Digital audio devices have been changing music entertainment environment. Those devices are bundled with music jukebox software, such as Apple?s iTunes, Sony?s CONNECT player. Jukebox software not only enables us to recode, play, search, purchase music on PC, but also to manage playlist. Anybody can make his/her own playlists, and play music according to the list. In this paper, we focus on iTMS (iTunse Music Stroe) playlists and use them as the data minig resources for a music recommendation system, then developing correlation measuring methods. We have retrieved about 13,000 playlists, and analyzed the frequency of artists/songs, cooccurrence of artists/songs in the playlists. Through the result data, we found out that all graphs we drew are follow the Zipf?s law. Furthermore, we have analyzed the hierarchical relation between songs according to their popularity. We proposed a basic idea of popularity measuring method.