Sharing my cancer story with data viz

Click the image above to view in full screen. 

I have cancer. Specifically, I’ve had thyroid cancer twice and I’m currently on leave following my second surgery in as many years. It was a successful one, and hopefully I am yet again on the mend, but nothing is guaranteed. If you stop reading here, just please take one piece of advice: enjoy every single day to the best extent that you can. 

As you might imagine, the past few years for me has been a roller coaster of emotions. However, during this time I was actively training for a half marathon and weighing myself on a smart scale daily. When taking a look at the data in the various apps available to me, I found myself a little frustrated at how the data was displayed and the level of granularity I had access to. I learned that I could export basically all of it, and then started dropping it in Google Sheets. This quickly made me remember that it’s been quite some time since I played with Tableau, so I downloaded the Public version with the intention of making some easy views for myself.

What I quickly realized, though, was that this data combined with my personal story makes for a pretty interesting static visualization. In addition to finding this effort therapeutic, I also found myself really motivated to make it as pretty as I could. This probably cements my status as a data nerd - a badge I will wear with honor.

You can view it here in this post, or in your browser at Tableau Public. I tried to optimize the image for small screens, but the dashboard in Tableau is definitely best viewed on a computer. I also tried to make this as accessible as I could for my friends who might be using a screen reader, but I’m pretty rusty in Tableau and can always learn more about how to do that. Please feel free to message me if you have any suggestions on that front.

Finally, while there are some happy moments contained within, this visualization deals with cancer, depression, and death. On top of that, the world isn’t in a really great place right now. I strongly encourage you to talk to someone - a therapist, mentor, friend - if you’re feeling down.

If I sent this graphic your way early, I appreciate the feedback. Megan, Don, Kacie, Rebecca, MK, Peter, Jaon, & Chris - as well as my high school friends who are bad viz critiques but I love you regardless.

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Why did you do this?

I was on medical leave and just beat The Last of Us Part 2 and my buddies that I talk to about it didn’t beat it yet, so I went to r/thelastofus2 subreddit and found no comfort there either. It was genuinely a coincidence that I started using the Fitbit and scale more regularly around the time that I got some questionable scans, so I decided to look at the data and I didn’t like any of the charts. Once it was in Tableau, it was reminiscent of some old projects I worked on while I was in consulting and it was just kind of fun to play with.

What is this visual meant to be?

It’s my quite strong belief that you can be an incredibly beautiful static visual or a fully interactive dashboard. It is incredibly difficult to do both. It’s like Michael Jordan playing baseball. In this case, the Tableau Public side of the house is baseball and the ability to be easily shared in many formats is the basketball. And that’s an intentional design decision because I wanted to share this to a few different places, and that there’s only one story to tell with this visualization. As a result, annotations are much longer and manually placed. The resolution I used for the dashboard is super large. Title and subtitle and axes are oversized. Axes are manually fixed to tell the story I want. I can curate every element of it, literally open up the Snipping Tool on Windows, and produce the image above. Throw any kind of filter, or calculation change, on top of this visual and it all falls apart. 

How was this similar and different to a typical project you’d work on?

I have 100% of the context to this data, which made things a lot easier. However, there were a few things that occurred that has shades of my work life - the data exports weren’t *quite* as granular as I’d like (it was non-trivial to identify the long run days based on the aggregated distance data provided), I found myself scope creeping in directions that didn’t really pan out (overlaying sleep/heart rate info in an already crowded visual), and the amount of time I took fine-tuning the visualization. I probably have about 15 hours all-in on this thing, which is why these kinds of views can be really time-consuming when it’s an analyst in a workplace dealing with data they might not be experts in yet. 

Why 7 day trailing average for miles?

Since the training program I was following calls for a long run every 7 days, and I take a few days of rest after, a week felt like the appropriate time to smooth outliers and tell a cohesive story. But at the end of the day it’s just my judgment call - there may be better ways, but that's just like, your opinion, man. 

Were you only running?

No - I would run maybe 2/3 times per week and supplement off-days with Orangetheory online videos, or the occasional hike. The Fitbit didn’t really capture workout stats as distance, but it’s a fair assumption to say the effort I put into them was fairly consistent when I was doing them.

What other data did you look at?

I have sleep, activity, and heart rate data that seems workable but didn’t really layer well onto this visual. 

What data are you missing?

Food, obviously. Too much of a pain to log food for me, personally. Assume my diet was baseline the same with the exception of depressed spikes called out in the graph, when I let myself eat/drink whatever I wanted. 

Can I see a progression gif of all the pedantic edits you made of this visual?

Hell yeah you can