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

In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

Violent crime rates for Everett, Snohomish County, Washington State, and the US as reported by the FBI's National Incident-Based Reporting System (NIBRS) program. The violent crime rate is defined as the number of reported violent crimes per 100,000 residents. Violent crime figures include the offenses of murder, rape, robbery, and aggravated assault. Note that County population figures come from the US Census Bureau's American Community Survey.

In 2023, the property crime rate in the District of Columbia was 4,307.4 reported property crimes per 100,000 residents. New Mexico, Washington, Colorado and Louisiana rounded out the top five states with the highest rates of property crime in that year.

The Washington SAC provides access to crime statistics through several methods; CrimeStats Online, the Uniform Crime Report (UCR), and the National Incident Based Reporting System (NIBRS). Queries are web-based interfaces that allow users to query Washington crime data online. For more detailed analyses, the UCR and NIBRS data are available in Excel spreadsheets and SAS datasets. County-level summaries from the Criminal Justice Data Book are available in Excel as well.

This data collection contains information on solved murders occurring in Washington State between 1981 and 1986. The collection is a subset of data from the Homicide Investigation Tracking System (HITS), a computerized database maintained by the state of Washington that contains information on murders and sexual assault cases in that state. The data for HITS are provided voluntarily by police and sheriffs' departments covering 273 jurisdictions, medical examiners' and coroners' offices in 39 counties, prosecuting attorneys' offices in 39 counties, the Washington State Department of Vital Statistics, and the Uniform Crime Report Unit of the Washington State Association of Sheriffs and Police Chiefs. Collected data include crime evidence, victimology, offender characteristics, geographic locations, weapons, and vehicles.

This dataset shows crime statistics for the City of Clarkston, WA Police Department.

These data were prepared in conjunction with a project using Bureau of Labor Statistics data (not provided with this collection) and the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program data to examine the relationship between unemployment and violent crime. Three separate time-series data files were created as part of this project: a national time series (Part 1), a state time series (Part 2), and a time series of data for 12 selected cities: Baltimore, Buffalo, Chicago, Columbus, Detroit, Houston, Los Angeles, Newark, New York City, Paterson (New Jersey), and Philadelphia (Part 3). Each data file was constructed to include 82 monthly time series: 26 series containing the number of Part I (crime index) offenses known to police (excluding arson) by weapon used, 26 series of the number of offenses cleared by arrest or other exceptional means by weapon used in the offense, 26 series of the number of offenses cleared by arrest or other exceptional means for persons under 18 years of age by weapon used in the offense, a population estimate series, and three date indicator series. For the national and state data, agencies from the 50 states and Washington, DC, were included in the aggregated data file if they reported at least one month of information during the year. In addition, agencies that did not report their own data (and thus had no monthly observations on crime or arrests) were included to make the aggregated population estimate as close to Census estimates as possible. For the city time series, law enforcement agencies with jurisdiction over the 12 central cities were identified and the monthly data were extracted from each UCR annual file for each of the 12 agencies. The national time-series file contains 82 time series, the state file contains 4,083 time series, and the city file contains 963 time series, each with 228 monthly observations per time series. The unit of analysis is the month of observation. Monthly crime and clearance totals are provided for homicide, negligent manslaughter, total rape, forcible rape, attempted forcible rape, total robbery, firearm robbery, knife/cutting instrument robbery, other dangerous weapon robbery, strong-arm robbery, total assault, firearm assault, knife/cutting instrument assault, other dangerous weapon assault, simple nonaggravated assault, assaults with hands/fists/feet, total burglary, burglary with forcible entry, unlawful entry-no force, attempted forcible entry, larceny-theft, motor vehicle theft, auto theft, truck and bus theft, other vehicle theft, and grand total of all actual offenses.

Context

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

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

Content

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

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

Acknowledgements

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

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

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

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

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

Inspiration

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

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

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

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

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

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

4. Does ethnicity play a role in crime rate?

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

In 2023, there were 906,176 cases of property crimes reported in California - the highest in the country. Texas, New York, Florida, and Washington rounded out the top five states in the U.S. for property crimes in that year.

