Cities of Tomorrow – Urban Sustainability Notebook (Fabric Contest Submission)
This notebook explores how modern cities evolve, grow, and maintain sustainability using the Sustainable Urban Planning & Landscape Dataset.
The analysis focuses on identifying patterns in urban density, green area ratios, pollution levels, renewable energy adoption, transport efficiency, and livability indicators.Key Features of the Notebook
Cleaned and prepared the dataset
Performed Exploratory Data Analysis (EDA) using Python
Visualized sustainability patterns across cities
Identified correlations among key indicators
Built a simple ML clustering model (K-Means)
Created insights on how cities can become greener, smarter & more livable
Questions Explored
How do green areas affect pollution and livability?
What makes a city sustainable?
Which cities balance growth and environment best?
Can we classify cities into sustainability groups using ML?
Tools Used
Python (Pandas, Matplotlib, Seaborn, Scikit-Learn)
Fabric Data Science Notebook
Sustainable Urban Planning Dataset (Kaggle)
Conclusion
This notebook tells the story of how cities can prepare for a smarter, greener, more sustainable future through data-driven insights.
https%3A%2F%2Fgithub.com%2Fmayanksonagara94-rgb%2F-Cities-Of-Tomorrow-.git
