2019 Wrapped: A Year In Data
Motivation
Data is all around us. Whether we like it or not, our devices track our every action. Humans produce over 2.5 quintillion bits of data each year and this number will keep growing. While companies track our data for their own profit, we can access much of this data ourselves. Self Tracking is easier than ever due to cheap sensors, machine learning, and cloud computing. Daily habits offer mass amounts of information for data tracking. One of the most popular forms of data tracking is Spotify’s Wrapped. Every year, users of Spotify can see their most listened to songs, artists, and genres of the year on the platform. Inspired by Spotify and other data tracking analytics, I composed a wrap up of my data for 2019. I collected my personal data through various platforms to gain clarity in my habits. Using techniques such as web scraping, I imported my data into Google Data Studio to visualize it. For much of my tracking, I was very surprised by what I discovered and learned a lot!
“Self-tracking is much broader than health. It is as big as our life itself. Tiny wearable digital eyes and ears can record every second of our entire day — who we saw and what we said — to aid our memories. Our stream of email and text, when saved, forms an ongoing diary of our mind. We can add the record of the music we listened to, the books and articles we read, the places we visited. The significant particulars of our routine movements and meetings, as well as nonroutine events and experiences, can also be funneled into bits and merged into a chronological flow.” — Kevin Kelly, The Inevitable
Health
2019 Fitness Activity From Strava
Last Christmas I received an Apple Watch as a gift. Smartwatches allow tracking workouts and health-related data with just a click of a button. My watch allowed me to track (most of) my runs, bike rides, and swims. As a triathlete, I look at my fitness data to see how I am improving after each workout. Strava is the platform I use to record all my workouts. I wrote a python script to retrieve the data from Strava every week and then import it into an excel file. In 2019, I logged over 1,583 miles. This could be further broken down into 944.92 miles ran and 636.74 miles biked. The high mileage is due to training for the Los Angeles Marathon and the Wisconsin Ironman. Unfortunately, a lot of my workouts were not recorded due to issues with my watch. I hope for 2020 to fix these issues. My average pace for running this year was 8:50 miles per minute. While shorter runs had a much faster pace, longer runs tended to slow down my pace for 2019. Training techniques for running show high mileage each week can reduce your average pace. My data backed this up as the weeks I was running four to five times showed decreases in my pace. Weeks where I implemented interval training also helped with my fitness.
Takeaway: High mileage results in faster pace time.
Goal for 2020: Reduce average pace and track workouts better.
Places I Visited
Locations visited in 2019
2019 was a year full of travel. I logged every place I visited into excel. I split most of my time between Atlanta (where I attended college) and Chicago (my hometown). I went on trips such as Mardi Gras in New Orleans, skiing in Lake Tahoe, and visiting a friend’s house in Kiawah Island.
Goal For 2020: Travel More and Visit New Cities Around The Globe!
Reading
Reading in 2019
For the past few years, I have kept a google sheet of all the books that I have read. I started doing this to help keep track of my reading and to remember all the books that I have read. You can see all the books I have read here. One of my main objectives of the year was to read quality over quantity. In 2018, I read 91 books. Many of the books I read in 2018 did not provide much value. My selection tended to be the newest featured book on New York Times Best Sellers list. For 2019, I aimed to select books that would provide the value I was lacking from the previous year. I also wanted to tackle longer books that in years past I shirked away from. I read a total of 45 books and listened to 26 audiobooks. This was much lower than my previous year. The Genre of books that I read this year varied. I enjoyed reading more fiction this year which showed as it was the largest category. This was then followed by “Management” books which the data shows I would through in a few days. Self Improvement, Finance, and Biographies rounded out the top five. The longest book I read, or I guess listened to, was Atlas Shrugged by Ayn Rand at 1,168 pages. The book took me over a month and a half to listen to this book at 2x speed. The longest book that I actually read was the epic samurai novel Musashi at 976 Pages. One of the interesting things I noticed was that in the months where I read long books, I tend not to read as many pages. In July, I read Fall; or, Dodge in Hell and in December I read Van Gogh two of the longest books I read all year. My interest in reading would wane due to getting bored at points or distracted. My favorite books I read for 2019 were On The Road by Jack Kerouac and Red Notice by Bill Browder. I would like to look more into my data for 2020 to find ways to help build my reading habit.
