Featured Projects

Discover a variety of projects that reflect my experience with data analytics, visualisation, and geospatial techniques, spanning a range of tools including R, Python, and more.

Click Each tab to see the featured projects, and follow the link at the top for a more detailed walkthrough.

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• »Project 1« Interactive Shiny App in R: Visualising meteorological data through windroses for specific locations and time periods.

  • • Developed using Shiny for dynamic data visualisation.
  • • Allows users to explore weather trends with interactive windrose plots.
  • • Data input from specific meteorological stations and time periods.

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• »Project 2«

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  • Interactive Shiny App in R: Analysing infection rates and deaths during the COVID-19 pandemic.

  • Interactive Map: Users can select a region in Scotland to view COVID-19 data.
  • Time Series Plots: Visualize trends in infection rates and deaths over time.
  • Data Filters: Filter data by date range, health board, or specific metrics (e.g., cases, deaths, hospitalizations).

  • Colorblind-Friendly Design: The dashboard uses a custom color palette for better accessibility.

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• »Project 3«

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  • KPI Dashboard: Developed using Tableau to track and present key performance indicators for business operations.

  • Features interactive visualisations, custom filters, and drill-down capabilities.
  • Designed to monitor metrics such as revenue, customer satisfaction, and sales performance, using simulated data created in R.

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• »Project 4«

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  • GIS Visualisation: Leveraging R’s geospatial packages to analyse and visualise deforestation trends in Poland using the Global Forest Change (GFC) 2000-2023 dataset.

  • Features 3d map, time series analysis, and forest loss/gain visualisations.
  • Designed to raise awareness about deforestation and its environmental impact, inspired by the work of Simona Kossak and Milos Popovic.

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• »Project 5«

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  • Stock Market Analysis and Prediction: Leveraging Python’s data science libraries to analyze historical stock data and predict future prices.

  • Features data fetching, trend visualization, and predictive modeling using machine learning.

  • Designed to provide actionable insights for investors, using publicly available stock data from yfinance.

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