Sydney's Spotify Listening Frequency
This project visualizes my listening habits on the streaming service Spotify from March 2021 to 2022. My interest in music listening statistics is largely inspired by Spotify's end-of-the-year review "Spotify Wrapped", as well as community-created apps that analyze and visualize listening data using Spotify's API. I was able to gain access to my listening data through Spotify, who will allow you to download a year's worth of your listening and account data upon request.
The circular barplot serves as a 24 hour clock, where each bar represents how many plays were recorded in that hour of the day. The charts are then split into quarters for morning, afternoon, evening, and night, mimicking daylight and night sky. These were created as histograms and were made circular using coord_polar(). The x and y axes were then modified to create the hole in the center.
The visual is faceted to show three unique dataframes: my entire listening history for that timeframe, my listening history of Fall Out Boy, and my listening history of 100 gecs. These were chosen to dissect my listening behavior at particular moments in my life.
I listen to Fall Out Boy primarily while traveling to and from Phoenix, and I listen to 100 gecs mostly while studying or coding. With this, I was able to recognize some of my habits in my barplots; my listening of Fall Out Boy was highest at 4-5AM and 8PM, which is usually when I would take long commutes. My listening of 100 gecs was highest at 7PM and 2AM, indicative of my night-owl studying habits.
Because of this challenge, I learned to familiarize myself with new R packages, as well as how circular barplots can be created using R Studio. Overall, it was a lot of fun and I'm excited to continue working with music and listening data in the future!
For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu
This item is part of the University of Arizona Libraries 2022 Data Visualization Challenge
