The problem Spotify Mood Analyser solves

It can be used to determine the user's mental state, and the lyrics of the songs can help in determining how the user is feeling like. The features of the tracks 'acousticness', 'danceability', 'energy', 'instrumentalness', 'liveness', 'loudness','speechiness', 'tempo', 'valence', are useful to relate with the current feelings and how much of a joyous or neutral or sad the user is at the moment. We also gave a score (from -1 to +1) to each song on the basis of their lyrics (after performing sentiment analysis using the Vader Package) to understand the overall mood, and plotted it to show how it varies over time. A wordcloud was also incorporated to show the frequency of the top words in the songs, after removing all the stopwords of course.

Challenges we ran into

Developing a fully functional website. There were some issues in the backend development of the website and in connecting the flask API to our Python Program.