🌍 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