In this project, our group were looking to leverage Spotify API to get access to the audio features of all the tracks in one of the group’s members’ playlist. Specifically, we investigated to see if we could cluster those tracks based on their audio features such as danceability, energy, valence, tempo,… and determine which particular genre to which the generated clusters belong, since their are no readily available genre labels for each of the tracks. In addition, we investigate the relationship between track popularity and track acousticness by implementing a hypothesis test. This insight could help artists and producers align their music styles to reach a larger audience. Next, we’ll explore the relationship between artists and genres across various playlists. This analysis allows us to assess how artists are currently performing in the music landscape. From there on, we can identify which genres dominate the music charts and examine the distribution of genres across playlists. Finally, we will examine the collaboration between the artists and who possesses the most collaborations throughout their songs. Therefore, we can investigate by building a collaboration network and finding out top artists having the most edges with other artists.