRIPTION- Description of location where incident happened . Through these columns name you can easily recognize what kind of data exists within that record/row. That’s why it’s important to get familiar with them first before diving into raw datasets because they’ll help make exploring and understanding large sets easier later on when we go further into illustrating charts & graphs using programs such as Tableau & Power BI or even spreadsheets (Excel). After understanding column names its time to explore further by digging deeper into each record/row and apply filters if required e.g below $100 value will show only those rows having value less than 100 thus it will filter entire dataset according to your requirement. Lastly analyse collected datasets either Visually through plotting graphs with help tableau software OR By using Mathematical mathematical equations based on research questions such as finding out average values after applying sum/avg functions from respective cells etc

Research Ideas

• Creating a visualization mapping tool to help visualize the types of crimes and their locations over time within Chicago.
• An analysis tool for city officials or police departments so they can understand correlations between crime type, geography, and other factors like weather changes or economic downturns in order to develop long-term plans for crime prevention.
• Developing an AI model that would be able to predict what areas may be more vulnerable for certain types of crimes or even predict crimes ahead of time based on the data from this dataset

Acknowledgements

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

License

See the dataset description for more information.

Columns

File: crimes-one-year-prior-to-present-1.csv | Column name | Description | |:-------------------------|:------------------------------------------------------------------------------| | CASE# | Unique identifier for each crime incident (String) | | BLOCK | Block where the crime incident occurred (String) | | LOCATION DESCRIPTION | Description of where an incident took place (String) | | ARREST | Indicates if an arrest was made in connection with a crime incident (Boolean) | | DOMESTIC | Indicates if a reported incident is domestic related (Boolean) | | BEAT ...

There has been a surge in crimes committed in recent years, making crime a top cause of concern for law enforcement. If we are able to estimate whether someone is going to commit a crime in the future, we can take precautions and be prepared. You are given a dataset containing answers to various questions concerning the professional and private lives of several people. A few of them have been arrested for various small and large crimes in the past.The train data consists of 39999 rows, while the test data consists of 5710 rows.

The train data consists of 39999 rows, while the test data consists of 5710 rows.

Use the given data to predict if the people in the test data will commit a crime. You are given three files to download: train, test and sample submission. The evaluation metric is precision score.

Under New York State’s Hate Crime Law (Penal Law Article 485), a person commits a hate crime when one of a specified set of offenses is committed targeting a victim because of a perception or belief about their race, color, national origin, ancestry, gender, religion, religious practice, age, disability, or sexual orientation, or when such an act is committed as a result of that type of perception or belief. These types of crimes can target an individual, a group of individuals, or public or private property. DCJS submits hate crime incident data to the FBI’s Uniform Crime Reporting (UCR) Program. Information collected includes number of victims, number of offenders, type of bias motivation, and type of victim.

This project examined different aspects of campus crime -- specifically, the prevalence of crimes among college students, whether the crime rate was increasing or decreasing on college campuses, and the factors related to campus crime. Researchers made the assumption that crimes committed by and against college students were likely to be related to drug and alcohol use. Specific questions designed to be answered by the data include: (1) Do students who commit crimes differ in their use of drugs and alcohol from students who do not commit crimes? (2) Do students who are victims of crimes differ in their use of drugs and alcohol from students who are not victims? (3) How do multiple offenders differ from single offenders in their use of drugs and alcohol? (4) How do victims of violent crimes differ from victims of nonviolent crimes in their use of drugs and alcohol? (5) What types of student crimes are more strongly related to drug or alcohol use than others? (6) Other than drug and alcohol use, in what ways can victims and perpetrators of crimes be differentiated from students who have had no direct experiences with crime? Variables include basic demographic information, academic information, drug use information, and experiences with crime since becoming a student.

In 2023, an estimated 1,21,467 violent crimes occurred in the United States. This is a decrease from the year before, when 1,256,671 violent crimes were reported. Violent crime in the United States The Federal Bureau of Investigation reported that violent crime fell nationwide in the period from 1990 to 2023. Violent crime was at a height of 1.93 million crimes in 1992, but has since reached a low of 1.15 million violent crimes in 2014. When conducting crime reporting, the FBI’s Uniform Crime Reporting Program considered murder, nonnegligent manslaughter, forcible rape, robbery and aggravated assault to be violent crimes, because they are offenses which involve force or threat of violence. In 2023, there were 19,252 reported murder and nonnegligent manslaughter cases in the United States. California ranked first on a list of U.S. states by number of murders, followed by Texas, and Florida.The greatest number of murders were committed by murderers of unknown relationship to their victim. “Girlfriend” was the fourth most common relationship of victim to offender in 2023, with a reported 568 partners murdering their girlfriends that year, while the sixth most common was “wife.” In addition, seven people were murdered by their employees and 12 people were murdered by their employers. The most used murder weapon in 2023 was the handgun, which was used in 7,1 murders that year. According to the FBI, firearms (of all types) were used in more than half of the nation’s murders. The total number of firearms manufactured in the U.S. annually has reached over 13 million units.

Context

This dataset is an exported version of the Atlanta Crime Data Report, a dataset on crimes in the city of Atalanta, Georgia published by the city's police department.

Content

This data is regarding crime data from the City of Atlanta. This area contains weekly crime reports commanders use to best deploy Atlanta officers to combat crime. It also contains a raw crime data dump that is updated weekly. Crime data in this area is counted by incident in the area.

Acknowledgements

The original source for this dataset is located on the Atlanta PD website.

Inspiration

What can you learn about crime in Atlanta from this dataset? How does it compare to crimes committed in other cities with data on Kaggle, like New York City?

Incident-based crime statistics (actual incidents, rate per 100,000 population, percentage change in rate, unfounded incidents, percent unfounded, total cleared, cleared by charge, cleared otherwise, persons charged, adults charged, youth charged / not charged), by detailed violations (violent, property, traffic, drugs, other Federal Statutes), police services in Ontario, 1998 to 2023.