Global Terrorism Analysis

Exploratory data analysis of the Global Terrorism Database (1970–2017) with interactive and static Python visualizations.

Course: Big Data Visualization, Machine Learning MSc, Semester 2
Team: Ghinea Andrei-Robert & Diaconu Bianca
Dataset: Global Terrorism Database (GTD)

This repository contains a Jupyter notebook that analyzes the Global Terrorism Database (GTD), generating interactive and static visualizations to highlight terrorist activity trends across time, regions, and groups.

---

Project Paper

A detailed scientific paper documenting the methodology, results, and discussion for this analysis is included in the repository:

• Global Terrorism Analysis.pdf — Final report with all figures, findings, and references.
• All Overleaf (LaTeX) source files are located in the Paper directory.

---

Dependencies

• All required Python packages are listed in requirements.txt.
• Install them with:

  pip install -r requirements.txt

• This project was tested with Python 3.11.

---

How to Run

1. Clone or download this repository.
2. Launch Jupyter and open the notebook:

   jupyter notebook gtd_analysis.ipynb

3. Execute all cells in order.

---

Visualization Structure

• Number of Terrorist Attacks per Year
• Correlation between Attacks and Fatalities per Year
• Monthly Seasonality of Attacks
• Top 25 Countries by Number of Attacks (Word Cloud)
• Terrorist Attacks per Year by Region
  • Continuous “Heatmap” of Attacks by Year & Region (Top 5 + Other)
  • Average Terrorist Attacks per Year by Region (Top 5 + Other)
• Global Terrorist Attacks by Country (Choropleth via Plotly)
• Top 10 Terrorist Groups by Number of Attacks
• Attacks per Year for Top 5 Terrorist Groups

---

License

This project is licensed under the MIT License. See the LICENSE file for details.