Over the past two years, I have noticed something interesting. Whenever I generate a new visual for a t-shirt, I don’t always like the results. I only tend to like visuals based on the artists I like as well. In other words: visuals generated for artists that I just casually like don’t really resonate with me.
Now that I know this, I take my time to come up with new designs. Actually, I just do nothing and wait. Wait until I feel a growing need for a new t-shirt.
Lucky for me, the wait was over a few days ago.
So why the Gorillaz? Well, I have been slowly expanding my album collection with music that I used to listen to when I was younger. And my collection would not be complete without the Gorillaz. Whether it is their ground-breaking Clint Eastwood, the lovely Dirty Harry, or one of my current favourites Melancholy Hill (my collection currently includes Gorillaz, Demon Days, and Plastic Beach), I just love their sounds. The fact that they were the first virtual band and have a visual style that I happen to like are some nice benefits.
For my new data visualisation t-shirt, I decided to go with the debut album: Gorillaz.
Data Analysis of Gorillaz
If you’re new to my dataviz t-shirt project, I recommend you to read this post first.
As always, I start my process with the lyrics . Analysing the 15 songs on Gorillaz for sentiment gives the following result:
Now that I have the debut album captured in 15 data points, the next step is to draw a line from dot to dot. The order is based on the index of the songs on the album. Drawing the line gives met the following result:
And as my script allows met to draw curved lines (Bezier curves for the technical readers), I gave that I try as well:
Whenever I make a new t-shirt, I try to force myself to come up with a new way to generate a shape. So I didn’t stop here.
The new edge shape
The cool thing about my t-shirt project is that one, I just need to make something that is aesthetically pleasing, and two, it only needs to be so for me (as I am the only customer of my t-shirts). Because of this, I can do whatever I like, and focus on generative data art over data sense making. Dare I say: form over function! Yes. Form over function.
I changed two things in my shape designing code. First, I changed the order of the data points the line should follow. The path used follow the index of the songs on the album. This time I decided to go with an outer shape path, making the line follow the path of the outermost data points. Second, I added a connecting line between the last data point and the first. This closes the shape.
The result with straight lines looks like this:
The result with curved lines looks like this:
This is the shape I liked and decided to go with for my next t-shirt design.
This was actually quite hard to build technically. First, I sorted the songs manually in a csv. After that, I figured out how to do it in code and added the edge shape filter to my GitHub Repository.
I have already told you that I like the design of the Gorillaz. One of the things that I still remember is that the lead singer, 2-D, is blind. And that his eyes have been removed. In most visuals, you can clearly see his all-black eye sockets:
Image of 2-D, Gorillaz’ lead signer. All rights belong to the Gorillaz.
For the t-shirt design, I used a very minimal version of the eye-socket-depth in 2-D (non-)eyes:
I felt this was a visual ready for print. So onto the t-shirt printing press it went.
The Gorillaz Dataviz T-Shirt
To prepare myself for summer, and the Gorillaz style has become a bit more colourful over the years, I went for a happy yellow t-shirt:
A proper influencer-style picture will be added later, probably when spring comes around and it is a bit more bearable to wear a t-shirt outside.
The Gorillaz once said:
It’s the music that we choose
And for me, that sometimes results in me designing a new t-shirt. After some programming and a little designing, I now have my very own, unique, Gorillaz dataviz t-shirt.
I am, again, happy with the result.
This post is part of my Avicii Project. An ongoing project in which I visualise a machine’s view on music lyrics.