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.

***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.

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.

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.

Disclaimer: Crime Responses is provided by the Gainesville Police Department (GPD) to document initial details surrounding an incident to which GPD officers respond. This dataset contains crime incidents from 2011 to present and includes a reduced set of fields focused on capturing the type of incident as well when and where an incident occurred. The Incident location addresses have been rounded off and are not the exact location due to the constitutional amendment known as "Marsy's Law".

In 2021, Florida reporting of crime data began a transition from Summary Reporting System (SRS) to National Incident-Based Reporting System (NIBRS), causing an effect on crime statistics reported by Law Enforcement Agencies such as the Gainesville Police Department who made this transition on November 16, 2021. The effect would be an increase in crime due to the elimination of the SRS Hierarchy Rule which collected only the most serious offense in an incident while NIBRS will now capture up to 10 offenses per incident and specifies more offense categories than SRS. The inclusion of these crimes, particularly property crimes, will reflect an increase in crime when switching from SRS reporting to NIBRS' reporting. The apparent increase (usually not greater than 2.7%) is simply due to the difference between how crimes are counted in NIBRS versus the SRS and its application of the Hierarchy Rule. More information regarding NIBRS effect on crime statistics can be found on the following link: https://ucr.fbi.gov/nibrs/2014/resource-pages/effects_of_nibrs_on_crime_statistics_final.pdf.

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.

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 (2017). For additional details, please see the attached data dictionary in the ‘About’ section.

Gain critical insights into crime trends, risk assessment, and public safety with our comprehensive Crime Dataset. Designed for law enforcement agencies, researchers, and analysts, this dataset provides structured and reliable crime data to support investigations, policy-making, and crime prevention strategies.

Dataset Features

Crime Reports: Access detailed records of reported crimes, including incident type, date, time, and location. Law Enforcement Data: Extract information on arrests, case statuses, and law enforcement responses. Geospatial Crime Mapping: Analyze crime distribution across different regions, cities, and neighborhoods. Trends & Patterns: Identify crime trends over time, including seasonal fluctuations and high-risk areas. Demographic Insights: Understand crime demographics, including offender and victim profiles.

Customizable Subsets for Specific Needs Our Crime Dataset is fully customizable, allowing you to filter data based on crime type, location, time period, or law enforcement jurisdiction. Whether you need broad coverage for national crime analysis or focused data for local risk assessment, we tailor the dataset to your needs.

Popular Use Cases

Crime Risk Assessment & Prevention: Identify high-crime areas, assess risk factors, and develop crime prevention strategies. Law Enforcement & Investigations: Support law enforcement agencies with structured crime data for case analysis and intelligence gathering. Urban Planning & Public Safety: Use crime data to inform city planning, improve public safety measures, and allocate resources effectively. AI & Predictive Analytics: Train AI models for crime forecasting, anomaly detection, and predictive policing. Policy & Legal Research: Analyze crime trends to support policy-making, legal studies, and criminal justice reforms.

Whether you're analyzing crime trends, supporting law enforcement, or developing predictive models, our Crime Dataset provides the structured data you need. Get started today and customize your dataset to fit your research and security objectives.

***In January 2020, as part of implementing a new citywide police incident reporting system the City began moving away from reporting crime to the FBI Unified Crime Reporting (UCR) Program and instead to the new National Incident-Based Reporting System (NIBRS) format. For this reason, 2020 UCR data may have inconsistencies and/or inaccuracies. A filtered view of UCR data is available for 2011-2019 at https://citydata.mesaaz.gov/Police/Crime-Reporting-Statistics-Uniform-Crime-Reporting/bfen-qa5d

As of January 1, 2021, the National Incident-Based Reporting System (NIBRS) became the national crime data collection program. NIBRS was implemented to improve the overall quality of crime data collected by law enforcement, by capturing details on each single crime incident, as well as on separate offenses within the same incident. The historic Summary Reporting System (SRS) data collection, which collects more limited information than the more robust NIBRS, was phased out to make Uniform Crime Reporting (UCR) a NIBRS-only data collection.

Coming soon, look for a new dataset based on NIBRS, which will provide more complete and comprehensive data for law enforcement, researchers, and the public.

The Uniform Crime Reporting Program collects statistics on the number of offenses known to City of Mesa Police Department. Address and Location data are not exact location of incidents and have been rounded to nearest hundred block. Lat/Long are approximations only based on rounded hundred block. Part 1 offenses are reported monthly and are chosen by the Federal Bureau of Investigation (FBI) because they are serious crimes, they occur with regularity in all areas of the country, and they are likely to be reported to police. Part I offenses are defined as: Criminal homicide, Forcible Rape, Robbery, Aggravated Assault, Burglary (breaking or entering), Larceny-theft (except motor vehicle theft), Motor vehicle theft and Arson.

