Written by Brian Gural
README last updated on September 24th 2023
This project is focused on a comprehensive analysis of personal listening habits using Spotify data. Utilizing R and various statistical and data visualization techniques, the project aims to provide insights into trends, preferences, and temporal patterns related to music listening. The ultimate goal is to provide a straighforward method of analyzing one's own Spotify data.
Spotify users can go here to request their own data.
This analysis pipeline is intented to be containerized via Docker. Follow the directions below to carry out the pipeline on your own computer*
*assumes that you have cloned this repo and have docker functioning
To run the code, build the Docker image and then start an RStudio server:
docker build -t spotify_analysis .
docker run --name=spotify -d -p 8787:8787 -e PASSWORD=pw -v $(pwd):/home/rstudio spotify_analysis
If you'd like to run the code in an interactive session: Open your web browser and go to http://localhost:8787.
Username: rstudio Password: pw
Otherwise, use make to run the scripts for the skeleton analysis:
- Enter an the docker session with
docker exec -it spotify /bin/bash - Navigate to our project directory with
cd home/rstudio - Run scripts with
make
Two plots should appear in the results/skeleton directory
To kill the docker container, find the container ID with docker ps -a, then use the container ID in docker kill "container ID".
Note: The docker run line uses the argument -v $(pwd):/home/rstudio to mount the current working directory to the docker container, then make the relative path to it (within the container) /home/rstudio