This data was obtained from https://mappingpoliceviolence.us/.

Mapping Police Violence is a 501(c)(3) organization that publishes the most comprehensive and up-to-date data on police violence in America to support transformative change.

This is a database set on openly sharing information on police violence in America.

Some information on this data according to their website: Our data has been meticulously sourced from official police use of force data collection programs in states like California, Texas and Virginia, combined with nationwide data from The Gun Violence Archive and the Fatal Encounters database, two impartial crowdsourced databases. We've also done extensive original research to further improve the quality and completeness of the data; searching social media, obituaries, criminal records databases, police reports and other sources to identify the race of 90 percent of all victims in the database.

We believe the data represented on this site is the most comprehensive accounting of people killed by police since 2013. Note that the Mapping Police Violence database is more comprehensive than the Washington Post police shootings database: while WaPo only tracks cases where people are fatally shot by on-duty police officers, our database includes additional incidents such as cases where police kill someone through use of a chokehold, baton, taser or other means as well as cases such as killings by off-duty police. A recent report from the Bureau of Justice Statistics estimated approximately 1,200 people were killed by police between June, 2015 and May, 2016. Our database identified 1,100 people killed by police over this time period. While there are undoubtedly police killings that are not included in our database (namely, those that go unreported by the media), these estimates suggest that our database captures 92% of the total number of police killings that have occurred since 2013. We hope these data will be used to provide greater transparency and accountability for police departments as part of the ongoing work to end police violence in America.

Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

This dataset, compiled by The Washington Post, logs every person shot and killed by an on-duty police officer in the United States from 2015 to 2024. Following the 2014 shooting of Michael Brown in Ferguson, it was discovered that FBI reports were significantly undercounted, with only a third of fatal shootings recorded by 2021. This comprehensive database aims to fill that gap and provide detailed information on each incident, including the police departments involved, to enhance accountability.

Version 3 release notes:

• Fix bug where Philadelphia Police Department had incorrect FIPS county code.

The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. Each data set contains over 2,200 columns and has a wealth of information about the circumstances of assaults on officers.

All the data was downloaded from NACJD as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. It was then cleaned in R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors).

About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself.

I did not make any changes to the numeric columns except for the following. A few years of data had the values "blank" or "missing" as indicators of missing values. Rows in otherwise numeric columns (e.g. jan_asslt_no_injury_knife) with these values were replaced with NA. There were three obvious data entry errors in officers killed by felony/accident that I changed to NA.

In 1978 the agency "pittsburgh" (ORI = PAPPD00) reported 576 officers killed by accident during March.
In 1979 the agency "metuchen" (ORI = NJ01210) reported 991 officers killed by felony during August.
In 1990 the agency "penobscot state police" (ORI = ME010SP) reported 860 officers killed by accident during July.

No other changes to numeric columns were made.

Each zip file contains all years as individual monthly files of the specified data type It also includes a file with all years aggregated yearly and stacked into a single data set. Please note that each monthly file is quite large (2,200+ columns) so it may take time to download the zip file and open each data file.

For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data.

The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:

"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety.

"... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."

If you have any questions, comments, or suggestions please contact me at jkkaplan6@gmail.com

Context

This dataset contains information about fatal shooting of civilians by police officers in the US since Jan 1st, 2015. The data about the shootings was collected by the Washington Post in their fatal police shootings dataset. The city locations were geocoded using OpenStreetMap Nominatim.

Content

fatal-police-shootings-data.csv contains information about each shooting. Each row is a shooting, and columns contain information about

• Name of the individual shot
• Date of the shooting
• Manner of death of the individual shot
• If and how the individual shot was armed
• Age of the individual shot
• Gender of the individual shot
• Race of the individual shot
• Whether the individual shot displayed signs of mental illness
• To what level the individual shot was attacking when shot
• If and how the individual shot was fleeing from police
• If an officer present for the shooting was wearing a body camera

CityLocations.csv contains the latitude and longitude for each city present in fatal-police-shootings-data.csv.

Acknowledgements and Licenses

The data in fatal-police-shootings-data.csv was collected by the Washington Post, and is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License.

The data in CityLocations.csv was geocoded using OpenStreetMap Nominatim, and is licensed under the Open Database License.

Cover image by Spenser.

Since 2013, protests opposing police violence against Black people have occurred across a number of American cities under the banner of “Black Lives Matter.” We develop a new dataset of Black Lives Matter protests that took place in 2014–2015 and explore the contexts in which they emerged. We find that Black Lives Matter protests are more likely to occur in localities where more Black people have previously been killed by police. We discuss the implications of our findings in light of the literature on the development of social movements and recent scholarship on the carceral state’s impact on political engagement.

DM-FS enables the bidirectional exploration of fatal encounters. In other words, it allows others to investigate how deaths in one group, officers, modulate deaths in another, fatally shot civilians and vice-versa Recommended Instructions First, click on the "Tree" button near the bold "Change View" text, underneath the "Files" tab. This will make the repository legible. Second, there are three folders listed below. Click on the folder whose contents you wish to access and download the corresponding database. Civilians. This folder contains DM-FS Civilians, a database that can enable the exploration of how a civilian’s death affects the number of officers that other civilians kill each year, and under which circumstances. Officers.This folder contains DM-FS Officers, a database that enables the exploration of how an officer’s death affects the number of civilians other officers fatally shoot each year, and under which circumstances. Technical Validation Tables. This folder contains the various technical validation tables that appear in the DM-FS data descriptor. For most users, we recommend (i) reading the codebook and (ii) downloading the cleaned version of DM-FS. For more advanced users who wish to customize the database and apply their own filtering, we recommend downloading the full database. Changelog DM-FS will be updated with additional information, such as additional years or databases. Any additions or changes to the database will appear in the text below. ************************* Version 1.0 January 16, 2025 ************************* This post represents the launch of the first full version of DM-FS. The version of DM-FS that appears below is therefore an exact copy of the one described in the Scientific Data dataset descriptor.

A geographically-resolved, multi-level Bayesian model is used to analyze the data presented in the U.S. Police-Shooting Database (USPSD) in order to investigate the extent of racial bias in the shooting of American civilians by police officers in recent years. In contrast to previous work that relied on the FBI’s Supplemental Homicide Reports that were constructed from self-reported cases of police-involved homicide, this data set is less likely to be biased by police reporting practices. County-specific relative risk outcomes of being shot by police are estimated as a function of the interaction of: 1) whether suspects/civilians were armed or unarmed, and 2) the race/ethnicity of the suspects/civilians. The results provide evidence of a significant bias in the killing of unarmed black Americans relative to unarmed white Americans, in that the probability of being {black, unarmed, and shot by police} is about 3.49 times the probability of being {white, unarmed, and shot by police} on average. Furthermore, the results of multi-level modeling show that there exists significant heterogeneity across counties in the extent of racial bias in police shootings, with some counties showing relative risk ratios of 20 to 1 or more. Finally, analysis of police shooting data as a function of county-level predictors suggests that racial bias in police shootings is most likely to emerge in police departments in larger metropolitan counties with low median incomes and a sizable portion of black residents, especially when there is high financial inequality in that county. There is no relationship between county-level racial bias in police shootings and crime rates (even race-specific crime rates), meaning that the racial bias observed in police shootings in this data set is not explainable as a response to local-level crime rates.

This study looks at the impact of police departments' organizational and managerial characteristics on police-community relations. Particular attention is paid to communities of color in the analysis. The dataset merges variables from various data sources. These include the following series housed within ICPSR: Two sub-series within the The Uniform Crime Reporting Program Data Series: Law Enforcement Officers Killed and Assaulted (LEOKA), and Offenses Known and Clearances by Arrest The Law Enforcement Management and Administrative Statistics (LEMAS) Series Additionally, the following sources are also contained in the final dataset and available online: The Fatal Encounters and Police Violence Project, both of which track the number of people killed by police. The American Community Survey, which is conducted by the U.S. Census Bureau. Variables include officer counts, demographics, weapons used, technologies, duties performed, salary figures, department units, qualifications, training structure, budgets, states, and addresses by department. Total crimes for each jurisdiction are collected. The presence of officer foot patrols, civilian review boards, and other community policing initiatives are measured. Violence committed against officers and civilians are included. Demographic variables of residents of jurisdictions including poverty, housing status, race, marital status are collected as well.

About this dataset

The Washington Post compiled a dataset of every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

In 2015, The Post began tracking more than a dozen details about each killing by culling local news reports, law enforcement websites and social media and by monitoring independent databases such as Killed by Police and Fatal Encounters. The available features are: - Race of the deceased; - Circumstances of the shooting; - Whether the person was armed; - Whether the victim was experiencing a mental-health crisis; - Among others.

In 2016, The Post is gathering additional information about each fatal shooting that occurs this year and is filing open-records requests with departments. More than a dozen additional details are being collected about officers in each shooting.

The Post is documenting only those shootings in which a police officer, in the line of duty, shot and killed a civilian — the circumstances that most closely parallel the 2014 killing of Michael Brown in Ferguson, Mo., which began the protest movement culminating in Black Lives Matter and an increased focus on police accountability nationwide. The Post is not tracking deaths of people in police custody, fatal shootings by off-duty officers or non-shooting deaths.

The FBI and the Centers for Disease Control and Prevention log fatal shootings by police, but officials acknowledge that their data is incomplete. In 2015, The Post documented more than two times more fatal shootings by police than had been recorded by the FBI. Last year, the FBI announced plans to overhaul how it tracks fatal police encounters.

How to use this dataset

• Understanding US Police Shootings by Curtis Thompson
• Dataset Questions and Suggestions
• More datasets

Acknowledgements

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

BibTeX

@misc{wapo-police-shootings-bot , author = {The Washington Post}, title = {data-police-shootings}, month = jan, year = 2015, publisher = {Github}, url = {https://github.com/washingtonpost/data-police-shootings} }

License

CC BY NC SA 4.0

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About Dataset:

Don't Forget to Upvote the dataset.

https://upload.wikimedia.org/wikipedia/commons/thumb/2/2f/Police_killings_in_the_USA_in_2018.svg/220px-Police_killings_in_the_USA_in_2018.svg.png" alt="">

Below are lists of people killed by law enforcement in the United States, both on duty and off duty. Although Congress instructed the Attorney General in 1994 to compile and publish annual statistics on police use of excessive force, this was never carried out, and the Federal Bureau of Investigation does not collect these data.

Deaths by age group in 2015, according to The Counted

Column Details:

COLUMN NAME	INFO
id	SERIAL NO
name	NAME OF VICTIM THAT GOT SHOT OR TASERED BY POLICE
date	DATE IN WHICH HE GOT VICTIMIZED
manner_of_death	TYPE OF MANNER IN WHICH HE DIED
armed	THE VICTIM WAS ARMED OR NOT
age	AGE OF VICTIM
gender	GENDER OF VICTIM
race	RACE,ETHICITY OF VICTIM
city	CITY IN THE USA IN which he/she DIED
state	STATE IN THE USA IN which he/she DIED
signs_of_mental_illness	VICTIM SHOWS SIGN OF ILLNESS
threat_level	LEVEL OF THREAT ON POLICE
flee	VICTIM FLEE OR DIE
body_camera	BODY CAMERA WAS ON POLICE OR NOT
longitude	LONGITUDE OF LOCATION
latitude	LATITUDE OF LOCATION
is_geocoding_exact	LOCATION AVAILABLE EXACT OR NOT

TO KNOW MORE FROM WIKIPEDIA :https://en.wikipedia.org/wiki/Lists_of_killings_by_law_enforcement_officers_in_the_United_States

The Arrest-Related Deaths (ARD) program is an annual national census of persons who die either during the process of arrest or while in the custody of state or local law enforcement personnel. The Bureau of Justice Statistics (BJS) implemented the ARD program in 2003 as part of the Deaths in Custody Reporting Program (DCRP). The DCRP was initiated to fulfill the data collection requirement of the Deaths in Custody Reporting Act of 2000 (DICRA, P.L. 106- 247). It collects in-depth information on deaths during arrest and incarceration, and it provides national-level information on the deaths of suspects and offenders from their initial contact with law enforcement personnel through the time they are incarcerated in a jail or prison. ARD data are collected to quantify and describe the circumstances surrounding civilian deaths that take place during an arrest or while in the custody of law enforcement. These data describe the prevalence and incidence of arrest-related deaths across the nation, identify the circumstances or activities that contribute to these deaths, and reveal trends in the causes and circumstances of these deaths in custody at national and state levels. These data can be used to inform specific policies that may increase the safety of law enforcement officers and citizens, identify training needs in law enforcement agencies, and assist in developing prevention strategies. The current ARD program relies on state reporting coordinators (SRCs) in each of the 50 states and the District of Columbia to identify and report on all eligible cases of arrest-related deaths. BJS compiles data from the states to produce national-level statistics on deaths that occur in the process of arrest by, or while in the custody of, state and local law enforcement personnel.

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 12 release notes:Adds 2021 data.Version 11 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will (probably, I haven't seen confirmation either way) be the last LEOKA data they release. Changes .rda file to .rds.Version 10 release notes:Changes release notes description, does not change data.Version 9 release notes:Adds data for 2019.Version 8 release notes:Fix bug for years 1960-1971 where the number of months reported variable was incorrectly down by 1 month. I recommend caution when using these years as they only report either 0 or 12 months of the year, which differs from every other year in the data. Added the variable officers_killed_total which is the sum of officers_killed_by_felony and officers_killed_by_accident.Version 7 release notes:Adds data from 2018Version 6 release notes:Adds data in the following formats: SPSS and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Version 5 release notes: Adds data for 1960-1974 and 2017. Note: many columns (including number of female officers) will always have a value of 0 for years prior to 1971. This is because those variables weren't collected prior to 1971. These should be NA, not 0 but I'm keeping it as 0 to be consistent with the raw data. Removes support for .csv and .sav files.Adds a number_of_months_reported variable for each agency-year. A month is considered reported if the month_indicator column for that month has a value of "normal update" or "reported, not data."The formatting of the monthly data has changed from wide to long. This means that each agency-month has a single row. The old data had each agency being a single row with each month-category (e.g. jan_officers_killed_by_felony) being a column. Now there will just be a single column for each category (e.g. officers_killed_by_felony) and the month can be identified in the month column. This also results in most column names changing. As such, be careful when aggregating the monthly data since some variables are the same every month (e.g. number of officers employed is measured annually) so aggregating will be 12 times as high as the real value for those variables. Adds a date column. This date column is always set to the first of the month. It is NOT the date that a crime occurred or was reported. It is only there to make it easier to create time-series graphs that require a date input.All the data in this version was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. Data is the same as from NACJD but using all FBI files makes cleaning easier as all column names are already identical. Version 4 release notes: Add data for 2016.Order rows by year (descending) and ORI.Version 3 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself. Several agency had impossible large (>15) officer deaths in a single month. For those months I changed the value to NA. The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which

What is The Counted? The Counted is a project by the Guardian – and you – working to count the number of people killed by police and other law enforcement agencies in the United States throughout 2015, to monitor their demographics and to tell the stories of how they died. The database will combine Guardian reporting with verified crowdsourced information to build a more comprehensive record of such fatalities. The Counted is the most thorough public accounting for deadly use of force in the US, but it will operate as an imperfect work in progress – and will be updated by Guardian reporters and interactive journalists as frequently and as promptly as possible.

