Examining the trends in Spotify's new releases in Australia with dynamic interactive graphs.



Each week a large number of new releases are added to Spotify in Australia. Exploring the trends in volume of releases per genre, per week, could yield a useful descision-making tool for market share growth on the platform for a record label. This project explores a few of many ways to look at this data.

New release data is collected and appended to the existing dataset (that begins at the 15th of May, 2020). The data is then transformed through a script I've written using Altair, a declarative statistical visualization library for Python based on Vega and Vega-Lite, into an interactive plot.

The graph below shows releases over time in Australia, with 'volume' being the number of releases from each genre each week.

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This second graph shows releases over time in Australia with a metric I've called 'Australian Audience Potential'. It takes into account the top five cities and the monthly listernership of each artist to determine which genres will likely impact Australian market share the most.

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Technology Used_

The code runs once a week on a stock Raspberry Pi 2 Model B sitting on a shelf in my home. It has a 900MHz quad-core ARM Cortex-A7 CPU and 1GB RAM.

The project was completed with Python. Here are a selection of the libraries used:

• Altair for interactive plotting.
• BeautifulSoup / Requests for web scraping.
• Pandas for data frame management.
• FTPLib for transferring files to this web server.


Below is an image of the interactive plot when it went live in it's third week of collecting data.


I’ve collected a few resources for further reading:

New Releases in AU on Every Noise At Once.
Raspberry Pi 2 Model B product page.
Altair Documentation.

© Copyright 2020 Tom Gilmore. All Rights Reserved.