I’ve been building a new application to track my personal fitness data. I’ve always loved thinking how to best represent data in visual ways, and not surprisingly it’s easy to get excited when you’re playing with your own data. While looking at my body weight this morning, I was reminded of how much scale impacts perception.
First, here is a look at my weight in kilograms using a line chart:
Next, let’s look at that same data using an area chart:
These two charts are kind of hard to follow since there’s not a lot of variance in the data, and there are periods of steep drop-offs for days where there weren’t any measurements available.
Finally, let’s look at the same data with a few tweaks:
There we go, that’s helpful. I converted my weight to pounds, tightened the scale of the Y-axis, and smoothed the chart out by removing the ‘0’ value measurements. Now, I’m able to see a couple of distinct patterns over the past five years:
- I gain weight in the winter and lose it in the spring (not surprising, I live in Chicago)
- I’ve progressively reduced my body weight year over year
I’m really happy about that second trend! I attribute it to healthier eating and exercise (cycling, strength training, and running).