https://github.com/andreighinea1/bdv-project
Exploratory analysis of the Global Terrorism Database (GTD) using Python and Jupyter. This project visualizes global terrorist activity trends from 1970 to 2017, highlighting patterns across time, regions, and groups using ML techniques.
https://github.com/andreighinea1/bdv-project
data-visualization exploratory-data-analysis jupyter-notebook kaggle-dataset terrorism-analysis
Last synced: 8 months ago
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Exploratory analysis of the Global Terrorism Database (GTD) using Python and Jupyter. This project visualizes global terrorist activity trends from 1970 to 2017, highlighting patterns across time, regions, and groups using ML techniques.
- Host: GitHub
- URL: https://github.com/andreighinea1/bdv-project
- Owner: andreighinea1
- Created: 2025-06-01T14:55:32.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-06-01T17:22:03.000Z (about 1 year ago)
- Last Synced: 2025-06-02T03:15:48.085Z (about 1 year ago)
- Topics: data-visualization, exploratory-data-analysis, jupyter-notebook, kaggle-dataset, terrorism-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 5.06 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 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)](https://www.kaggle.com/datasets/START-UMD/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](Paper/Global%20Terrorism%20Analysis.pdf) — *Final report with all figures, findings,
and references.*
* All Overleaf (LaTeX) source files are located in the [Paper](Paper) directory.
---
## Dependencies
* All required Python packages are listed in [`requirements.txt`](requirements.txt).
* Install them with:
```bash
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:**
```bash
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](LICENSE) file for details.