Project 9 - Data Tracking

Description

Rather than track a habit, I decided to represent my heart rate data for the last several months.

Because the data is so vast, I only choose 30 random heart rates from 30 random dates (decided dynamically on load).

Instructions

The interface is pretty intuitive, but simply hover over each heart to see each date and BPM rate.

Design Process

For my design process, I used my Apple Watch data, dating back several months. At first, I examined the health data by exporting it (into raw XML).

The raw data was pretty massive, containing both data from my Apple Watch and my iPhone. For context, my json file contained over 140,000 lines. I ended up following this guide to figure out how to extract the data for further analysis.

I was able to run the scripts via Jupyter Notebook, which compiled about 20 CSV files for different Apple Health activities (i.e. steps taken, distance traveled):

I then took the CSV I was most interested in, specifically Heart Rate, and created a script to parse that Heart Rate CSV into a json file.

You can see the end result here (uploaded to Google Drive).

Reflections

Quite honestly, I reserved the tracking portion of the project for my Apple Watch. I knew I was most interested in my body and health data, and was excited by the amount of data that this watch data might provide.

Moreover, I think the whole purpose of getting the watch was to record my vitals and health statistics, and the data visualization features are pretty limited currently within the watch's interface.

There is something certainly satisfying about working and expressing data about my own body, even though it's collected with a kind of cold source. By working with my Apple Watch data, I feel like I made it more human.

I also enjoyed all the love (via heart emojis) that this sketch emits :)