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.

This map shows the total crime index in the U.S. in 2020 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layersPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Retirement Notice: This item is in mature support as of June 2023 and will be retired in December 2025. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item.This map shows the total crime index in the U.S. in 2022 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The layer uses 2020 Census boundaries. The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indices Permitted use of this data is covered in the DATA section of the EsriMaster Agreement (E204CW) and these supplemental terms.

This dataset aggregates Seattle Police Department crime statistics with spatial ZIP code boundaries and US Census data to determine the property crime rate per 1,000 residents. The following sources were used to create this dataset:

King County ZIP Code Boundaries

Source: https://data-seattlecitygis.opendata.arcgis.com/datasets/SeattleCityGIS::zip-codes/explore

King County provides approximate ZIP code boundaries, updated quarterly and published by the city of Seattle.

SPD Crime Data: 2008-Present

Source: https://data.seattle.gov/Public-Safety/SPD-Crime-Data-2008-Present/tazs-3rd5

The Seattle Police Department publishes data for reported crimes from 2008 to the present, refreshed daily. This data includes whether the crime is classified as against a person, against property, or against society.

2020 ACS 5-year estimates for population

Source: https://data.census.gov/cedsci/table?q=population%20seattle&g=0400000US53%248600000&tid=ACSDP5Y2020.DP05

The US Census Department American Community Survey (ACS) publishes 5-year estimates of population by a variety of geographies, including ZIP Code Tabulation Areas (ZCTAs), geographic approximations of each ZIP code.

Data Processing

Using the pandas and geopandas libraries within python, the following processing steps were followed to prepare this dataset: - Converted the date and time reported field in the SPD dataset to a datetime object and extracted the year - Filtered to crimes reported between 2008 and 2021 - Filtered to only crimes against property - Dropped rows with null values for year, crime against category, longitude, or latitude - Performed a spatial join using the latitude and longitude for each report in the SPD data to append a ZIP code from the King County ZIP Code boundary shapefile - Summarized to calculate a count of property crimes reported for each combination of year and ZIP code - Summarized by ZIP code to calculate the count of years with at least one crime reported and the total number of property crimes reported - Calculated the average number of property crimes reported per year in each ZIP code - Merged with the ACS population estimates - Calculated the number of property crimes reported per year per 1,000 population for each zip code

Photo by Justus Hayes: https://www.pexels.com/photo/a-bicycle-chained-to-a-metal-post-6355944/

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 NameField DescriptionIncident Numberthe number associated with either the incident or used as reference to store the items in our evidence roomsDate Reportedthe date the incident was reported to LMPDDate Occurredthe date the incident actually occurredBadge IDBadge ID of responding OfficerOffense ClassificationNIBRS Reporting category for the criminal act committedOffense Code NameNIBRS Reporting code for the criminal act committedNIBRS_CODEthe 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/viewNIBRS Grouphierarchy that follows the guidelines of the FBI National Incident Based Reporting SystemWas Offense CompletedStatus indicating whether the incident was an attempted crime or a completed crime.LMPD Divisionthe LMPD division in which the incident actually occurredLMPD Beatthe LMPD beat in which the incident actually occurredLocation Categorythe type of location in which the incident occurred (e.g. Restaurant)Block Addressthe location the incident occurredCitythe city associated to the incident block locationZip Codethe zip code associated to the incident block locationContact:LMPD Open Records lmpdopenrecords@louisvilleky.gov

The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_60 _100.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_100 _250.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_250 _plus.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'total_crime': total crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'total_violent _crime': total violent crime - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft - 'tot_prop _crime': total property crime - 'arson': arson

Photo by David von Diemar on Unsplash

Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2024.

This map shows the total crime index in the U.S. in 2021 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.For more information about the AGS Crime Indices, click here. Additional Esri Resources:Esri DemographicsU.S. 2021/2026 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layersPermitted use of this data is covered in the DATA section of the EsriMaster Agreement (E204CW) and these supplemental terms.

Note: Due to a system migration, this data will cease to update on March 14th, 2023. The current projection is to restart the updates on or around July 17th, 2023.Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_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/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov

Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_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/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov

This map shows the total crime index in the U.S. in 2018 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.Additional Esri Resources:Esri DemographicsU.S. 2018/2023 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers

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.

