Data Science Project: Trendspotting on Spotify

The Pandas of Jupyter

• Atul | anulkar| Nulkar
• Justin | justinjapan | McSpadden
• Jasmine | jasmineorr | Orr
• Keith | keithhorbin | Horbin
• Stone | stonega1992 | Powell

Project Goals/Research Questions to Answer

Explore Spotify's Playlists across different Genres of music and understand various relationships and trends between Artists, Songs & their Audio Features:

1. Which Genres are more popular than others? Statistically, are there significant differences in Popularity between Genres?
2. Does the Duration of a song affect it’s Position within a playlist?
3. Does the Position of a song in a playlist impact it’s Popularity?
4. How are popular songs trending in terms of their Valence, i.e. songs that sound more positive (e.g. happy, cheerful, euphoric), vs songs that sound more negative (e.g. sad, depressed, angry)? Is there any correlation between the Speechiness and the Valence of a song?
5. How do various Audio Features of a Song - such as it's Danceability and Energy - influence it’s Popularity?

Dataset Sources

• Artists, Playlists, Tracks and Music Metadata sourced using the Spotify Web API.
• CSV files exported using the API and which were used in our analysis can be found here.

Jupter Notebooks

• spotify_exploration.ipynb - contains code to retrieve and wrangle data using the Spotify web APIs and generate some basic stats/plots.
  • To run the notebook, you will need a Spotify developer account with your own client_id and client_secret credentials to authenticate the API requests. Generate your client credentials from the Spotify Developer Dashboard.
  • Once you have setup your credentials on the Dashboard, create an api_keys.py file in your local repository and copy the following lines of code, so that your credentials are imported automatically in the jupyter notebook.

    spotify_client_id = 'your client_id goes here'
    spotify_client_secret = 'your client_secret goes here'

• spotify_analysis.ipynb - contains code to perform more in-depth analysis of the Spotify data and to seek answers to our research questions.

Presentation (Results Report)

A detailed analysis of our findings can be found in this presentation.