What?

This is an attempt at visualizing how last.fm listeners react when an artist dies. One can expect a sudden rise in artist's popularity after the musician's death, which is likely to happen.

The thing is the that the fact of inspecting changes in the artist's charts makes me wonder about a lot things, such as:

How long does the increment of playcounts?

Does it depen on how famous the artist was?

Maybe the most listened songs change?

Which artist has the higher increment of playcounts?

How do charts change when a new album appears? when the artist is on tour?

The data

The purpose of this data visualization is to satisfy my curiosity and at least get some the questions above.

Although last.fm offers an API to extract data from its platform, the API does not offer the chance to retrieve the artist playcounts based on specific dates. This kind of data is available (**update: this data is not available anymore, more on this at the end) on the artist's page, so I scraped it in order to retrieve the weekly playcounts during the 2 months before and after the death date. Once the data was scrapped, this data visualization was built in order to give some insight about the last.fm listener's behaviours.

**Update: While creating this data visualization, last.fm rolled out a new beta website. With the new version it's not possible anymore to scrape the artist's URLs to obtain the data so sadly I was limited to play with the data I had until this moment, which is the set of artists displayed above.

Tech stack

The data was scrapped with python (Requests and Beautiful Soup libs to the rescue). Yeoman, angular, bower, grunt and bootstrap helped with the frontend and D3.js has been the swiss knife to build all the charts.