🔋 Energy Consumption Dashboard

Welcome to the Energy consumption monitoring challenge. In this exercise, you will transform raw data from European demo sites into a live, interactive dashboard. This exercise demonstrates the "value chain" of Renku for data science: moving from a static dataset to a decision-support tool while ensuring every step is reproducible.

1. Renku’s added value: why this approach?

In typical data projects, we can find a gap between the data scientist's notebook and the final dashboard. Renku bridges this gap by:

• Decoupled data, code and compute: We use Data Connectors to link to the large Excel files (hosted on Zenodo) rather than bloating our Git repository with binary files.
• Instant deployment: By using Session Launchers, we turn a Python script into a web application (Streamlit) that others can access without installing Python locally.

2. Step-by-step guide

To "bring this project to life," follow these two phases:

Phase A: Connecting the data

1. Follow the steps to add a new data connector for a data repository: https://docs.renkulab.io/en/latest/docs/users/data/guides/connect-data/connect-data-from-data-repositories
2. Visit the URL for the GEO4CIVHIC dataset: https://zenodo.org/record/4651327 and copy the DOI URL
3. Be aware that the Mount Path is automatically assigned when bringing a global data connector.

Phase B: Creating a session launcher for the code

1. Go to Sessions > Session Launchers in the Renku UI.
2. Click New Launcher and use these settings:
   • Title: Energy Consumption Dashboard
   • Command: streamlit run src/energy_app.py --server.port 8501
3. Click Launch. A new browser tab will open showing the live load profiles for the demo sites.
4. Modify the code