Air Quality Analysis

Abstract

1. Introduction

Jupyter notebooks and Python code for analyzing air quality (fine particles, PM2.5)

2. Objective

Jupyter notebooks and Python code for analyzing air quality (fine particle, PM2.5)

This project demonstrates how HTML, Pandas, Python can be applied to a real-world Data Science problem.

4. Technology Stack

• a detour to look at conversion of wind data (U, V) vectors to speed and direction in degree
• how to use MetPy packages calculate such conversion instead of manually undertake
• explore data for the next which is selecting relevant data for predicting PM2.5
• some graph examples:
• relation of height (to the ground) vs. pressure
• compare values from different sources (such as from observed station, a public API, or reanalysis product)
• correlation of wind speed in different altitude to PM2.5 concentration
• the analysis is carried out on Jupyter Notebook (and later with Jupyter Lab 2.2), Ubuntu 18.04LTS.

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• A modern web browser
• VS Code or any code editor
• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/bi2air/air-quality-analysis.git
cd air-quality-analysis

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by bi2air and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.