I don’t know about you, but I’m feeling 22 Taylor Swift data visualizations.
This is the Extended Version post. If you want to read just the highlights:
- Check out my shorter blog post
If you want to watch me talk about this post:
- Check out my YouTube video
Table of Contents
Popularity
1. Billboard Hits
2. Demand for The Eras Tour
3. Audience Growth
Sound
4. Sound Evolution
5. Keys of Songs
Lyrics
6. Seasons
7. Days of the Week
8. Complex Words
Lyrics Over Time
9. Swear Words
10. Never vs Always
11. Girl vs Woman
12. Colors
Collaborators
13. Tour Openers
14. Co-Writers
15. Top Hits with Main Co-Writers
Midnights
16. Up and Down Theme
17. Song Connections
Mastermind
18. Album Titles From Song Lyrics
19. Song Lyrics From Album Titles
20. 3 Pen Types
21. Revenge Songs
22. Last Line of Every Album
How Did I Do This Analysis?
1. Billboard Hits
The majority of the songs on her albums make it to the Billboard Top 100.
2. Demand for The Eras Tour
Fans have been waiting years for The Eras Tour and can’t wait to hear all her greatest hits.
3. Audience Growth
She keeps expanding her fan base. Somehow both me and my niece who’s 20 years younger than me are both Swifties!
4. Sound Evolution
Her sound keeps evolving and she’s getting more experimental over time.
5. Keys of Songs
She writes a song in almost every key on folklore!
My guess is she’s transitioned from writing songs mostly on the guitar to the piano.
Even though she writes a lot of sad songs, most of her songs are in major keys.
6. Seasons
Not a lot is going on for Taylor in the spring.
7. Days of the Week
She loves singing about Tuesday nights.
8. Complex Words
She hides complex words inside pop songs.
9. Swear Words
She’s been slowly adding swear words to her vocabulary over the years.
10. Never vs Always
As she gets older, she uses the term never less and always more.
11. Girl vs Woman
Her lyrics have transitioned from talking about girls to women, and boys to men.
12. Colors
The colors in her songs have gotten more complex over time.
13. Tour Openers
Ed Sheeran and Shawn Mendes both made it big after touring with Taylor.
14. Co-Writers
Taylor wrote all of Speak Now on her own, and had the most number of co-writers on reputation.
15. Top Hits with Main Co-Writers
She writes her best sad songs with Liz Rose, her angsty songs with Jack Antonoff and love songs on her own.
16. Up and Down Theme
Every song on Midnights references something up or down, just like the time midnight, where both hands of the clock are pointing up.
17. Song Connections
The words in one song lead to the next song in Midnights, like “haze” in the first song of the album to “hazy” in the second song of the album.
18. Album Titles From Song Lyrics
Starting with 1989, her album titles have come from prior song lyrics (except for folklore, which was a surprise album).
19. Song Lyrics From Albums Titles
She references her album titles in later songs, like when she talks about being a “fearless leader” in the song, The Man (Lover).
20. 3 Pen Types
She imagines what type of pen she is holding (fountain, quill or glitter gel) as she writes her songs.
21. Revenge Songs
She says she writes in the style of 3 pen types (see previous visualization), but I think there may be a 4th pen type for her revenge songs.
22. Last Line of Every Album
The last line of every album shows how she’s grown over time to becoming more confident in herself.
She can finally admit that she is a mastermind. I hope you enjoyed these 22 Taylor Swift data visualizations!
How Did I Do This Analysis?
These data visualizations may look simple, but they were the product of a lot of technical work behind the scenes!
I want to thank the following people for their technical resources:
- I followed Cameron Watts‘s Extracting Song Data From the Spotify API Using Python tutorial on Medium to extract Taylor Swift’s song metadata using the Spotify API. He is a software engineer at Microsoft.
- I borrowed heavily from Melanie Walsh‘s Introduction to Cultural Analytics & Python online textbook to extract Taylor Swift’s lyrics using the Genius API. She is a Professor at UW.
- I did most of my data analysis using Excel and Python, but I double checked my work using Shayna Kothari’s awesome Taylor Swift Lyric Search app. She is a software engineer at Facebook.
I did most of my data analysis in Excel, my data extraction and text analysis in Python and my data visualizations in Keynote.
You can find spreadsheets containing Taylor Swift’s song lyrics and metadata, along with the Python code I used to get the data from the Genius API and Spotify API on Github.
Superman is from Speak Now not Fearless.
Thanks for catching that! I updated the data viz.
This is so amazing. I watched your introduction to NLP series on Youtube and learned so much. Now this is just another level of cool. I will go through the code and do a similar analysis of my favorite artist Mxmtoon!
Thank you! Have fun with your analysis. 🙂
This is amazing i love it