Much research has examined how crime rates vary across urban neighborhoods, focusing particularly on community-level demographic and social characteristics. A parallel line of work has treated crime at the individual level as an expression of certain behavioral patterns (e.g., impulsivity). Little work has considered, however, whether the prevalence of such behavioral patterns in a neighborhood might be predictive of local crime, in large part because such measures are hard to come by and often subjective. The Facebook Advertising API offers a special opportunity to examine this question as it provides an extensive list of “interests” that can be tabulated at various geographic scales. Here we conduct an analysis of the association between the prevalence of interests among the Facebook population of a ZIP code and the local rate of assaults, burglaries, and robberies across 9 highly populated cities in the US. We fit various regression models to predict crime rates as a function of the Facebook and census demographic variables. In general, models using the variables for the interests of the whole adult population on Facebook perform better than those using data on specific demographic groups (such as Males 18-34). In terms of predictive performance, models combining Facebook data with demographic data generally have lower error rates than models using only demographic data. We find that interests associated with media consumption and mating competition are predictive of crime rates above and beyond demographic factors. We discuss how this might integrate with existing criminological theory.

Esri's Crime Indexes data incorporates information from the AGS national CrimeRisk database that is based on an extensive analysis of several years of crime incidents reported by most US law enforcement jurisdictions. The Crime Indexes database includes standardized indexes for a range of serious crimes against both persons and property. The data vintage is 2019. All attributes are available at the following geography levels: State, County, Tract, Block Group, ZIP Code, Place, CBSA and DMA. Attributes include total crime index, personal crime index, and other indexes for serious crimes. To view ArcGIS Online items using this service, including the terms of use, visit http://goto.arcgisonline.com/demographics5/USA_Crime.

Update Frequency: Daily

Current year to date. The data included in this dataset has been reviewed and approved by a Milwaukee Police Department supervisor and the Milwaukee Police Department’s Records Management Division. This approval process can take a few weeks from the reported date of the crime. For preliminary crime data, please visit the Milwaukee Police Department’s Crime Maps and Statistics dashboard at https://city.milwaukee.gov/police/Information-Services/Crime-Maps-and-Statistics.

Wisconsin Incident Based Report (WIBR) Group A Offenses.

The Crime Data represents incident level data defined by Wisconsin Incident Based Reporting System (WIBRS) codes. WIBRS reporting is a crime reporting standard and can not be compared to any previous UCR report. Therefore, the Crime Data may reflect:

• Information not yet verified by further investigation
• Preliminary crime classifications that may be changed at a later date based upon further investigation
• Information that may include mechanical or human error

Neither the City of Milwaukee nor the Milwaukee Police Department guarantee (either express or implied) the accuracy, completeness, timeliness, or correct sequencing of the Crime Data. The City of Milwaukee and the Milwaukee Police Department shall have no liability for any error or omission, or for the use of, or the results obtained from the use of the Crime Data. In addition, the City of Milwaukee and the Milwaukee Police Department caution against using the Crime Data to make decisions/comparisons regarding the safety of or the amount of crime occurring in a particular area. When reviewing the Crime Data, the site user should consider that:

• The information represents only police services where a report was made and does not include other calls for police service
• The information does not reflect or certify "safe" or "unsafe" areas
• The information will sometimes reflect where the crime was reported versus where the crime occurred

This data is not intended to represent a total number/sum of crimes, rather 1 = True and 0 = False.

The use of the Crime Data indicates the site user's unconditional acceptance of all risks associated with the use of the Crime Data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page. XY fields in data is in projection Wisconsin State Plane South NAD27 (WKID 32054).

***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.

This dataset contains different collected datasets with crime data of many large cities. Below are the descriptions for each seperate dataset. Note: Dataset properties and column may differ from each other since the information was collected by the local police in different styles and situations.

1. Los Angeles

The Los Angeles dataset has the collected data on different crimes that happened in Los Angeles from 2000 up until May 2024. The columns are as follows:

• DR_NO - Division of Records Number: Official file number made up of a 2 digit year, area ID, and 5 digits

• Date Rptd - The date when the police found out about the crime

• Date OCC - The actual date of the crime

• Time OCC - In military time

• Area - The LAPD has 21 Community Police Stations referred to as Geographic Areas within the department. These Geographic Areas are sequentially numbered from 1-21.

• Area Name - The 21 Geographic Areas or Patrol Divisions are also given a name designation that references a landmark or the surrounding community that it is responsible for. For example 77th Street Division is located at the intersection of South Broadway and 77th Street, serving neighborhoods in South Los Angeles.

• Rpt Dist No - A four-digit code that represents a sub-area within a Geographic Area. All crime records reference the "RD" that it occurred in for statistical comparisons. Find LAPD Reporting Districts on the LA City GeoHub at http://geohub.lacity.org/datasets/c4f83909b81d4786aa8ba8a74a4b4db1_4

• Crm Cd - Indicates the crime committed. (Same as Crime Code 1)

• Crm Cd Desc - Defines the Crime Code provided.

