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data-visualisation Data Visualisation Project Academic Project An interactive data visualization project built with R, R Shiny, and ggplot2 for creating dynamic, explorable visualizations. An interactive data visualization project using R and R Shiny. 2026-01-05 1 Completed
R
R Shiny
Data Visualization
ggplot2
i-ph-chart-bar-duotone

::warning The project is currently in progress, and more details will be added as development continues. ::

This project involves creating an interactive data visualization application using R and R Shiny. The goal is to develop dynamic and explorable visualizations that allow users to interact with the data in meaningful ways.

🛠️ Technologies & Tools

  • R: A statistical computing environment, perfect for data analysis and visualization.
  • R Shiny: A web application framework for R that enables the creation of interactive web applications directly from R.
  • ggplot2: A powerful R package for creating static and dynamic visualizations using the Grammar of Graphics.
  • dplyr: An R package for data manipulation, providing a consistent set of verbs to help you solve common data manipulation challenges.
  • tidyr: An R package for tidying data, making it easier to work with and visualize.
  • tidyverse: A collection of R packages designed for data science that share an underlying design philosophy, grammar, and data structures.
  • sf: An R package for working with simple features, providing support for spatial data manipulation and analysis.
  • rnaturalearth: An R package that provides easy access to natural earth map data for creating geographical visualizations.
  • rnaturalearthdata: Companion package to rnaturalearth containing large natural earth datasets.
  • knitr: An R package for dynamic report generation, enabling the integration of code and text.
  • kableExtra: An R package for customizing tables and enhancing their visual presentation.
  • gridExtra: An R package for arranging multiple grid-based plots on a single page.
  • moments: An R package for computing moments, skewness, kurtosis and related statistics.
  • factoextra: An R package for multivariate data analysis and visualization, including PCA and clustering methods.
  • shinydashboard: An R package for creating dashboards with Shiny.
  • leaflet: An R package for creating interactive maps using the Leaflet JavaScript library.
  • plotly: An R package for creating interactive visualizations with the Plotly library.
  • RColorBrewer: An R package providing color palettes for maps and other graphics.
  • DT: An R package for creating interactive data tables.

📚 Resources

You can find the code here: Data Visualisation Code

And the online application here: Data Visualisation App

📄 Detailed Report