Data visualisations are a powerful tool that let people see trends and patterns in complex statistical findings. This project aims to create an interactive web application that visualises the effect of student commute length on attendance and overall academic performance. The data gathered from the University of Westminster was transformed and analysed using the R language for statistical computing. Visualisations were created using the JavaScript chart library, D3.js. Relevant research was undertaken to gather requirements on the most effective visualisation techniques. While also gathering an understanding of the fundamental principles of designing effectively for accessible users, particularly those with visual impairments. The findings from this research show that there is a positive relationship between student attendance and academic performance, but no correlation between commute length and attendance.
View the website here: https://evisat.github.io/6COSC006W-data-vis/dist/index.html
Data Analysis: https://github.com/evisat/rdata-6COSC006W
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Run git clone https://github.com/evisat/6COSC006W-data-vis.git to get a copy of the project on your device.
Run npm install to setup.
Run npm run dev to build project for development.
Run npm run start to build with live reloading.
Run npm run build to build project for publication.
This project is licensed under the MIT License - see the LICENSE.md file for details