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City Crime Trends Dataset

Government & Civic Records

Tags and Keywords

Crime

Statistics

Urban

Trends

Assault

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City Crime Trends Dataset Dataset on Opendatabay data marketplace

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Free

About

This dataset provides insights into urban crime statistics over a 21-year period, from 2000 to 2020. It records the number of occurrences for various crime types in a city, offering a valuable resource for analysing crime trends over time. The data can assist in identifying periods when specific crimes are more prevalent and is suitable for developing predictive models to estimate future crime likelihood.

Columns

  • Year: Indicates the year the crime was recorded, ranging from 2000 to 2020.
  • Type of Crime: Specifies the category of crime, including Assault, Burglary, Robbery, and Vehicle Theft. Other categories are also present, with Assault and Burglary each representing 26% of reported unique crime types, and "Other" making up 49%.
  • Number of Crimes: Represents the count of reported occurrences for each crime type in a given year. Values range from 105 to 6203, with a mean of approximately 1,700.

Distribution

The dataset is presented in a comma-separated value (CSV) format and has a file size of 1.7 kB. It consists of three columns and contains 82 valid records. There are no missing or mismatched values. The dataset is static, with no expected future updates.

Usage

This dataset is ideal for:
  • Analysing crime trends across a two-decade span.
  • Identifying patterns and hotspots for particular crime types.
  • Developing and testing predictive models for urban crime.
  • Statistical analysis of crime data.

Coverage

The data covers a time span of 21 years, from 2000 to 2020. The statistics are recorded for "a city," though a specific geographical location is not detailed in the available information.

License

CC0: Public Domain

Who Can Use It

  • Researchers: For academic studies on social science and crime patterns.
  • Data Analysts: To extract insights and visualise trends in urban safety.
  • Urban Planners: To inform policy decisions related to public safety.
  • Predictive Modellers: To build algorithms forecasting crime occurrences.

Dataset Name Suggestions

  • Urban Crime Statistics 2000-2020
  • City Crime Trends Dataset
  • Twenty-Year Urban Crime Data
  • Crime Occurrences Dataset (2000-2020)

Attributes

Original Data Source: City Crime Trends Dataset

Listing Stats

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LISTED

10/08/2025

REGION

GLOBAL

Universal Data Quality Score Logo UDQSQUALITY

5 / 5

VERSION

1.0

Free

Download Dataset in CSV Format