As a music producer, I wanted to analyze the music that I have put up on Spotify to see what patterns and conclusions I can draw not only about the music that I have released, but the music I listen to as well. Therefore, I hope to use MATLAB as a way to visualize some of the data that can be produced using the Spotify Web API (Python wrapper class: https://github.com/plamere/spotipy). By graphing scatterplots, histograms, manipulating some of the quantitative variables produced from the API and creating metrics to create and measure variables, I hope to demonstrate my proficiency with MATLAB and Python in a project that extends my interests and allows me to learn more about them.
The graphs are shown in the Documentation.docx file.
The most noticeable observations made were: my predilection for songs that are high energy and are very danceable, that the music distribution of the song tempos I listen to is normally distributed but is left skewed when looking at the distribution for the song danceability and energy. It is also implicitly understood based on the lack of relationships found for other Spotipy API variables that my music taste is varied enough in mood, style, and genre that causes no predilection towards a specific variable heaviness (balance in valence, acousticness prevalence, etc.).