This project analyzes the distribution of electric vehicle (EV) charging stations and population density across Berlin's postal codes. Using geospatial visualization, it identifies potential areas needing additional charging infrastructure. The project is built with Streamlit for interactivity and data visualization.
- Interactive heatmaps: Visualize EV charging station density and population distribution.
- Data-driven insights: Identify underserved areas for potential infrastructure expansion.
- Streamlit app: User-friendly interface for analysis and exploration.
- Python: Core programming language.
- Pandas & Geopandas: Data manipulation and geospatial analysis.
- Streamlit: Web application framework.
- Matplotlib & Plotly: Visualization tools.
- OpenStreetMap: Basemap and geospatial data.
- Clone the repository: git clone https://github.com/yourusername/ev-charging-analysis.git
- Install the depandancies: pip install -r requirements.txt
- Run the Application streamlit run app.py