Bracket Challenge - Disney Songs

With my niece Evelyn turning 1 next week, we've been getting back into watching Disney movies and listening to Disney songs on Spotify, knowing that she'll get to experience them all for the very first time soon enough. That sparked a great debate... "What's the Best Disney Song Ever?"

To tackle this, we decided to send Cinderella to the Big Dance!

I put together a spreadsheet with our top 64 Disney songs and ranked them using Spotify play counts (or YouTube if not available on Spotify). I initially did this in Google Sheets because it was relatively easy to make a bracket there, but as a self-proclaimed "Tableau Wizard" I had to try it out in my favorite data viz application.

After...

1. 63 set actions
2. an image of a bracket I threw together in Excel and used as the background
3. a heck of a lot of formatting and floating objects, and 
4. a URL-action enabled song preview feature... 

It's now your turn to join in on the Big Dance and see if your favorite song is ready to have its own "Cinderella story" in my Tableau-enabled Bracket Challenge of Disney Songs.

Tweet at me or leave a comment to let me know what you think.

#QuantifiedSelf - I Am What I Listen To

 Hello, my name is Dave, and I'm a music addict.

In 2007, I started tracking the music I listened to through a website called Last.fm. Back then, I typically listened to music through iTunes. However, iTunes didn't provide a good historic view of all the songs I've listened to. My eclectic, offbeat taste in music combined with my inner data nerd made Last.fm a great resource to me. Over the years, I've used Last.fm to track much of the music I've listened to through my iTunes desktop application, my iPod, and now through my Spotify desktop application. The only downside is that Last.fm doesn't track music I listen to on my iPhone's Spotify app, which I tend to use quite a bit.

The next step, after tracking and storing the data, is to visualize it. And what better time to create a music data viz than #QuantifiedSelf month?! I took my data, flowed it through Tableau and came up with a visualization that encourages the exploration of my music listening habits.

A few interesting insights to point out from the 1 year look-back period shown above:

• I typically have project huddles during the morning and try to reserve afternoons for development, which can be clearly seen in the "typical week, in songs played" heat map
• My peak time of day to listen to music is around 3pm on Wednesday, and when clicking on this time I see I listen to a lot of punk rock, which typically has shorter song lengths, thus the higher song play count at that time
• You can see I typically don't start listening to music until 9am, but on 3/28 I had some early morning work to do where I listened to a lot of Math Rock, a genre of asymmetric time signatures and complex rhythms, to stimulate my brain and keep me going early in the morning.
• If you switch over to the "mood" filter, you can see I'm pretty well balanced between upbeat and relaxed music and that I've been listening to a lot more "chill" music recently. If you check out some of the chillwave bands I've been listening to, you'll see their music is perfect for warm weather - I'm ready for Summer!