Using the WineQT.csv dataset, evaluate various clustering algorithms by applying K$-$Means with Euclidean distance and K$-$Medoids with Manhattan distance. Follow the procedure discussed in class to determine the optimal number of clusters based on the optimality criteria. Create the corresponding cluster plots and compute the cluster centroids $($or medoids$).$ Briefly summarize your observations based on the results from these four methods.