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This Flask application visualizes European population, mortality, and temperature data interactively on a map using Leaflet on the frontend and Chart.js for time series. It supports multi-scale zoom and analysis, with additional granularity for Vienna at the NUTS-3 level.
It is hosted on Python Anywhere for easy access and exploration.
This project provides an interactive dashboard using Flask and Folium to explore the Climate Change Effect on Europe (CCEE):
See the project structure here: http://danielprecioso.com/Climate-Change-Effect-on-Europe/
├── data/ # Input and downloaded data
├── scripts/ # Data processing scripts
├── static/ # JS, CSS, assets
├── templates/ # HTML views
├── app.py # Flask server
├── requirements.txt
└── README.md
git clone https://github.com/daniprec/Climate-Change-Effect-on-Europe.git
cd Climate-Change-Effect-on-Europe
Scenario | File to install | Typical use |
---|---|---|
Run the web app only | requirements.txt |
PythonAnywhere / prod |
Do data prep, notebooks, model fitting | requirements‑dev.txt |
Local dev / CI |
# minimal runtime stack
pip install -r requirements.txt
# OR full analytics stack
pip install -r requirements‑dev.txt
This makes the ccee
library importable:
pip install .
Editable mode for active development:
pip install -e .
python app.py
Open your browser at http://127.0.0.1:5000/ to explore the interactive map.
Tips:
If you work in a virtual‑env, create and activate it before step 2.
python -m venv .venv && source .venv/bin/activate
For hot‑reload during development, set FLASK_ENV=development
or run
flask --app app run --debug
On PythonAnywhere deploy only requirements.txt
to keep the footprint small; use requirements‑dev.txt
locally for notebooks and batch jobs.
Most of the data used in this project is available through public APIs or data portals. You can build the files used by the map just by running:
python scripts/build_geojson.py
python scripts/build_csv.py
The only data that needs to be downloaded manually is the CORDEX CMIP data, which requires a WGET script. Below are the instructions for downloading and preparing the data.
Pipeline overview diagram – docs/pipeline_overview.md
Step-by-step data & script details – docs/pipeline_details.md
This project is licensed under the MIT License, permitting reuse with attribution. Feel free to fork and adapt for academic or personal use.
For questions or suggestions, feel free to reach out:
We welcome feedback and contributions-help us grow this project!