*** EDIT: new version of the viz here!
When I was new to #dataviz, seeing only finalised projects by seasoned practitioners used to puzzle me: I always have thousands of questions on the process: how did you get there?
That’s why I document most of my projects, explaining the reasoning, design choices, technical hurdles etc.
Strong storytelling, quirky dataviz and quoting Hamilton are 3 of my favourite hobbies. I mixed the 3 and shared a tribute to my favourite musical in the form of a visualisation project celebrating its clever catchy phrases aka motifs.
So how did I do it? Let me drop some knowledge!
- Get the lyrics
I scrapped (extracted) the lyrics and singers from Genius.com with the tool Webscraper.io and reworked the export to clean it with OpenRefine.
- Find the themes
I started looking at text analysis tools such as Voyant tools and then realised there was no need: everything clever about Hamilton’s lyrics and motifs has already been written. I focused on a qualitative analysis.
- They deserve credit for all the credit they gave me
- Shirley Wu’s Interactive Visualization of Every Line in Hamilton made me want to explore the topic in depth. It’s so beautiful and her idea of grouping the lines by a consecutive set of lines by a singer saved me of a lot of headaches.
- Johnathon Rose-Lyon‘s Hamilton and Motifs: Creating Emotional Paradoxes
- video explains all you need to know about motifs in a entertaining way
- Genius.com comments, especially this page dedicated to motifs
- Hungry for more?
- Interested in musical motifs? Howard Ho’s YouTube channel’s content is top notch. I cannot believe he made something so technical so easy to digest
- Interested in poetry? The Wall Street Journal wrote an algorithm to analyse the complex rhyming lyrics.
- I took a pen
The visualisation and navigation were all created on Tableau except the hand sketched ones. Oh, you haven’t seen them? The bunny must have hidden them…
The online dots 