Takeaway: Long books do not always provide as much use as thought.
Goal for 2020: Find trends in reading as well as continue to read impactful books.
Streaming
2019 Streaming Habits
Streaming was the hardest measurements to track. It is difficult to track TV usage due to viewing devices that are not yours. I stuck to tracking the streaming I did on my devices only. It is very easy to track your Netflix activity due to its history feed. I wrote a python script to scrape the data from my history feed. Unfortunately, other streaming providers do not have this feature. I had to rely on entering all the shows through memory. Luckily for me, this was easy to do as I only watched a few shows this year. For 2019, I watched 154 episodes of streaming services and logged 120 hours, equating to 5 days or 1.37% of the year. The service provider I watched the most was HBO due to watching Curb Your Enthusiasm, Watchmen (my favorite show of the year), and Game of Thrones. A higher TV consumption compared to other years was due to my Ironman training. When I biking indoors, I watched TV shows to help pass the time.
Takeaway: While 5 days of TV may seem like a lot, it’s not as much compared to the entire year.
Goal for 2020: To monitor my streaming so that I am not watching too much at a given time.
YouTube
2019 Video History Scraped off YouTube
Tracking my YouTube history lead to the most interesting discoveries. YouTube does provide each user with their video history, making it easy to web scrape. It is hard to determine the exact time spent watching each video due to skipping parts of each video. 5/10 of my top watched videos are music and 2/10 are meditations. The music videos help further explain to me why music videos get so many views on YouTube. Saturday Night Live is my most-watched channel for 2019. Channels producing shorter videos like movie trailers are higher on my list than I would have thought. An interesting trend I uncovered is that on Tuesdays I watch almost the same amount as I do on the weekend. This baffled me since I have much more free time on the weekends and could not explain this trend. The craziest fact is that on March 21st I watched 71 YouTube videos!
Takeaway: It is easy for music and short-form videos to dominate YouTube.
Goal For 2020: Watch Less YouTube!
Eating Out
Eating Out Habits in 2019
This category will have the biggest effect on me. I always thought that I ate healthy and didn’t eat out that much. Boy was I wrong! I ate 203 meals out this year. The way I obtained the data for this was through Mint.com. Mint.com connects with your credit cards to track your financial activity. They have a feature to export all transactions on my credit card into a csv file. This is much easier than scraping all the data off your credit cards. From there, I filtered the data down to only include transactions that were for food. For this article, I decided to focus on the number of times eaten out instead of the dollar amount. One of the biggest surprises to me is how many times I ate unhealthy when going out. Fast food joints dominated the list. Even though I cook healthy majority of the time the data shows that it gets ruined when I eat out. Another surprise is that Monday is a huge day for me to out. I am uncertain of how this came to be. If I had to hypothesize, I would treat myself when starting out the week. Months where I traveled a lot had a higher amount of eating out, resulting in unhealthy eating. This is important to keep in mind for me since I am starting my job with high travel in 2020.
Takeaways: I eat unhealthy food the most when I go out especially when I travel.
Goal For 2020: Eat healthy when going out!
What’s In Store For 2020?
2019 was a great year for me, but I am very excited for what will come in 2020. I would like to track more of my daily habits in 2020. One of the biggest features I will be monitoring for 2020 will be my daily phone usage. While having data is great, utilizing is better. I plan to use data science to predict and find trends to improve my life for the better. If you are interested in obtaining any of your own data feel free to reach out to me at jacklgorman9@gmail.com