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.

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 communitycrimemap.comData Dictionary:

Field Name

Field Description

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 Occurred

the date the incident actually occurred

Badge ID

Badge ID of responding Officer

Offense Classification

NIBRS Reporting category for the criminal act committed

Offense Code Name

NIBRS Reporting code for the criminal act committed

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

NIBRS Group

hierarchy that follows the guidelines of the FBI National Incident Based Reporting System

Was Offense Completed

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

Location Category

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

Contact:LMPD Open Records lmpdopenrecords@louisvilleky.gov

Context

From 1934 to 1963, San Francisco was infamous for housing some of the world's most notorious criminals on the inescapable island of Alcatraz. Today, the city is known more for its tech scene than its criminal past. But, with rising wealth inequality, housing shortages, and a proliferation of expensive digital toys riding BART to work, there is no scarcity of crime in the city by the bay. From Sunset to SOMA, and Marina to Excelsior, this dataset provides nearly 12 years of crime reports from across all of San Francisco's neighborhoods.

This dataset was featured in our completed playground competition entitled San Francisco Crime Classification. The goals of the competition were to:

• predict the category of crime that occurred, given the time and location

• visualize the city and crimes (see Mapping and Visualizing Violent Crime for inspiration)

Content

This dataset contains incidents derived from SFPD Crime Incident Reporting system. The data ranges from 1/1/2003 to 5/13/2015. The training set and test set rotate every week, meaning week 1,3,5,7... belong to test set, week 2,4,6,8 belong to training set. There are 9 variables:

• Dates - timestamp of the crime incident

• Category - category of the crime incident (only in train.csv).

• Descript - detailed description of the crime incident (only in train.csv)

• DayOfWeek - the day of the week

• PdDistrict - name of the Police Department District

• Resolution - how the crime incident was resolved (only in train.csv)

• Address - the approximate street address of the crime incident

• X - Longitude

• Y - Latitude

Acknowledgements

This dataset is part of our completed playground competition entitled San Francisco Crime Classification. Visit the competition page if you are interested in checking out past discussions, competition leaderboard, or more details regarding the competition. If you are curious to see how your results rank compared to others', you can still make a submission at the competition submission page!

The original dataset is from SF OpenData, the central clearinghouse for data published by the City and County of San Francisco.

In 2023, murder and manslaughter charges had the highest crime clearance rate in the United States, with 57.8 percent of all cases being cleared by arrest or so-called exceptional means. Motor vehicle theft cases had the lowest crime clearance rate, at 8.2 percent. What is crime clearance? Within the U.S. criminal justice system, criminal cases can be cleared (or closed) one of two ways. The first is through arrest, which means that at least one person has either been arrested, charged with an offense, or turned over to the court for prosecution. The second way a case can be closed is through what is called exceptional means, where law enforcement must have either identified the offender, gathered enough evidence to arrest, charge, and prosecute someone, identified the offender’s exact location, or come up against a circumstance outside the control of law enforcement that keeps them from arresting and prosecuting the offender. Crime in the United States Despite what many people may believe, crime in the United States has been on the decline. Particularly in regard to violent crime, the violent crime rate has almost halved since 1990, meaning that the U.S. is safer than it was almost 30 years ago. However, due to the FBI's recent transition to a new crime reporting system in which law enforcement agencies voluntarily report crime data, it is possible that figures do not accurately reflect the total amount of crime in the country.

To estimate national trends of crime, the FBI collects crime reports from law enforcement agencies across the country. In 2022, Delaware, the District of Columbia, and Oklahoma had perfect participation rates, with 100 percent of law enforcement agencies reporting crime data to the FBI in those states. In contrast, the state of Florida had the lowest share of law enforcement agencies who reported crime data to the FBI in the United States, at *** percent. An unreliable source? Along with being the principal investigative agency of the U.S. federal government, the FBI is also in charge of tracking crimes committed in the United States. In recent years, however, the FBI made significant changes to their crime reporting system, requiring a more detailed input on how agencies report their data. Consequently, less crime data has been reported and the FBI has come under criticism as an unreliable source on crime in the United States. In 2022, the FBI was found to rank low on trustworthiness for Americans when compared to other government agencies, further demonstrating the need for transparent and accurate data. Importance of crime rates As crime and policing data can help to analyze emerging issues and policy responses, the inaccuracy of the FBI’s crime reporting system may lead to misinformation which could be used to impact elections and the beliefs of the American public. In addition, the lack of crime data from Republican states such as Florida may prove problematic as 78 percent of Republicans said that crime was a very important issue for them in midterm elections.

