Web scraping and exploratory data analysis project of RuPaul’s Drag Race. Includes a custom Spotify playlist, an interactive map, and a network diagram.
Data Collection
In this personal project, I dove deep into the fabulous world of drag queens, scouring wiki pages about RuPaul’s Drag Race and other global franchises to gather data. With the help of rvest, a web scraping library in R, I was able to grab all the details I needed.
After I scraped the data, I sketch out a blueprint for what the ultimate drag queen database would look like, you can see the data model on my GitHub. With my new “database” of Drag Queen data, I set out to explore the data with a few cool projects.
Lip Sync Playlist
First - I wanted a playlist of RPDR lip sync songs. I needed some jamz to inspire me while I thought about some visualization projects.
Luckily, I had already scraped all the lip sync songs from Wikipedia. Using Spotify’s API service, I was able to lookup each song and get the Spotify track IDs. I then used their create playlist function to generate my own playlist using the track IDs. In a matter of seconds I had 300+ songs and 20hrs worth of lip sync songs in my very own playlist!
Where Are You Queen?
Where are the queens originally from? I used tidygeocoder to produce the geo coordinates for each hometown, and used leafletR (Leaflet wrapper) to generate the map. With crosstalk, I created a filter input - you can search for any queen featured on RPDR. It’s pretty cool to see how Ru’s family footprint has expanded around the world - you can find queens from almost all continents!
Drag Race NetWerk
I also wanted to explore the connections and overlap among queens featured on the different drag show seasons and franchises. I created this network diagram with D3 in an Observablenotebook.
Sometimes contestants from previous seasons reappear on newer seasons. There are also cross over shows like UK vs. The World, where contestants from different international franchises are invited to compete again for an international crown.