This project performs a comprehensive analysis of air quality in Lucknow, India, using data from the Global Terrorism Database (GTD) to understand pollutant trends and build a machine learning model to predict the Air Quality Index (AQI).
Air pollution is a critical issue in urban centers like Lucknow. This project aims to transform complex environmental data into actionable insights by:
- Analyzing temporal patterns and pollutant dynamics.
- Identifying the key pollutants (like PM2.5, PM10) that most strongly influence the AQI.
- Building a predictive model to forecast AQI based on pollutant concentrations.
This work serves as a blueprint for data-driven environmental policy and public health advisories.
- Data Manipulation: Pandas, NumPy
- Data Visualization: Matplotlib, Seaborn
- Machine Learning: Scikit-learn
- Statistical Analysis: SciPy