The relationship between property prices and proximity to public transport is a well-documented phenomenon in urban studies. Properties located near public transport hubs often command higher prices due to the convenience and accessibility they offer. Understanding this relationship can provide valuable insights for real estate investors, urban planners, and policymakers.

Bundles of 2 or more products will be searched in order to be put on sale together. This is a common practice by markets in order to boost sales of less desired products. As we do not possess the exact sales data of the products contained in the set, we will choose a few products from the less prevalent segment. In order to achieve the desired output, market basket analysis will be conducted with the usage of the Apriori algorithm.

Beer to me was always a filler drink, used as a basis for socialization, an appetizer for a good meal or a beverage to go along with sporting events. Never was it an experience in itself, which can be attributed to the fact that I could never distinguish between beers, with all of them falling into the 'good' category. This paper aims to change that using Multi-Dimensional Scaling, with an addition of PAM clustering, to find the most unique beers there are.

This document tries to search for similarities in sales data between Walmart stores. This might be useful in applying business strategies to certain locations, proving which stores are bound to be shut down and which are worth investing into. The data was taken from Kaggle (https://www.kaggle.com/datasets/ujjwalchowdhury/walmartcleaned). Among others, it contains weekly sales from each department of a certain store. The number of stores amounts to 45 in total. Three methods of clustering will be compared: K-means, Clara and PAM.