To be honest, I don’t really believe in song ratings. Because music today is mostly a matter of taste. And what is popular with some people is not necessarily popular with others.
However, we have to admit that these ratings are exist, they are watched, they are studied, and artists try to get into them at all costs. Especially if such ratings have the prestigious Billboard label.
Billboard is one of the oldest song rankings in the Western world. Billboard is an American entertainment media brand owned by Billboard-Hollywood Reporter Media Group. It publishes articles including news, videos, opinions, reviews, events, and is also known for its music charts, including the Hot 100, Billboard 200, and Global 200, tracking the most popular songs and albums in various genres. This brand also hosts events, owns a publishing company and runs several TV shows.
The impact of these rankings can hardly be overestimated. Many artists and their songs have become famous only because of their appearance on the Billboard charts.
When I found a dataset with top 100 billboard rankings since 1958, I couldn’t resist. Despite my skepticism concerning many music in these charts, my interest as a data science specialist still took its toll.
In this post, I will share with you my exploration of this data using the Python programming language and the Pandas library.
Links
- Collaboratory: https://colab.research.google.com/
