This repository presents a collection of projects focused on providing appropriate visualizations of data on interactive dashboards. It acts as a navigation hub that explains each project and links to its dedicated implementation repository.
- Posters (R + Python)
- Spotify Shared Music Dashboard (Python)
- CryptoStock Prediction Dashboard (Python + Apache tools)
- NYC-Citibike Dashboard (R)
Outcome: Three publication-styled posters translating technical and empirical analyses into clear, visually compelling stories across network science, machine learning, and sports economics.
➡️ Repository: Posters
Problem: How can shared music listening patterns between users or groups be visualized in an intuitive and exploratory way?
Outcome: A user-friendly interactive flow chart that reveals overlap in music preferences and listening habits across individuals or groups.
➡️ Repository: Spotify_Dashboard
Spotify.Dashboard.mp4
Problem:
How can real-time and historical market data be combined into meaningful visualizations that drive the decision-making of traders?
Outcome:
An IaaC service that provided real-time crypto and stock market data on a dashboard with predictions of a price for the next time window.
➡️ Repository: CryptoStockPrediction
Crypto.Dashboard.mp4
Problem: How did the COVID-19 pandemic affect bicycle usage patterns in New York City, and how does bike traffic vary spatially across neighborhoods and time of day?
Outcome: An interactive Shiny dashboard enabling users to explore temporal and spatial bike usage patterns in NYC, supporting intuitive comparison across years, locations, and time windows.
➡️ Repository: NYC---bikes-analysis
These projects were developed as part of my university coursework during the following classes:
- Spotify Dashboard - Data Visualisation Techniques
- Cryptocurrency & Stock Markets Dashboard - Big Data Analytics
- Posters - Data Visualisation Techniques, Social Networks and Recommendation Systems
- NYC-Citibike Dashboard - Structured Data Processing