This repository contains a Jupyter Notebook that performs a geospatial and temporal analysis of reported conflict events between India and Pakistan during May 2025. The data includes multiple event types, casualty figures, and coordinates, curated from publicly available news and reporting sources.
- Data Cleaning & Structuring: Processes raw event data for spatial and temporal aggregation.
- Macro vs Micro Location Mapping: Differentiates general areas (e.g., cities) and pinpoint sites (e.g., mosques).
- Casualty Summarization: Groups and visualizes civilian and non-civilian impact.
- Time Trend Analysis: Visualizes escalation patterns and high-intensity days.
- Folium Maps: Interactive geospatial maps showing event severity.
- Insightful Commentary: Each step includes context and interpretations to support understanding and further use.
| File | Description |
|---|---|
Final_With_Time_Trend_Indian_Attack_May7.ipynb |
Annotated notebook with cleaned logic, insights, and time series trend |
events_with_viewpoints.csv |
Raw input dataset used for analysis |
README.md |
This project overview and documentation |
- The dataset is a snapshot of an evolving conflict, and not all events may be fully validated.
- Source information is compiled from multiple public platforms, and some discrepancies may exist.
- This notebook is intended for exploratory and research purposes.
- Integrate event-type-level filtering (e.g., airstrike vs reconnaissance)
- Incorporate sentiment or credibility scoring of sources
- Automate data ingestion from RSS feeds or APIs
- Create a dashboard or public visualization site
Developed by Adam Kureshi as part of a rapid situational analysis using Python and open-source geospatial tools.
All insights and conclusions are drawn from publicly available data as of May 2025.
MIT License – you are free to use, modify, and distribute this for academic or open-source use with attribution.