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.

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

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

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).

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.

This dataset contains official crime records reported in Los Angeles City from January 2020 to December 2023.

The data provides valuable information about reported crimes, including the date, area, crime details, victim information, premises, weapons used, and status.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

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Interesting Task Ideas:

1. Analyze the temporal patterns of crimes in different areas of Los Angeles City.
2. Identify the most common crimes.
3. Explore the correlation between victim age and crime types.
4. Investigate the crime rates in different areas of the city.
5. Examine the relationship between premises and specific crime codes.
6. Visualize the distribution of crimes on a map of Los Angeles City.
7. Analyze the relationship between crime status and occurrence location.
8. Use machine learning techniques to predict crime categories based on available features.

Data for violent crimes per Police Incident Data taken from the records managment sysmte

This project aims to identify areas in Los Angeles that are at high risk of crime in the future and to propose optimal locations for new police stations in those areas. By applying machine learning to post-COVID-19 crime data and various socioeconomic indicators, we predict crime risk at the ZIP Code level. Using a location-allocation model, we then determine suitable locations for new police stations to improve coverage of high-risk zones. The results of our analysis can support the efficient allocation of public safety resources in response to growing demand and budget constraints, helping city officials optimize law enforcement services. The content of the archive- Jupyter Notebook- Data (GeoJSON, CSV)- Summary report PDF FileThe platform on which the notebook should be run.This notebook is designed to run on Datahub.Project materials - Project Material we created on AGOL 1 Los Angeles Crime Hotspothttps://ucsdonline.maps.arcgis.com/home/item.html?id=4bddbae65c164f2d9b0285e09cb2820e 2 Choropleth Map of Predicted Crime Levels by ZIP Codehttps://ucsdonline.maps.arcgis.com/home/item.html?id=e47abb448f0a411ab77c6ac754ba0c34 3. Optimizing LA Police Station: A Location Allocation Analysishttps://ucsdonline.maps.arcgis.com/home/item.html?id=2409da85c3fe410e9578a0eaaed8471e - ArcGIS StoryMaphttps://ucsdonline.maps.arcgis.com/home/item.html?id=cfbd4fc27a3b400296e4e31555951d27 Software dependencies - pandas: Used for loading, formatting, and performing matrix operations on tabular data.- geopandas: Used for loading and processing spatial data, including spatial joins and coordinate transformations.- shapely.geometry.Point: Used to create spatial point objects from latitude and longitude coordinates.- arcgis.gis, arcgis.features, arcgis.geometry, arcgis.geoenrichment: Used to retrieve and manipulate geographic data from ArcGIS Online and to extract population statistics using the GeoEnrichment module.- numpy: Used for feature matrix formatting and numerical computations prior to model training.- IPython.display (display, Markdown, Image): Used to format and display Markdown text, data tables, and images within Jupyter Notebooks.- scikit-learn: Used for building and evaluating machine learning models. Specifically, it was used for data preprocessing (StandardScaler), splitting data (train_test_split), model selection and tuning (GridSearchCV, cross_val_score), training various regressors (e.g.,LinearRegression, RandomForestRegressor, KNeighborsRegressor), and assessing performance using metrics such as R², RMSE, and MAE.Other Components we used - ArcGIS Online: Used to create and host interactive web maps for spatial visualization and public presentation purposes.- Flourish: Used to create interactive graphs and charts for visualizing trends and supporting the analysis.

This interactive map symbolizes the population of total homeless individuals with small to large blue circles in each zip code. Additional homeless population demographics available by pop-up.

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

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 location

Is Boston Metro, MA Safe? The B grade means the rate of crime is slightly lower than the average US metro area. Boston Metro is in the 69th percentile for safety, meaning 31% of metro areas are safer and 69% of metro areas are more dangerous. This analysis applies to the Boston metro area's proper boundaries only. See the table on nearby places below for nearby metro areas.

The rate of crime in the Boston metro area is 19.92 per 1,000 residents during a standard year. People who live in the Boston metro area generally consider the southwest part of the metro area to be the safest.

Your chance of being a victim of crime in the Boston metro area may be as high as 1 in 32 in the central neighborhoods, or as low as 1 in 92 in the southwest part of the metro area. See the section on interpreting the crime map, however, because comparing rates for crime or any other crime is not as intuitive as it may seem. It can help us answer?

Type of crime vs locations where the crime took place? If there is any change in criminal activities in past years? Which location is safe and which is unsafe? Interestingly one can peek - DO MORE BROKEN WINDOWS MEAN MORE CRIME?

Here is the theory:

Researchers theorized that graffiti, abandoned buildings, panhandling, and other signs of disorder in neighborhoods create an environment that leads people to commit more crime.

In the “broken windows theory,” as it has come to be known, such characteristics convey the message that these places aren’t monitored and crime will go unpunished. The theory has led police to crack down on minor crimes with the idea that this will prevent more serious crimes, and inspired research on how disorder affects people’s health.

Inspiration Is the crime incident related to the area in Boston? Is there any relationship between the region and the types of crime? Is there any specific time during a week, a month or a year will infect the crime?

Retirement Notice: This item is in mature support as of July 2022 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This layer uses 2010 Census geographies. This layer shows the USA property 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:Personal 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 statistic shows the crime severity index value of metropolitan areas in Canada in 2023. As of 2023, the crime severity index in Saskatoon, Saskatchewan, stood at 116.31.

This layer shows the personal 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:Personal crime indexSub-categories of the personal crime indexThe 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. 2017/2022 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers