nowideallywe' also filter out star warsyou don' want to be looking at similarities to the movie itself that you started frombut we'll worry about that latersoif you want to play with this little bit morelike said was sort of an arbitrary cutoff for the minimum number of ratings if you do want to experiment with different cutoff valuesi encourage you to go back and do so see what that does to the results you knowyou can see in the preceding table that the results that we really like actually had much more than ratings in common sowe end up with "vtujo pxfst *oufsobujpobm bopg ztufsz coming in there pretty high with only ratings so maybe isn' high enough jopddijp snuck in at not very similar to star warssoyou might want to consider an even higher threshold there and see what it does please keep in mind toothis is very smalllimited dataset that we used for experimentation purposesand it' based on very old dataso you're only going to see older movies sointerpreting these results intuitively might be little bit challenging as resultbut not bad results now let' move on and actually do full-blown item-based collaborative filtering where we recommend movies to people using more complete systemwe'll do that next making movie recommendations to people okaylet' actually build full-blown recommender system that can look at all the behavior information of everybody in the systemand what movies they ratedand use that to actually produce the best recommendation movies for any given user in our dataset kind of amazing and you'll be surprised how simple it is let' golet' begin using the *ufn#btfe$'jqzoc file and let' start off by importing the movielens dataset that we have againwe're using subset of it that just contains , ratings for now butthere are larger datasets you can get from grouplens org-up to millions of ratingsif you're so inclined keep in mind thoughwhen you start to deal with that really big datayou're going to be pushing the limits of what you can do in single machine and what pandas can handle without further adohere' the first block of codejnqpsuqboebtbtqe @dpmt sbujoht qesfbe@dtw tvoephdpotvmuqbdluebubtdjfodfnm  ebub tfq = obnft @dpmtvtfdpmt sbohf @dpmt npwjft qesfbe@dtw tvoephdpotvmuqbdluebubtdjfodfnm  jufn tfq obnft @dpmtvtfdpmt sbohf