Fighting COVID Gut with Data Science Pt.1

Posted by Chris Russell on JUNE 12TH 2020
There I was…looking at the reflection of a body I no longer recognized. I was an athlete and although I’d gone through the ups and downs of body weight, never like this. A gentle poke of the tummy produced a visible jiggle that lasted more seconds than I’m comfortable sharing. I knew in that instant that I had become infected with what one can only deem as COVID gut.
COVID gut is similar to the freshmen 15lbs or the first-year teacher 40lbs, but with one key difference- the existential dread that accompanies the feeling that life has fundamentally changed for the foreseeable future. I decided that it's time for me to fight this COVID gut beast, and my weapon of choice, data science.

Welcome to part 1 of my COVID gut journey that hopes to help teach folks some data science skills through a very personal use case.

Objective – Chris will be able to decrease body weight from 222lbs to 190lbs or below

Hypothesis – If Chris follows an intermittent fasting schedule 16:8 (8:00 AM – 4:00 PM) and reduces calories to <=1500 a day, then he will decrease his body weight and destroy COVID gut.

Variables:

  • total_calories - Calories must be 1500 or less a day and is measured by the calorie tracker
  • weight_am - Weigh-in occurs every morning at 8:00 AM EST, measured in lbs
  • weight_pm - Weigh-in occurs every evening at 8:00 PM EST, measured in lbs
  • exercise_cal - Measured by apple watch of total calories burned throughout day
  • exercise_min - Measured by apple watch of total dedicated exercise minutes
  • sleep (hh:mm) - Measured by smart sleep device
  • energy_level - 6-point Likert scale ranging from 1 (not at all) to 6 (completely so) to the question,"Feel energetic to do everything"
  • time - Each day all food consumption will take place between the hours 8:00 - 4:00 PM

Setting up the data collection instrument - For the purposes of this journey, I felt setting up a google sheet would be easiest to use for data intake, particularly for counting calories.

Let's look at a few features of sheets I incorporated into this calorie counter:

Freeze Rows
Freezing the top row allows me to input data and easily see the column variable. Since I do alot of input on my phone, this is super helpful!

Conditional Formatting
I used conditional formatting to auto update the first row that represents the present date. This makes it easier to see where a new day begins!

Sumif() & today()
I combined the sumif() formula with the today() functionality to calculate my daily calories. This is helpful when I need to know how close I am to hitting my 1500 calorie cap.

Data Validation
I have a tendency to fat thumb inputs on my phone, so I added data validation where appropriate for dropdown functionality.

This wraps up part 1 of this journey- I’m hoping to cover more concepts in both google and python as I continue this journey! See a sneak peek of an interactive python graph below displaying progress so far!

-Chris Russell