Hugging Face's logo

Datasets:
zwn22
/
NC_Crime

Languages:
English
Tags:
legal
License:
Dataset card Files Community
1
NC_Crime / README.md
zwn22's picture
zwn22
Update README.md
edd5ed6 verified
preview code
|
raw
history blame
11.3 kB
metadata
license: unknown
language:
  - en
tags:
  - legal

North Carolina Crime Dataset

Dataset Description

  • Homepage:

The processed dataset, which will soon be updated, is available at the following Huggingface portal: https://huggingface.co/datasets/zwn22/NC_Crime. For the raw datasets, their respective homepages are:

For any issues related to the raw datasets, please reach out to the respective government offices. For inquiries or issues regarding the processed data, you can contact zwn22 at Huggingface.

Dataset Summary

The dataset, derived from public police incident reports from various cities in North Carolina, spans from the early 2000s to 2024. The source data originate from the open data portals of Cary, Charlotte, Durham, and Raleigh. The dataset underwent a process of merging data from these cities, followed by cleaning to remove incomplete rows. Additionally, the dataset focuses on extracting and categorizing major crime types, providing valuable information such as crime type, time, location of occurrence, and other relevant details.

Supported Tasks

  1. Crime Trend Analysis: Analyzing crime trends over time and across different locations. This could involve identifying patterns in crime rates, seasonal variations, or shifts in the types of crimes committed.

  2. Predictive Policing: Developing models to predict future crime occurrences based on historical data. This could help in resource allocation and proactive policing strategies.

  3. Geospatial Analysis: Mapping crime incidents to identify hotspots and regions with higher crime rates. This can aid in understanding geographical factors influencing crime and in deploying resources more effectively.

  4. Crime Type Classification: Using machine learning algorithms to automatically classify incidents into different crime types based on the incident descriptions.

  5. Time Series Analysis: Examining how crime rates change over time and understanding long-term trends or cyclic patterns.

Languages

English

Dataset Structure

Data Instances

Here is an illustrative example from the processed dataset (note that specific details are subject to change):

{
  "year": 2022,
  "city": "Raleigh",
  "crime_major_category": "Theft",
  "crime_specific_category": "Vehicle Theft",
  "latitude": 35.7796,
  "longitude": -78.6382,
  "start_time": "2022-05-15T14:00:00",
  "end_time": "2022-05-15T16:00:00",
  "clear_status": "Cleared by Arrest",
  "incident_address": "123 Main St, Raleigh, NC",
  "notes": "Weapon: None"
}

Data Fields

The dataset contains several fields, each providing specific information about police incidents. Here is a list of these fields along with their descriptions and data types:

  • year (integer): The year in which the incident occurred. Used as input in temporal analysis tasks.
  • city (string): The city where the incident took place. This field is crucial for geographic analyses and comparisons between cities.
  • crime_major_category (string): A broad categorization of the crime, used as input for crime pattern analysis and categorization tasks.
  • crime_specific_category (string): More detailed classification of the crime, falling under the major category. This field allows for a finer-grained analysis of crime types.
  • latitude (float) and longitude (float): Geographical coordinates pinpointing the location of the incident. These fields are essential for geospatial analysis.
  • start_time (datetime) and end_time (datetime): The beginning and end times of the incident, providing temporal context. These fields are used in analyses that require time-based information.
  • clear_status (string): The resolution status of the case, such as whether it was cleared by arrest or remains under investigation. This field can be used to understand case outcomes.
  • incident_address (string): The specific address where the incident occurred. This field adds a detailed spatial dimension to the data.
  • notes (string): Additional remarks or details about the incident, like weapon usage or other relevant factors. This field provides supplementary information that may be relevant for certain analyses.

Dataset Creation

Curation Rationale

The dataset, covering police incidents in select North Carolina cities from 2000 to 2024, aims to aid crime research. It provides a long-term view of crime patterns and trends, useful for criminologists, sociologists, and public policy researchers. The comprehensive data enables analyses of crime evolution and its socio-economic correlations. It also supports the development of predictive models for law enforcement and policy planning. Additionally, the dataset's multi-city scope allows for comparative studies to understand unique challenges and inform localized crime prevention strategies.