The Seattle Police Department (SPD) replaced its Records Management System (RMS) in May 2019. To preserve data quality and continuity between systems (2008-Present), SPD relied on the National Incident-Based Reporting System (NIBRS). The standardization of crime classifications allows for comparison over time. For more information on definitions and classifications, please visit https://www.fbi.gov/services/cjis/ucr/nibrs.

Additional groupings are used to analyze crime in SPD’s Crime Dashboard. Violent and property crime categories align with best practices. For additional inquiries, we encourage the use of the underline data to align with the corresponding query.

Disclaimer: Only finalized (UCR approved) reports are released. Those in draft, awaiting approval, or completed after the update, will not appear until the subsequent day(s). Data is updated once every twenty-four hours. Records and classification changes will occur as a report makes its way through the approval and investigative process.

The King County Sheriff’s Office (KCSO) is providing offense report data captured in it's Records Management System (RMS) from 2020 to present. KCSO replaced its RMS in late 2018 and at the same time transitioned to the FBI’s National Incident-Based Reporting System (NIBRS). The NIBRS standardization of crime classifications allows for comparison over time and between agencies. For official KCSO NIBRS reporting, please visit the WASPC Crime in Washington Report: https://www.waspc.org/cjis-statistics---reports.

Disclaimer: Only finalized (supervisor approved) reports are released. Those in draft, awaiting supervisor approval, or completed after the daily update of data, will not appear until the subsequent day(s). Data updates once every twenty-four hours. Records and classification changes will occur as a report makes its way through the approval and investigative process, thus reports might appear in the data set one day, but be removed the next day if there is a change in the approval status. This mirrors the fluidity of an investigation. Once a report is re-approved, it will show back up in the data set. Other than approval status, the report case status is factored into what can be released in the daily data set. As soon as a report case status matches the criteria for release, it will be included in the data set. For a list of offenses that are included in the data set, please see the attached pdf.

Resources: - KCSO's 2019 crime data: https://data.kingcounty.gov/Law-Enforcement-Safety/King-County-Sheriff-s-Office-Incident-Dataset/rzfs-wyvy - Police District GIS shapefile: https://gis-kingcounty.opendata.arcgis.com/datasets/king-county-sheriff-patrol-districts-patrol-districts-area/explore - Police District key: https://data.kingcounty.gov/Law-Enforcement-Safety/KCSO-Patrol-Districts/ptrt-hdax/data - For more information on definitions and classifications, please visit https://www.fbi.gov/services/cjis/ucr/nibrs - SPD's Crime Data: https://data.seattle.gov/Public-Safety/SPD-Crime-Data-2008-Present/tazs-3rd5

In 2022, the New Orleans-Metairie, LA metro area recorded the highest homicide rate of U.S. cities with a population over 250,000, at **** homicides per 100,000 residents, followed by the Memphis, TN-MS-AR metro area. However, homicide data was not recorded in all U.S. metro areas, meaning that there may be some cities with a higher homicide rate. St. Louis St. Louis, which had a murder and nonnegligent manslaughter rate of **** in 2022, is the second-largest city by population in Missouri. It is home to many famous treasures, such as the St. Louis Cardinals baseball team, Washington University in St. Louis, the Saint Louis Zoo, and the renowned Gateway Arch. It is also home to many corporations, such as Monsanto, Arch Coal, and Emerson Electric. The economy of St. Louis is centered around business and healthcare, and boasts ten Fortune 500 companies. Crime in St. Louis Despite all of this, St. Louis suffers from high levels of crime and violence. As of 2023, it was listed as the seventh most dangerous city in the world as a result of their extremely high murder rate. Not only does St. Louis have one of the highest homicide rates in the United States, it also reports one of the highest numbers of violent crimes. Despite high crime levels, the GDP of the St. Louis metropolitan area has been increasing since 2001.