For any questions about this data please email me at jacob@crimedatatool.com. If you use this data, please cite it.Version 7 release notes:Add data from 2018Version 6 release notes:Adds data in the following formats: SPSS and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Version 5 release notes: Adds data for 1960-1974 and 2017. Note: many columns (including number of female officers) will always have a value of 0 for years prior to 1971.Removes support for .csv and .sav files.Adds a number_of_months_reported variable for each agency-year. A month is considered reported if the month_indicator column for that month has a value of "normal update" or "reported, not data."The formatting of the monthly data has changed from wide to long. This means that each agency-month has a single row. The old data had each agency being a single row with each month-category (e.g. jan_officers_killed_by_felony) being a column. Now there will just be a single column for each category (e.g. officers_killed_by_felony) and the month can be identified in the month column. This also results in most column names changing. As such, be careful when aggregating the monthly data since some variables are the same every month (e.g. number of officers employed is measured annually) so aggregating will be 12 times as high as the real value for those variables. Adds a date column. This date column is always set to the first of the month. It is NOT the date that a crime occurred or was reported. It is only there to make it easier to create time-series graphs that require a date input.All the data in this version was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. Data is the same as from NACJD but using all FBI files makes cleaning easier as all column names are already identical. Version 4 release notes: Add data for 2016.Order rows by year (descending) and ORI.Version 3 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself. Several agency had impossible large (>15) officer deaths in a single month. For those months I changed the value to NA. See the R code for a complete list. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data.The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety."... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."

Does increased militarization of law enforcement agencies (LEAs) lead to an increase in violent behavior among officers? We theorize that the receipt of military equipment increases multiple dimensions of LEA militarization (material, cultural, organizational, and operational) and that such increases lead to more violent behavior. The U.S. Department of Defense 1033 program makes excess military equipment, including weapons and vehicles, available to local LEAs. The variation in the amount of transferred equipment allows us to probe the relationship between military transfers and police violence. We estimate a series of regressions that test the effect of 1033 transfers on three dependent variables meant to capture police violence: the number of civilian casualties; the change in the number of civilian casualties; the number of dogs killed by police. We find a positive and statistically significant relationship between 1033 across all models.

The Counted is a project by the Guardian – and you – working to count the number of people killed by police and other law enforcement agencies in the United States throughout 2015 and 2016, to monitor their demographics and to tell the stories of how they died.

The database will combine Guardian reporting with verified crowdsourced information to build a more comprehensive record of such fatalities. The Counted is the most thorough public accounting for deadly use of force in the US, but it will operate as an imperfect work in progress – and will be updated by Guardian reporters and interactive journalists as frequently and as promptly as possible.

This dataset is one of three that pull together data from several different sources regarding police-related violence and racial equity in the United States. The datasets currently include these types of data:

Part 1: Citizen deaths, police deaths, and other outcomes - Police shootings - Citizen fatalities involving police - Police officer deaths suffered in the line of duty

Part 2: Demographics, crime stats, protests, and other data - Social and economic data - Political leanings of citizens - Sales of DoD equipment to law enforcement agencies - City budgets - Police department headcounts - Police department policies and contract provisions - Juvenile arrests by type of crime and race - Crimes and arrests for the prime city in the four largest metro areas. - Protest activity - Police response - Press activity - Video clips of incidents

I don't believe that any amount of data can fully describe the social dysfunction we have. At the same time, I hope these datasets can be an objective source for providing thoughtful, fact-based analysis of this important issue.

On March 16, 2023, two officers with the Edmonton Police Service (EPS) were killed in the line of duty during an interaction with members of the public. During the same incident, one civilian was killed and another civilian was injured. Because civilians suffered harm during an interaction with police officers, the Alberta Serious Incident Response Team was directed to perform a review of the EPS investigation into the circumstances that led to the deaths and injury.

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