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  • The artistic side of data: who says data has to be boring? 🎨

The artistic side of data: who says data has to be boring? 🎨

I used Spotify chart data to jazz up the walls of my new place

I got myself a new house! Woohoo, something I've been working towards for a while now. You might be wondering why I'm bringing this up when we're supposed to be talking about content strategy... Well, you're absolutely right! But I wanted to take you on this journey with me, where I used Spotify chart data to jazz up the walls of my new place.

Anyone who knows me even a little knows I'm super into data storytelling, data art, and finding new ways to get people excited about data analysis. I've tackled similar projects in the past, like the ones over here, but this time, I wanted to set a fresh challenge for myself.

Could I use Spotify chart data in a way that looks awesome, reflects my passion, and doubles as decoration for my new pad? πŸ§‘β€πŸŽ¨

Alright, let's dive into the beginning!

To kick things off, I began by scraping the weekly Spotify charts in the Netherlands for the year 2023. Just so you know, you can actually do this for any country around the world, by the way.

From the top 100 tracks each week, I pulled out the following details:

  • The song's name and the artists behind it

  • Where it stood on the chart

  • And I also snagged their corresponding single or album covers.

This led me to a clean dataset that I could use for the poster print.

This is where the creative juices started flowing, and I grabbed my trusty drawing board. I began by laying out each week in 2023 in a single horizontal row. Then, for every rank position on the chart, ranging from 1 to 100, I created a corresponding column. The end result? A grid that had the week's end date (Thursday) along the Y-axis and the chart ranking along the X-axis.

From that point, the real challenge was plotting 10,400 images. 🀯 This posed a few interesting challenges:

  1. Space Management: How do you cram 10,400 images onto a poster file and still make them look good?

  2. Image Quality: Achieving high-quality images with a high DPI (dots per inch) demands large and detailed image files. This leads to a massive design file.

  3. Efficiency: The process of plotting all these images takes a substantial amount of time, around 30 minutes, using a program I wrote.

Handling these challenges was quite an adventure but you’ll be able to see the results below. πŸ§‘β€πŸŽ¨πŸ‘©β€πŸ’»

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