V6 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. V5 release notes: Changes the word "larceny" to "theft" in column names - eg. from "act_larceny" to "act_theft."Fixes bug where state abbrebation was NA for Washington D.C., Puerto Rico, Guam, and the Canal Zone.Fixes bug where officers_killed_by_accident was not appearing in yearly data. Note that 1979 does not have any officers killed (by felony or accident) or officers assaulted data.Adds aggravated assault columns to the monthly data. Aggravated assault is the sum of all assaults other than simple assault (assaults using gun, knife, hand/feet, and other weapon). Note that summing all crime columns to get a total crime count will double count aggravated assault as it is already the sum of existing columns. Reorder columns to put all month descriptors (e.g. "jan_month_included", "jan_card_1_type") before any crime data.Due to extremely irregular data in the unfounded columns for New Orleans (ORI = LANPD00) for years 2014-2016, I have change all unfounded column data for New Orleans for these years to NA. As an example, New Orleans reported about 45,000 unfounded total burglaries in 2016 (the 3rd highest they ever reported). This is 18 times largest than the number of actual total burglaries they reported that year (2,561) and nearly 8 times larger than the next largest reported unfounded total burglaries in any agency or year. Prior to 2014 there were no more than 10 unfounded total burglaries reported in New Orleans in any year. There were 10 obvious data entry errors in officers killed by felony/accident that I changed to NA.In 1974 the agency "Boston" (ORI = MA01301) reported 23 officers killed by accident during November.In 1978 the agency "Pittsburgh" (ORI = PAPPD00) reported 576 officers killed by accident during March.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by accident during April.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by accident during June.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by felony during April.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by felony during June.In 1978 the agency "Queens Transit Authority" (ORI = NY04040) reported 56 officers killed by accident during May.In 1978 the agency "Queens Transit Authority" (ORI = NY04040) reported 56 officers killed by felony during May.In 1996 the agency "Ruston" in Louisiana (ORI = LA03102) reported 30 officers killed by felony during September.In 1997 the agency "Washington University" in Missouri (ORI = MO0950E) reported 26 officers killed by felony during March.V4 release notes: Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Makes all column names lowercase.Change some variable namesMakes values in character columns lowercase.Adds months_reported variable to yearly data.Combines monthly and yearly files into a single zip file (per data type).V3 release notes: fixes a bug in Version 2 where 1993 data did not properly deal with missing values, leading to enormous counts of crime being reported. Summary: This is a collection of Offenses Known and Clearances By Arrest data from 1960 to 2016. Each zip file contains monthly and yearly data files. The monthly files contain one data file per year (57 total, 1960-2016) as well as a codebook for each year. These files have been read into R using the ASCII and setup files from ICPSR (or from the FBI for 2016 data) using the package asciiSetupReader. The end of the zip folder's name says what data type (R, SPSS, SAS, Microsoft Excel CSV, Stata) the data is in. The files are lightly cleaned. What this means specifically is that column names and value labels are standardized. In the original data column names were different between years (e.g. the December burglaries cleared column is "DEC_TOT_CLR_BRGLRY_TOT" in 1975 and "DEC_TOT_CLR_BURG_TOTAL" in 1977). The data here have standardized columns so you can compare between years and combine years together. The same thing is done for values inside of columns. For example, the state column gave state names in some years, abbreviations in others. For the code uses to clean and read the data, please see my GitHub file h

