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🌍 AtmosTrace

AtmosTrace is a data exploration project focused on climate trends across cities, states, and countries using historical temperature datasets. It includes preprocessing, visualization, and insights based on global land temperature data.

📁 Folder Structure


AtmosTrace/
├── data/
│   ├── \_GlobalTemperatures.csv
│   ├── \_TemperaturesByCountry.csv
│   ├── \_TemperaturesByMajorCity.csv
│   ├── \_TemperaturesByState.csv
│   └── archive.csv
├── notebook/
│   └── air\_quality.ipynb
├── .gitattributes
├── .gitignore
├── README.md
└── requirements.txt

📊 Features

  • 🧹 Clean and structure large CSV datasets (climate data)
  • 📈 Visualizations using Python (matplotlib, seaborn)
  • 📓 Interactive notebook for air quality & temperature analysis
  • 🗂️ Multiple granularity levels: Country, State, City
  • 📦 Git LFS used for large file storage

📦 Datasets Used

All datasets are sourced from Berkeley Earth and preprocessed into:

  • GlobalTemperatures.csv
  • TemperaturesByCountry.csv
  • TemperaturesByMajorCity.csv
  • TemperaturesByState.csv

Note: Datasets are tracked using Git LFS due to size.

🚀 Getting Started

1. Clone the Repository

git clone https://github.com/Akrishna4/AtmosTrace.git
cd AtmosTrace

2. Install Required Packages

pip install -r requirements.txt

3. Open the Notebook

cd notebook
jupyter notebook air_quality.ipynb

🛠 Tech Stack

  • Python 3.x
  • Jupyter Notebook
  • pandas
  • matplotlib, seaborn
  • Git & Git LFS

✅ To Do / Future Enhancements

  • 📊 Add interactive dashboard (Streamlit or Plotly)
  • 🌱 Time-series modeling for forecasting temperature change
  • 🧠 Integrate basic ML models to detect anomalies
  • 🌍 Air quality index mapping by region

🤝 Contributing

Feel free to fork, suggest improvements, or open issues. Collaboration is welcome!

👤 Author

Ayush Krishna 📌 GitHub: @Akrishna4