The National Crime Victimization Survey (NCVS) Series, previously called the National Crime Surveys (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. The survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual attack, 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 version of the NCVS, referred to as the collection year, contains records from interviews conducted in the 12 months of the given year.

This dataset reflects incidents of crime in the City of Los Angeles from 2010 - 2019. 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 global crime analytics software market is expected to grow at CAGR of 8.2% for the forecast period 2023-2030.

Growing demand for effective crime prevention and reduction techniques due to rising crime rate is expected to drive the growth of the crime analytics software market
North America dominates the crime analytics software market

Factors Affecting Crime Analytics Software Market Growth

Growing demand for effective crime prevention and reduction techniques due to rising crime rate; 

The increasing crime rates and growing demand for effective crime prevention and reduction techniques primarily drives the demand for crime analytics software. In recent years, the rise in crime rates has become a major concern for many countries around the world. Murder cases, terrorism, cybercrime has increases drastically in in last few years due to the growing inflation and unemployment. With the development of online and mobile technologies, cybercrime is becoming more and more common. According to the study, about 40% of internet users worldwide experienced cybercrime in 2022. As crime rates increase, law enforcement agencies and other organizations recognize the need to make informed decisions based on data. Traditional reactive policing methods are often insufficient to address rising crime rates due to improper recording of data and information. In such cases, crime analytics software helps to collect, analyse, and visualize crime-related data, enabling law enforcement professionals to understand crime patterns, allocate resources, and develop targeted strategies.

In 2021, a total of 60,96,310 crimes, comprising 36,63,360 Indian Penal Code (IPC) crimes and 24,32,950 Special and Local Laws (SLL) crimes were registered in India.

(Source: Crime in India - Wikipedia)

In a report released in July 2023, Statistics Canada researchers found that violent crime rose by five per cent in 2022, reaching its highest point since 2007.

(Source: Police-reported crime is on the rise again, with violent crime at its highest since 2007 | CBC News)

Crime Analytics Software Market Restraint:

Budgetary restrictions faced by law enforcement organizations.

Crime analytics software often requires initial investment for licensing, infrastructure, and training. Law enforcement agencies with tight budgets might find it difficult to allocate funds for such expenses, leading to hesitation in adopting these solutions. Besides the initiation cost, crime analytics software also requires technology upgrades and software purchases. This might hamper the adoption of crime analytics software in police stations and investigation agencies.

Crime Analytics Software Market Opportunity:

Technology development as an opportunity for the market.

New technological innovations have been developed to prevent crime and to improve the performance of the police. Innovations in criminal justice technology can be categorised into hard technology comprises hardware & components, and soft technology includes computer software, information systems, etc. With the adoption of different hardware such as CCTV cameras, metal detectors, bulletproof teller windows, security systems encourage the crime analytics software.

On June 2023, Google Cloud has announced the launch of Anti Money Laundering AI (AML AI), an artificial intelligence (AI)-powered product designed to help global financial institutions more effectively and efficiently detect money laundering.

(Source: Google Cloud Launches AI-Powered Anti Money Laundering Product for Financial Institutions (prnewswire.com))

The COVID-19 impact on the Crime Analytics Software Market.

The COVID-19 pandemic has had a significant impact on the crime analytics software market, resulting in both challenges and opportunities for the industry. The most immediate impact of the pandemic was the widespread imposition of travel restrictions, lockdowns, and quarantines. Due to the lockdowns, social distancing measures, and changes in daily routines, the burglary and street-level crimes have noticed some reduction. Crime analytics software would have been crucial in identifying and analysing these shifts. Remote work became essential during the pandemic, including for law enforcement agencies. Crime analytics software that could be accessed and operated remotely gained importance, allowing personnel to analyse data...

Context

Approximately 10 people are shot on an average day in Chicago.

http://www.chicagotribune.com/news/data/ct-shooting-victims-map-charts-htmlstory.html http://www.chicagotribune.com/news/local/breaking/ct-chicago-homicides-data-tracker-htmlstory.html http://www.chicagotribune.com/news/local/breaking/ct-homicide-victims-2017-htmlstory.html

Content

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. This data includes unverified reports supplied to the Police Department. 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.

Update Frequency: Daily

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:chicago_crime

https://cloud.google.com/bigquery/public-data/chicago-crime-data

Dataset Source: City of Chicago

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source —https://data.cityofchicago.org — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Ferdinand Stohr from Unplash.

Inspiration

What categories of crime exhibited the greatest year-over-year increase between 2015 and 2016?

Which month generally has the greatest number of motor vehicle thefts?

How does temperature affect the incident rate of violent crime (assault or battery)?

https://cloud.google.com/bigquery/images/chicago-scatter.png" alt=""> https://cloud.google.com/bigquery/images/chicago-scatter.png