This project explores how cities balance growth, sustainability, and livability using the Sustainable Urban Planning & Landscape Dataset. The goal is to understand what makes a city “future-ready” through simple data cleaning, visual exploration, and a custom Sustainability Score.
- Basic data cleaning and preparation
- Exploratory Data Analysis (heatmaps, scatterplots, rankings)
- A simple Sustainability Score combining green area, energy, transport, and pollution
- Clustering cities based on sustainability patterns
- Clear markdown explanations and insights
Microsoft Fabric Notebooks, Python, Pandas, Seaborn, Matplotlib, Scikit-Learn
The notebook highlights how greener cities often show lower pollution, stronger livability, and more balanced urban growth. It’s a beginner-friendly exploration aimed at learning and storytelling—not just coding.
