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🌍 Interactive World Map & Volcano Visualizer

A dynamic web-based map built with Python that visualizes geographical data. This project maps out volcano locations and international borders using specialized data formats like JSON and Text files.

✨ Features

  • Dynamic Map Generation: Automatically creates an interactive Map1.html file.
  • Data Integration: Parses coordinates from Volcanoes.txt and geographical boundaries from world.json.
  • Marker Clustering & Styling: Custom markers to identify specific points of interest (Volcanoes).
  • Layer Control: Ability to toggle different data layers on the map for a cleaner view.

🛠️ Tech Stack

  • Language: Python 3.x
  • Libraries: * Folium (For generating Leaflet.js maps)
    • Pandas (For data manipulation and reading files)
    • JSON (For parsing world boundary data)

🚀 How It Works

  1. The script reads the Volcanoes.txt file to extract Latitude, Longitude, and Name.
  2. It uses the world.json file to draw polygonal boundaries of different countries.
  3. Folium then layers this data onto an interactive map that can be opened in any web browser.

📖 Getting Started

Installation

You will need to install the required libraries first:

pip install folium pandas

Usage

  1. Clone the repository:
git clone [https://github.com/wajiharubab648-coder/interactive-data-map.git](https://github.com/wajiharubab648-coder/interactive-data-map.git)
  1. Run the script:
python app2.py
  1. Open the generated Map1.html in your browser to view the result.

🛤️ Future Roadmap

  • Add real-time weather data overlay.
  • Implement search functionality for specific locations.
  • Color-code markers based on volcano elevation or status.

💡 Lessons Learned

  • Handling Geospatial Data and understanding Coordinate systems.
  • Working with different file formats (.txt, .json, .html) in a single project.
  • Visualizing complex datasets to make them user-friendly.

Developed by Wajiha | BSIT Student | Python & Data Visualization

About

An interactive geospatial map application built with Python, Folium, and Pandas to visualize geographic data layers, markers, and spatial datasets.

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