Overview:

This project aims to tackle the critical issue of food waste and emissions throughout the food supply chain. By addressing food waste, we can make significant strides in reducing environmental impact, conserving resources, improving food security and fighting worldwide hunger.

1. Data Collection:

   1. Sources:
      1. df_final_demo.csv
      2. df_final_web_data_pt_1.csv
      3. df_final_web_data_pt_2.csv
      4. df_final_experiment_client.csv

2. Datasets categories:

   1. Client Profiles (df_final_demo): Demographics like age, gender, and account details of our clients.
   2. Digital Footprints (df_final_web_data): A detailed trace of client interactions online, divided into two parts: pt_1 and pt_2.
   3. Experiment Roster (df_final_experiment_clients): A list revealing which clients were part of the grand experiment.

3. KPIs & Metrics:

   1. Completion Rate
   2. Time Spent on Each Step
   3. Error Rates

4. Visualization:

   1. Charts and Graphs: Used countplots, barcharts and heatmaps to better visualize key data points on our KPIs.

5. Tools and Software:

   1. Data Analysis Tools: Python, Jupyter notebook
   2. Data Visualization Tools: EDA tools from python libraries (matplotlib, plottyexpress and seaborn) and Tableau