Source Data

Five datasets are primarily utilized as source data:

  • Cary:
    • Cary Open Data Portal - CPD Incidents
    • Details:
      • Size: 116317 rows * 34 columns
      • Column names: 'Crime Category', 'Crime Type', 'UCR', 'Map Reference', 'Incident Number', 'Begin Date Of Occurrence', 'Begin Time Of Occurrence', 'End Date Of Occurrence', 'End Time Of Occurrence', 'Crime Day', 'Geo Code', 'Location Category', 'District', 'Beat Number', 'Location', 'ID', 'Lat', 'Lon', 'Charge Count', 'Neighborhood ID', 'Apartment Complex', 'Residential Subdivision', 'Subdivision ID', 'Phx Activity Date', 'Phx Record Status', 'Phx Community', 'Phx Status', 'Record', 'Offense Category', 'Violent Property', 'timeframe', 'domestic', 'Total Incidents', 'Year'
  • Charlotte:
    • Charlotte Open Data Portal - CMPD Incidents
    • Details:
      • Size: 483632 rows * 30 columns
      • Column names: 'X', 'Y', 'YEAR', 'INCIDENT_REPORT_ID', 'LOCATION', 'CITY', 'STATE', 'ZIP', 'X_COORD_PUBLIC', 'Y_COORD_PUBLIC', 'LATITUDE_PUBLIC', 'LONGITUDE_PUBLIC', 'DIVISION_ID', 'CMPD_PATROL_DIVISION', 'NPA', 'DATE_REPORTED', 'DATE_INCIDENT_BEGAN', 'DATE_INCIDENT_END', 'ADDRESS_DESCRIPTION', 'LOCATION_TYPE_DESCRIPTION', 'PLACE_TYPE_DESCRIPTION', 'PLACE_DETAIL_DESCRIPTION', 'CLEARANCE_STATUS', 'CLEARANCE_DETAIL_STATUS', 'CLEARANCE_DATE', 'HIGHEST_NIBRS_CODE', 'HIGHEST_NIBRS_DESCRIPTION', 'OBJECTID', 'Shape', 'GlobalID'
  • Durham:
  • Raleigh:
    • This dataset is updated daily. I will try to monitor these updates and continue collecting data until February 15th, 2024.

Considerations for Using the Data

Social Impact of Dataset

Discussion of Biases

Other Known Limitations

Rights reserved by governments.

Additional Information

Dataset Curators

For detailed information regarding the individuals involved in collecting the dataset and their affiliations, as well as any funding details, interested parties are encouraged to directly contact the respective government offices.

Licensing Information

The dataset from cities in North Carolina, including Cary, Charlotte, Durham, and Raleigh, is sourced from their respective open data portals, each with its specific licensing information and terms of use.

Cary's Open Data Portal operates under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license. This allows for both commercial and non-commercial use, distribution, and adaptation of the data, as long as proper attribution is given and any derived works are shared under the same terms.

While Durham and Charlotte's Open Data Portals do not specify a particular license, their websites state that the data is publicly accessible and can be freely used. Charlotte's portal serves as a resource for the public to explore, visualize, and download data, facilitating the creation of new applications and maps. Similarly, Durham's portal is dedicated to making all government data available for public use without restrictions.

Raleigh's Open Data Policy stipulates that by using data from their site, users agree to the terms and conditions described under the City of Raleigh Open Data Privacy Policy. The City of Raleigh makes no warranties regarding the completeness, accuracy, or timeliness of the data, and disclaims all express or implied warranties, including those of merchantability or fitness for a particular purpose. Users should be aware that the data format or schema may change as updates are made, and they use the information at their own risk.

Contributions

Thanks to Town of Cary, City of Charlotte, City of Durham, and City of Raleigh for providing the raw dataset.