In recent years, people's ability to collect music got enhanced greatly. Many people who prefer listening music offline even stored thousands of music on their local storage or portable device. However, their ability to deal with music information has not been improved accordingly, which results in two problems. One is how to find out the favourite songs from large music dataset and satisfy different individuals. The other one is how to compose a play list quickly. To solve these problems, the authors proposed a content and user-based music visual analysis approach. We first developed a new recommendation algorithm based on the content of music and user's behaviour, which satisfy individual's preference. Then, we make use of visualization and interaction tools to illustrate the relationship between songs and help people compose a suitable play list. At the end of this paper, a survey is mentioned to show that our system is available and effective.