Market basket analysis is a data mining technique that helps businesses discover the patterns and associations among the products that customers buy together. Using the Apriori algorithm, businesses can efficiently generate and evaluate the rules describing how often and how strongly the products are related. For example, if customers who buy bread also tend to buy butter, the "Bread -> Butter" rule can be derived and used for marketing purposes.

In this report, I will explain the principles of market basket analysis and how to use the Apriori algorithm in Python. I will also demonstrate the implementation and results of the algorithm on a sample dataset of supermarket transactions.

Because the dataset had too few columns, we did not make any visualizations for the project.