yakubuta/sahel-security-dashboard

Interactive conflict intelligence dashboard visualizing armed violence across the Lake Chad Basin (Nigeria, Niger, Chad, Cameroon) 2015–2024 | Python · Streamlit · Folium · UCDP Data # 🛡️ Lake Chad Basin Security Dashboard An interactive conflict intelligence dashboard visualizing armed violence across the Lake Chad Basin region (Nigeria, Niger, Chad, and Cameroon) from 2015 to 2024. Built with Python and Streamlit using open-source conflict event data from the Uppsala Conflict Data Program (UCDP). Live Demo: View Dashboard ## 📸 Screenshots ## ✨ Features - **Interactive Conflict Map** — heatmap and clustered marker views with event popups - **Timeline Analysis** — monthly conflict trends colored by death toll - **Violence Type Breakdown** — state-based, non-state, and one-sided civilian targeting - **Most Affected Regions** — state and province level ranking - **Deadliest Conflicts** — top armed group confrontations by fatalities - **Filterable Data Table** — drill down into raw event records - **Sidebar Filters** — filter by country, year range, and violence type --- ## 📊 Data Source **UCDP Georeferenced Event Dataset (GED) Global v25.1** Uppsala Conflict Data Program — Uppsala University, Sweden 🔗 ucdp.uu.se > Sundberg, Ralph and Erik Melander (2013) Introducing the UCDP Georeferenced Event Dataset. *Journal of Peace Research* 50(4). Coverage: 8,019 conflict events across the Lake Chad Basin (2015–2024) Total deaths recorded: 54,391 | Civilian deaths: 13,767 --- ## 🗺️ Region Coverage | Country | Events | |---------|--------| | Nigeria | 5,232 | | Cameroon | 2,049 | | Niger | 575 | | Chad | 163 | Key conflict zones: Borno State, Far North Region (Cameroon), Tillabéri Region (Niger), Diffa Region --- ## 🚀 Getting Started ### 1. Clone the repository ```bash git clone github.com cd sahel-security-dashboard ``` ### 2. Install dependencies ```bash pip install -r requirements.txt ``` ### 3. Download the data - Download **UCDP GED Global v25.1** CSV from ucdp.uu.se - Place the file in the project root folder - Run the data pipeline: ```bash py …