Viz What You Love: Part II

cmavizJust over three weeks ago, I posted a viz about Notre Dame football, supporting it with a blog post called ‘Viz What You Love,’ professing and detailing my love for the Fighting Irish football program. A few days after that post, I shared a viz outlining the history of the CMA (Country Music Association) Awards Album of the Year winners. Having grown up in the middle of nowhere, literally, in northwestern Minnesota, sports and music were two of the things that became very important to me early on in life. While, my desire to be active and competitive fire were fueled through sports, music was always there when it was time to relax, study or have fun. I love several genres of music, but where I grew up, country music was big and it has always had a place in my heart. My first ever CD was John Michael Montgomery…no seriously!! And my first ever concert was Tim McGraw, way back when his only hit was “Don’t Take the Girl.” The point is that I love country music and that one really fun way to continue improving your Tableau skills is to produce data visualizations about things you love. I like to call this “Viz What You Love.” Part II is about my CMA Awards 51 Albums of the Year viz.

When I first saw Sean Miller‘s ‘The 100 Greatest Metal Albums of All-Time’ viz, I was blown away not only by how cool it was, but also by how much information was right there at my fingertips. Now, while I’m not a huge metal-head, I’ve listened to enough to know many of the artists and albums on the list, among them Black Sabbath and Ozzy Osborne. The very first thing that caught my attention on Sean’s viz was the range of energy in Black Sabbath/Ozzy albums vs. those of Slayer, which is all energy, all the time. I hadn’t heard much Slayer before, so pulled them up on Spotify. You could say their music is…aggressive!! Anyway, I thought Sean’s viz was awesome and I wanted to try something similar from some music more familiar to me. The first step would be to find a data set…well wouldn’t you know Sean also blogged about his viz and included a sweet little trick you can do in Spotify to capture several different attributes. Thanks for sharing Sean!! Here’s the link he included in his blog that helps you sort your music, so you can then throw it into a spreadsheet and start visualizing. This process is much more seamless than I was expecting, so that was a pleasant surprise!!

As for song attributes, I chose beats per minute, energy, acoustic and popularity. Being country music was my choice, I thought valence may also be interesting, but it didn’t tell the story I was hoping for. I included all songs from each album, because I wanted to see any clustering, especially on the low and high ends of each attribute category. For instance, a majority of two-time Album of the Year award winner, Charlie Rich’s music is low energy and highly acoustic, while recent two-time winner, Chris Stapleton offers a wide variety on his albums. The extreme unpopularity of country music from the 60s through the 80s is clear, save a few notable exceptions such as Merle Haggard, Kenny Rogers and Willie Nelson. There’s a gradual increase in popularity, the newer the music is and neither of these facts are a huge surprise when you think about the demographics of Spotify listeners. I’m really going out on a limb here, but my hunch is that more millennials are using Spotify than senior citizens. I mean, my dad certainly isn’t on Spotify…can you get Spotify on a track phone??? Wait, is it track phone or TracFone? Ah, who the hell knows, the point is not many millennials are listening to Ronnie Milsap, Alabama or George Strait, but they damn well should be!! Ok, here’s what I like about the viz;

  • Like I mentioned earlier, I’m a fan of including all songs on the dot plot, as the clustering of songs within an album is interesting to see.
  • I would have never chosen these colors on my own, but a quick Google search led me to colors associated with each genre of music. So, I chose four related to country music and feel that they actually look pretty nice together, thanks in large part to the dark blue background.
  • I think the highlight actions work well, as you can hover on a song under one column and easily see where that song falls in the other categories as well.

I hope you enjoyed reading, now go out and Viz What You Love!! Thank you again for the inspiration Sean, this was a really fun project!!

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