Carbon Footprint Optimisation of dishes (HashMap AIA and Apriori Version)

The dataset aims to facilitate research in the optimization of the carbon footprint of recipes. Consisting of 30 Excel files processed through various Python scripts and Jupyter notebooks, the dataset serves as a versatile resource for both performance analysis and environmental impact assessment. The unique attribute of this dataset lies in its ability to calculate representative values of carbon footprint optimization through multiple algorithmic implementations. This enables the research community to understand the trade-offs and benefits associated with different optimization strategies. It should be noted that the dataset is specifically configured for the initial set of data based on "Courtepaille" recipes. Users intending to employ different datasets must make appropriate code modifications to ensure correct execution. Therefore, potential limitations exist in terms of the extensibility of the dataset for different types of culinary data. While associated publications are not yet available, they are forthcoming, underscoring the dataset's value in advancing the domain of carbon footprint optimization in food recipes.