Peter Hajas



Peterometer Chapter 1: Tracking Hydration

This is the first in a series of posts I hope to write about building tools for “Peterometer”, a way to visualize stats I’ve collected about myself.

Inspiration for Peterometer

I’ve long been inspired by people who build beautiful visualizations of their gathered metrics. For example, Nicholas Felton’s annual reports. Here is an example from his 2007 report:

The first page of Nicholas Felton’s 2007 annual report

I think this format of visualization is really cool. It’s easy to glance at while being information-dense.

Another cool example is Anand Sharma’s April Zero, which is now an app called Gyroscope:

An image of Gyroscope

He has some great posts about his creative process here and here. The Iron Man-style HUD influence shines through in the finished product.

These visualizations are really cool ways to show stats gathered about your life. I’ve recently been getting more into tracking my day-to-day life, and experimenting with visualization techniques to showcase this data.

Hydration Tracking

Since December 2018, I’ve been tracking my hydration every day. Every time I finish drinking something, I log the type of drink it was, and how much of it I drank. I log the data using the WaterMinder app on my watch and phone. WaterMinder lets you have saved drinks, which is really helpful if you drink the same thing often (my Nalgene, a cup of coffee from the machine at work, etc.)

Some Visualizations

WaterMinder lets you export your data in CSV format. With a little bit of Python, we can parse this into a “stream” stacked area chart to show how I hydrate myself:

A stacked area plot of my hydration

This chart is a bit tough to read due to data density. The legend is sorted in descending order of consumption. By the numbers, this is:

Drink fluid oz.
Water 4159.7
Coffee 1482.7
Soda 826.9
Sports Drink 761.9
Tea 751.4
Smoothie 398.0
Carbonated Water 381.4
Energy Drink 273.6
Beer 225.0
Protein Shake 162.0
Liquor 130.0
Juice 94.0
Coconut Water 81.6
Milk 55.1
Wine 17.6
Hot Chocolate 15.0
Total 9815.9

Using the chart and table there are some interesting takeaways: