🌍 Sustainable Spending Dashboard

What is 🌍 Sustainable Spending Dashboard?

A financial analytics tool that connects your spending data to climate impact. It uses LLMs to classify transactions, calculate carbon footprint, and enable automated carbon offset transfers via Bunq. Built for individuals who want to understand and reduce their environmental impact through everyday spending.

How to use 🌍 Sustainable Spending Dashboard?

Clone the repository, create a Python virtual environment, install dependencies from requirements.txt, and add a Bunq API key to a .env file. Then run streamlit run dashboard.py to launch the interactive dashboard.

Key features of 🌍 Sustainable Spending Dashboard

• Classify spending into intuitive categories.
• Calculate total CO₂ emissions and CO₂ per € spent.
• Assign a sustainability zone (Green / Yellow / Red).
• Visualize insights in a modern dashboard.
• Transfer offset amounts to a Bunq green account.
• Display motivational messages like “you planted 3 trees!”
• Show a gamified leaderboard comparing offset-to-spend ratios.

Use cases of 🌍 Sustainable Spending Dashboard

• Understand your personal carbon footprint from monthly expenses.
• Automate small offset transfers to a Bunq green account.
• Compete with peers on a sustainability leaderboard.
• Track progress toward more eco-friendly spending habits.

FAQ from 🌍 Sustainable Spending Dashboard

What data does it use?

It can analyze a sample transactions.csv file or connect to real Bunq accounts via the Bunq API key stored in .env.

What are the runtime requirements?

Python 3 with Streamlit, pydantic_ai, Gemini/OpenAI LLM access, Pandas, Matplotlib, and the Bunq SDK. All are listed in requirements.txt.

How is the sustainability zone determined?

Green (CO₂ per € < 0.4), Yellow (0.4–0.6), Red (> 0.6). The zone is displayed as a dynamic badge in the app.

Can I use it without a Bunq account?

Offset transfers require a Bunq account and API key. Other features (classification, CO₂ calculation, visualization) work with the sample data.

What LLMs are supported?

The dashboard uses Gemini and OpenAI via the pydantic_ai agent orchestration library for spending classification and CO₂ reasoning.