Official UK police crime data by postcode, including crime types, locations, and outcomes

This method returns total crime rates, crime rates by crime types, area ratings by total crime, and area ratings by crime type for small areas (Lower Layer Super Output Areas, or LSOAs) and Local Authority Districts (LADs). The results are determined by the inclusion of the submitted postcode/coordinates/UPRN within the corresponding LSOA or LAD.

All figures are annual (for the last 12 months).

The crime rates are calculated per 1,000 resident population derived from the census 2021.

The dataset is updated on a monthly basis, with a 3-month lag between the current date and the most recent data.

Visit the interactive Crime Mapping Tool and prepare your own tailored crime report showing the latest maps, graphs and data on crimes, victims and offenders in NSW LGAs, suburbs or postcodes.

*Note: prior to June 2021 there were three additional crime tools available providing data for Local Government Areas on crime trends, crimes by premises and LGA crime rankings. These tools are no longer supported; this information is available in the Crime Mapping Tool.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

Quarterly recorded crime reports and datasets

The quarterly recorded crime reports are available from 2004 and annually from 1997. They contains statistics and graphs relating to the 62 offences BOCSAR reports on, with trends rates and ratios for LGAs and Statistical Areas.

The datasets are produced quarterly for all of NSW and broken down by LGA, postcode and suburb for the 62 offences. The data includes incident counts by month from 1995

In 2023/24 the crime rate of Northern Ireland stood at 55 crimes per 1,000 people, with the policing district of Belfast City having the highest crime rate of 96 crimes per 1,000 people.

This dataset provides detailed information on the 2019 Index of Multiple Deprivation (IMD) for Birmingham, UK. The data is available at the postcode level and includes the Lower Layer Super Output Area (LSOA) information.Data is provided at the LSOA 2011 Census geography.The decile score ranges from 1-10 with decile 1 representing the most deprived 10% of areas while decile 10 representing the least deprived 10% of areas.The IMD rank and decile score is allocated to the LSOA and all postcodes within it at the time of creation (2019).Note that some postcodes cross over LSOA boundaries. The Office for National Statistics sets boundaries for LSOAs and allocates every postcode to one LSOA only: this is the one which contains the majority of residents in that postcode area (as at 2011 Census).

The English Indices of Deprivation 2019 provide a detailed analysis of relative deprivation across small areas in England. The Crime Deprivation dataset is a key component of this index, measuring the risk of personal and material victimization at the local level. This dataset includes indicators such as recorded crimes for violence, burglary, theft, and criminal damage. It helps identify areas with high levels of crime, guiding policy interventions and resource allocation to improve safety and reduce crime rates.

Level of education, social benefits claimants and crime suspects by 4-digit postcode zone, 2011-2012 (Dutch only)

Open Postcode Geo is a postcode dataset and API optimised for geocoding applications. You can use Open Postcode Geo to geocode a dataset, geocode user input, and therefore build a proximity search.

Data is derived from the ONS (Office for National Statistics) postcode database and is free to use, subject to including attributions to ONS, OS (Ordinance Survey) and Royal Mail.

Information is also provided on a range of topics, including education, health, crime, business, etc.

Postcodes can be entered at area, district, sector, and unit level - see Postcode map for the geographical relationship between these.

Postcode-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to …Show full descriptionPostcode-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to police in that respective financial year. For more information please see the original spreadsheet. Source: The data was downloaded from data.sa.gov.au and summarised by the Adelaide Data Hub to generate monthly Crime Statistics datasets at Offence Level 3. The data was spatialised using South Australian suburbs boundaries which was dissolved to reflect the postcode boundaries. Copyright attribution: Government of South Australia - South Australian Police, (2020): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)

Dataset Description: South Australia Crime Data 2022-2023🕵️‍♂️

Overview: Dive into the depths of criminal activities with the South Australia Crime Statistics 2022-2023 dataset. This comprehensive collection encapsulates a detailed breakdown of crimes reported across various suburbs, offering insights into offences against persons and properties. Ideal for enthusiasts and practitioners of data science, criminology, and policy-making, this dataset opens up possibilities for a wide array of analyses.

What We Can Do with the Data: - Perform trend analysis to understand crime patterns over time. - Conduct geographical analysis to identify crime hotspots. - Explore relationships between different types of crimes. - Develop predictive models for crime occurrence or escalation. - Inform public policy and community safety strategies.

Column Descriptors: - Reported Date: Date of crime report (e.g., 01/07/2022). - Suburb - Incident: Suburb where the incident occurred. - Postcode - Incident: Postcode of the incident location. - Offence Level 1 Description: Broad categorization of the offence. - Offence Level 2 Description: More specific categorization of the offence. - Offence Level 3 Description: Detailed description of the offence. - Offence count: Number of times the offence occurred.

Tips for Processing Data: - Convert 'Reported Date' to datetime format for any time-series analysis. - Handle missing values in 'Suburb - Incident' and 'Postcode - Incident'. - Check and clean any duplicate or inconsistent records. - Consider normalizing or standardizing 'Offence count' if used in predictive modeling.

Acknowledgements: We extend our deepest gratitude to the South Australian authorities and South Australian Police for their commitment to transparency and public safety by making this dataset available. Your dedication greatly aids in educational, social, and scientific advancements.

For more information and to access the original dataset, please visit the South Australia Crime Statistics.

By delving into this dataset, you're not just learning about data manipulation and analysis; you're also uncovering the stories behind the numbers, contributing to a safer and more informed community. Happy analyzing!