In this project, a Market Basket Analysis is conducted on a dataset (cafelepetit.csv), containing transaction information of items bought in a café in a busy city. Associative Rule Learning is used to find out rules about ‘people who bought X also bought Y’. Here, the Apriori model is employed to analyze the items ordered by customers of Cafelepetit. By tweaking the minimum support and confidence levels, successful insights were gleaned from the buying patterns of the customer.