Title: Hit or Miss? (2000's Hit Predictor Model)
Context:
The purpose of the data visualizarion model is to predict whether a track would be a hit or not, based on multiple factors (i.e. danceability, energy, speechiness, liveness, valence, and target).
(Note: The author does not objectively consider a track inferior, bad or a failure if its labeled 'Miss'. 'Miss' here merely implies that it is not a song that probably could not be considered popular in the mainstream.)
Tech/Framework:
-Python
-Bokeh (ridgeplot model)
-Pandas
Acknowledgements:
-Remote source: Provides the Spotify Hit Predictor Dataset https://github.com/fortytwo102/the-spotify-hit-predictor-dataset
-"spotipy": Python module for Spotify's API (https://pypi.org/project/spotipy/)
-"billboard": Python module for Billboard's API (https://pypi.org/project/billboard.py/)
-Spotify, the company itself. For keeping a database of such in-depth details of every track in their library. And for exposing their API for the world to use.