• Mocodes - Modus Operandi: Activities associated with the suspect in commission of the crime.

• Vict Age - The age of the victim

• Vict Sex - The gender of the victim. They are as follows:

  • M - Male
  • F - Female
  • X - Unknown

• Vict Descent - Descent Code:

  • A - Other Asian
  • B - Black
  • C - Chinese
  • D - Cambodian
  • F - Filipino
  • G - Guamanian
  • H - Hispanic/Latin/Mexican
  • I - American Indian/Alaskan Native
  • J - Japanese
  • K - Korean
  • L - Laotian
  • O - Other
  • P - Pacific Islander
  • S - Samoan
  • U - Hawaiian
  • V - Vietnamese
  • W - White
  • X - Unknown
  • Z - Asian Indian

• Premis Cd - The type of structure, vehicle, or location where the crime took place.

• Premis Desc - Defines the Premise Code provided.

• Weapon Used Cd - The type of weapon used in the crime.

• Status - Status of the case. (IC is the default)

• Status Desc - Defines the Status Code provided.

• Crm Cd 1 - Indicates the crime committed. Crime Code 1 is the primary and most serious one. Crime Code 2, 3, and 4 are respectively less serious offenses. Lower crime class numbers are more serious.

• Crm Cd 2 - May contain a code for an additional crime, less serious than Crime Code 1.

• Crm Cd 3 - May contain a code for an additional crime, less serious than Crime Code 1.

• Crm Cd 4 - May contain a code for an additional crime, less serious than Crime Code 1.

• Location - Street address of crime incident rounded to the nearest hundred block to maintain anonymity.

• Cross Street - Cross Street of rounded Address

• LAT - Latitude

• LON - Longitude

This dataset has 28 columns and 944K rows. I hope you will find it useful. God bless you

1. Chicago

This dataset contains crime data on Chicago, from 2001 to present. The columns are as follows:

• ID - Unique Identifier for the record

• Case Number - The Chicago Police Department RD Number (Records Division Number), which is unique to the incident.

• Date - Date when the incident occurred. this is sometimes a best estimate.

• Block - The partially redacted address where the incident occurred, placing it on the same block as the actual address.

• IUCR - The Illinois Unifrom Crime Reporting code. This is directly linked to the Primary Type and Description. See the list of IUCR codes at https://data.cityofchicago.org/d/c7ck-438e..

• Primary Type - The primary description of the IUCR code.

• Description - The secondary description of the IUCR code, a subcategory of the primary description.

• Location Description - Description of the location where the incident occurred.

• Arrest - Indicates whether an arrest was made.

• Domestic - Indicates whether the incident was domestic-related as defined by the Illinois Domestic Violence Act.

• Beat - Indicates the beat where the incident occurred. A beat is the smallest police geographic area – each beat has a dedicated police beat car. Three to five beats make up a police sector, and three sectors make up a police district. The Chicago Police Department has 22 police districts. See the beats at https://data.cityofchicago.org/d/aerh-rz74.

• Distric...

The Justice Equity Need Index (JENI), by Advancement Project California, offers a means to map out the disparate burden that criminalization and a detention-first justice model place on specific communities. The index includes the following indicators:System Involvement: The system-involved population by ZIP Code results in direct needs for justice equity, as measured by adult and youth probation. Indicators: Adult Probation (per 1,000 people); Youth Probation (per 1,000 people) Inequity Drivers: Root inequities across communities that contribute to racial and economic disparities as seen in incarceration and policing. Indicators: Black, Latinx, AIAN, and NHPI Percentages of Population (average percentile); Unemployment Rate (%); Population aged 25+ without a High School Diploma (%); Population below 200% of the Federal Poverty Level (%); Violent Crime Rate (per 1,000 people) Criminalization Risk: Conditions where the criminal justice system has historically taken a detention-first, prevention-last approach. Indicators: Mental Health Hospitalizations (per 1,000 people); Substance Use-Related Hospitalizations (per 1,000 people); Homelessness Rate (per 1,000 people) Learn more at https://www.catalystcalifornia.org/campaign-tools/maps-and-data/justice-equity-need-index.Supervisorial Districts, SPAs, and CSAs determined by ZIP Code centroid.

This layer shows the total crime index in the U.S. in 2017 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.Additional Esri Resources:Esri DemographicsU.S. 2017/2022 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers