Peter Hajas

January 29, 2020 •  📊🥚

This is the second in the Peterometer series. The first can be found here.

After I felt comfortable tracking hydration, I wanted to introduce other metrics tracking into my life. I’ve been tracking the food I’ve eaten since March 2019. With less than a week of downtime, I’ve tracked everything I’ve eaten since that time.

I track my food in the LoseIt app. I usually log the food right after eating it, and I really enjoy seeing how many calories I’ve eaten that day.

In the past year, I’ve also become really into eating raw eggs. I enjoy them on starchy foods, like ramen or rice. Kind of like my own version of tamago kake gohan. In a given week, I’ll end up eating a few meals with raw eggs.

But how many raw eggs? Let’s find out!

Exporting LoseIt Data

LoseIt lets you export the food you’ve eaten on a weekly basis from their website. These export as a CSV file, which is perfect for processing and backup. If you’re a Premium member, go to your “Insights” tab on the website and then look for “Weekly Summary” and “Export to spreadsheet”. I export my data every 2 or 3 weeks, and collect it all in a folder on my machine. These files are numbered based on their starting day since January 1 2000:

$ ls

Generating a master food CSV

I wrote a simple shell script to combine all these summaries, remove workouts (I track these separately), and then generate a master combine.csv file with all my food in one place:

# delete the combine file
rm combine.csv
# concatenate all the csvs, sorting
echo "Date,Name,Type,Quantity,Units,Calories,Fat (g),Protein (g),Carbohydrates (g),Saturated Fat (g),Sugars (g),Fiber (g),Cholesterol (mg),Sodium (mg)" > combine.csv
cat *.csv | grep -v "Calorie Burn" | grep -v "Date,Name" | grep -v "HealthKit" | sort >> combine.csv

With this, we can cat out the combined CSV file to see the food I’ve eaten:

$ cat combine.csv
Date,Name,Type,Quantity,Units,Calories,Fat (g),Protein (g),Carbohydrates (g),Saturated Fat (g),Sugars (g),Fiber (g),Cholesterol (mg),Sodium (mg)
01/01/2020,"Sandwich, Sub, JJ Gargantuan",Lunch,1.5,Each,"1,656",82.50,108,124.50,22.50,n/a,7.50,268.50,5121

(this example highlights a problem with my use of sort in the script: 01/01/2020 sorts alphabetically before 12/01/2019)

Analyzing the food I’ve eaten

We can use some simple utilities to query the file. For example, how many food entries have I logged?

$ cat combine.csv | wc -l

Wow! That’s a lot of food. This averages to around 12 entries per day.

We can grep for other data, like how many burritos I’ve had.

$ cat combine.csv | grep -i burrito | wc -l

I’ve eaten a burrito every 9 days or so.

Counting raw eggs

But how many raw eggs have I eaten? I usually log these when I eat actual raw eggs (when I cook an egg dish on the stove without oil I will also count it as raw eggs). Let’s grep the CSV file:

$ cat combine.csv |grep -i egg
01/02/2020,Egg raw,Dinner,2.0,Servings,140,9.60,12.60,0.80,3.20,n/a,n/a,372,142
01/02/2020,Scrambled Eggs,Breakfast,1.0,Each,91,7,6,1,2,0.80,0,169,88

This grep picked up anything with “egg” in the title, like scrambled eggs. We only want to look for raw eggs - it’s simple enough to do that by modifying our grep invocation. But keep in mind the header line of combine.csv:


The fourth column is the quantity. This is how many raw eggs I actually ate. So we really want to sum that column.

We can print the fourth column with a bit of awk:

$ cat combine.csv |grep -i egg |grep -i raw | awk -F, '{ print $4; }'

and sum it with a bit more:

$ cat combine.csv |grep -i egg |grep -i raw | awk -F, '{ eggs+=$4; } END { print eggs; } '

(yes, I did eat non-whole portions of eggs some days)

276.75 raw eggs. That’s nearly two dozen dozen raw eggs!

Raw egg consumption based on day of the week

As a fun visualization, I wanted to see if I ate raw eggs more on a particular day of the week. I did this using some simple categorization in Numbers:

Raw eggs visualized by day

Wow! Based on this, I had way fewer raw eggs on Fridays. Tuesdays and Thursdays are lighter weekdays for raw egg consumption.

Looking forward to more food analysis

Counting raw egg was a fun test of the data I’ve been gathering for the past 10 months. I’m really excited about the other visualizations and analysis I can do on the food that I’ve eaten.