Small changes in food waste can lead to massive economic and environmental savings worldwide.
Data Source:
- Global Food Wastage dataset (Kaggle)
- GDP per Capita dastaset (World Bank)
This project focuses on answering various questions like:
- 🍗 What food category is wasted the most?
- 📈 What are the global food wastage trends?
- 🌐 What countries waste the most?
- 💵 What are the economic loss trends?
- 🔍 How does income level relate to food waste efficiency?
Besides visualization of the data, a predictive model was built to:
- Predict economic loss based on food waste
- Simulate a scenario where food waste is reduced by 10%
- Estimate the potential economic savings from reduced waste
To make the analysis more complete, GDP per Capita data was merged with the original dataset. This helped explore how a country’s income level affects how efficiently it manages food waste.
- 📊 Data Cleaning and Merging
- 🔎 Exploratory Data Analysis
- 📈 Data Visualization (Matplotlib, Seaborn)
- 🧠 Machine Learning Modeling (Random Forest Regressor)
- 💬 Insight Communication and Scenario Analysis
Reducing prepared food waste by just 10% globally between 2018–2024 could have saved approximately 1.75 trillion $ in economic losses, proving that smarter waste management could save huge amounts of money and protect the environment.