V8 release notes: Adds 2017 data.V7 release notes: Removes SPSS (.sav) and Excel (.csv) files. Changes column names for clearances to "tot_clr_..." to make explicit that this is all clearances, not just adult clearances. 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-crime (e.g. jan_act_murder) being a column. Now there will just be a single column for each crime (e.g. act_murder) and the month can be identified in the month column. Adds a month column and 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. Removes all card columns. This was done to reduce file size. Reorders crime columns to the order of assaults/deaths of officers, actual crimes, total clearance, clearance under age 18, unfounded. Within each category the columns are alphabetized.Monthly data and yearly data are now in different zip folders to download.V6 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. V5 release notes: Changes the word "larceny" to "theft" in column names - eg. from "act_larceny" to "act_theft."Fixes bug where state abbrebation was NA for Washington D.C., Puerto Rico, Guam, and the Canal Zone.Fixes bug where officers_killed_by_accident was not appearing in yearly data. Note that 1979 does not have any officers killed (by felony or accident) or officers assaulted data.Adds aggravated assault columns to the monthly data. Aggravated assault is the sum of all assaults other than simple assault (assaults using gun, knife, hand/feet, and other weapon). Note that summing all crime columns to get a total crime count will double count aggravated assault as it is already the sum of existing columns. Reorder columns to put all month descriptors (e.g. "jan_month_included", "jan_card_1_type") before any crime data.Due to extremely irregular data in the unfounded columns for New Orleans (ORI = LANPD00) for years 2014-2016, I have change all unfounded column data for New Orleans for these years to NA. As an example, New Orleans reported about 45,000 unfounded total burglaries in 2016 (the 3rd highest they ever reported). This is 18 times largest than the number of actual total burglaries they reported that year (2,561) and nearly 8 times larger than the next largest reported unfounded total burglaries in any agency or year. Prior to 2014 there were no more than 10 unfounded total burglaries reported in New Orleans in any year. There were 10 obvious data entry errors in officers killed by felony/accident that I changed to NA.In 1974 the agency "Boston" (ORI = MA01301) reported 23 officers killed by accident during November.In 1978 the agency "Pittsburgh" (ORI = PAPPD00) reported 576 officers killed by accident during March.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by accident during April.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by accident during June.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by felony during April.In 1978 the agency "Bronx Transit Authority" (ORI = NY06240) reported 56 officers killed by felony during June.In 1978 the agency "Queens Transit Authority" (ORI = NY04040) reported 56 officers killed by accident during May.In 1978 the agency "Queens Transit Authority" (ORI = NY04040) reported 56 officers killed by felony during May.In 1996 the agency "Ruston" in Louisiana (ORI = LA03102) reported 30 officers killed by felony during September.In 1997 the agency "Washington University" in Missouri (ORI = MO0950E) reported 26 officers killed by felony during March.V4 release notes: Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Makes all column names lowercase.Change some variable namesMakes values in character columns lowercase.Adds months_reported variable to yearly data.Combines monthly and yearly files into a single zip file (per data type).V3 release notes: fixes a bug in Version 2 where 1993 data did not properly deal with missing values, leading to enormous counts of crime being report

In 2023, ***** hate crime offenses were reported in California, the most out of any state. New Jersey, New York, Washington, and Massachusetts rounded out the top five states for hate crime offenses in that year.

In 2023, New Mexico had the highest burglary rate in the United States. That year, they had 517.9 occurrences per 100,000 residents. Washington followed with 481 incidents per 100,000 residents. What is burglary? Burglary in the United States is considered a felony or misdemeanor. It includes trespassing and theft, and going inside a building or car with the intent to commit any crime. Even if the crime is not necessarily theft, it is still illegal. Some states consider burglary committed during the day as housebreaking, not burglary. The Bureau of Justice Statistics defines it as unlawful or forcible entry into a building. There are four types of burglary in total: completed burglary, forcible entry, unlawful entry, and attempted forcible entry. Burglary in the United States Burglary affects all 50 states in the United States, as burglary was the third most common type of property crime in the United States in 2023. California had the highest number of reported burglaries in that same year, whereas New Hampshire had the lowest number. However, the overall reported burglary rate in the United States has decreased significantly since 1990.

In 2023, the District of Columbia had the highest rate of motor vehicle theft in the United States, with 1,070.9 cases per 100,000 inhabitants. Washington, Nevada, Colorado, and Maryland rounded out the top five states for motor vehicle theft in that year. Nationwide, the rate of motor vehicle theft stood at 318.7 cases per 100,000 residents.

Alaska saw the highest rape rate in the United States in 2023, with 118.4 rapes per 100,000 inhabitants. The lowest rate was found in New Jersey, with 17.9 rapes per 100,000 inhabitants. Sexual assault in Alaska Fighting sexual assault in Alaska is particularly difficult due to small, isolated, close-knit communities who can be wary of airing their dirty laundry to outsiders, as well as a low number of law enforcement employees in the state. In addition, Alaska’s low population is spread out over a large land area, meaning that in the event of an assault being reported to police, it can take law enforcement hours, or even days, to reach the most isolated communities. The victims of sexual assault There tends to be more reported female victims of sexual assault than male victims. However, since sexual assault is typically an underreported crime, especially among males, these figures could be, and probably are, much higher. In addition, many victims of sexual offenses tend to be young, although sexual assault can occur at any age.

The rate of incidents of violent criminal code violations in Canada increased by 51.1 incidents (+3.71 percent) in 2023 in comparison to the previous year. In total, the rate of incidents amounted to 1,427.94 incidents in 2023.