https://github.com/0xnu/gb-road-casualties
An analysis of UK road accident statistics from the RAS91 dataset covering 2015-2024.
https://github.com/0xnu/gb-road-casualties
casualties dft great-britain road transport uk
Last synced: 9 months ago
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An analysis of UK road accident statistics from the RAS91 dataset covering 2015-2024.
- Host: GitHub
- URL: https://github.com/0xnu/gb-road-casualties
- Owner: 0xnu
- License: other
- Created: 2025-08-21T12:18:16.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-21T12:28:50.000Z (10 months ago)
- Last Synced: 2025-09-06T10:54:51.885Z (9 months ago)
- Topics: casualties, dft, great-britain, road, transport, uk
- Language: Jupyter Notebook
- Homepage:
- Size: 1.39 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Codeowners: CODEOWNERS
- Security: SECURITY.md
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README
## gb-road-casualties
[](https://github.com/0xnu/gb-road-casualties/releases/latest)
[](/LICENSE)
An analysis of UK road accident statistics from the RAS91 dataset covering 2015-2024.
### What It Does
It analyzes UK road accident statistics from the RAS91 dataset covering 2015-2024. It provides:
+ Analysis of road casualties by various demographics
+ Trends and patterns in road accidents over time
+ Breakdown by road user type, severity, age, sex, and geographical regions
+ Statistical insights and visualizations of accident data
### Key Features
#### 📊 Data Extraction & Processing
+ Automated extraction from RAS91 ODS files to CSV format
+ Multiple datasets: Numbers, Age/Sex, Severity, Monthly, Local Authority, and Regional data
+ Data cleaning and preprocessing for analysis
+ Structured data organization for easy access
#### 🔍 Statistical Analysis
+ Year-over-year trend analysis (2015-2024)
+ Demographic breakdown by age groups and sex
+ Severity classification (Killed, KSI, All casualties)
+ Road user type analysis (Pedestrians, Cyclists, Motorists, etc.)
+ Geographical analysis by local authorities and regions
#### 📈 Data Visualization
+ Time series plots of accident trends
+ Demographic distribution charts
+ Severity comparison visualizations
+ Geographical heat maps and regional comparisons
+ Interactive plots using Matplotlib and Seaborn
#### 📋 Dataset Coverage
+ Numbers: 32 rows, 12 columns - Overall casualty statistics
+ Age/Sex: 384 rows, 14 columns - Demographic breakdown
+ Local Authority: 852 rows, 14 columns - Geographical analysis
+ Monthly: 440 rows, 15 columns - Temporal trends
+ Severity: 176 rows, 13 columns - Accident severity classification
+ Regional: 48 rows, 13 columns - Regional comparisons
### Install Dependencies
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install required libraries:
```sh
# Prerequisites
python3 -m venv .venv
source .venv/bin/activate
pip install pandas numpy matplotlib seaborn scikit-learn openpyxl odfpy jupyter
```
### Data Requirements
It requires the RAS91 ODS file from the UK Department for Transport to run the analysis.
+ File: `ras91.ods` (placed in the data/ folder)
+ Source: [Reported road casualties Great Britain, provisional results: 2024](https://www.gov.uk/government/statistics/reported-road-casualties-great-britain-provisional-results-2024)
+ The script automatically extracts and processes the data into CSV format
### Run the System
Click the `Run` button to run the individual cell of the [Jupyter Notebook](./road_casualties.ipynb).
### License
This project is licensed under the [Modified MIT License](./LICENSE).
### Copyright
(c) 2025 [Finbarrs Oketunji](https://finbarrs.eu). All Rights Reserved.