okay solet' go ahead and compute the first half of item-based collaborative filteringwhich is finding similarities between items download and open the jnjmbs pwjftjqzoc file in this casewe're going to be looking at similarities between moviesbased on user behavior andwe're going to be using some real movie rating data from the grouplens project grouplens org provides real movie ratings databy real people who are using the pwjf-fotpsh website to rate movies and get recommendations back for new movies that they want to watch we have included the data files that you need from the grouplens dataset with the course materialsand the first thing we need to do is import those into pandas dataframeand we're really going to see the full power of pandas in this example it' pretty cool stuff