My whole life in a single database

As part of the FxLifeSheet project I’ve started back in 2019, I started collecting all kinds of metrics about my life. Every single day for the last 2.5 years I’ve tracked over 100 different data types of my life.

I haven’t yet had the time to analyze all the outcomes, but felt like I already have some very interesting graphs I’d like to share here.

Currently, I have ~370,000 data points, with the biggest data sources being:

Data SourceNumber of data entriesType of data
RescueTime150,000Daily computer usage
Foursquare Swarm125,000Location and POI data
Manually entered63,000Fitness, mood, socializing, productivity
Manually entered time ranges10,000Occupation, lockdown status, home setup
Weather API16,000Temperature, rain, sunlight, wind, air pressure
Apple Health1,000Steps data

This project has 3 components:

◦ Database

A timestamp-based key-value database of all data entries powered by Postgres. This allows me to add and remove questions on-the-fly.

◦ Data Inputs

Multiple times a day, I manually answer questions FxLifeSheet sends me via a Telegram bot.

◦ Data Visualizations

After having tried various tools available to visualize, I ended up writing my own data analysis layer using Ruby, JavaScript together with Plotly.

Flying Stats - General

All flights taken within the last 7 years, tracked using Foursquare Swarm, analyzed by JetLovers.

  • This clearly shows the impact of COVID starting 2020
  • Sunday has been my "commute" day, flying between San Francisco, New York City and Vienna
Sources: JetLovers, Swarm Flying Stats - General 7 years of data - Last updated on 2021-12-12

Flying Stats - Top

All flights taken within the last 7 years, tracked using Foursquare Swarm, analyzed by JetLovers.

  • Frankfurt - Vienna was the flight connecting me with most US airports
  • Germany is high up on the list due to layovers, even though I didn't spend time there
Sources: JetLovers, Swarm Flying Stats - Top 7 years of data - Last updated on 2021-12-12

Top Cities (Checkins)

Each time I checked-into a place (e.g. Coffee, Restaurant, Airport, Gym) at a given city, this is tracked as a single entry

Sources: Swarm Top Cities (Checkins) 7 years of data - Last updated on 2021-12-12

Top Cities over the years

Each check-in at a given city is counted as a single entry, grouped by years

  • 2016 and 2017 I lived in San Francisco
  • 2018 and 2019 I lived in New York City
  • 2020 and 2021 I lived in Vienna
  • The longer it's been since I moved away from Austria, the more time I actually spent back home in Austria for visits and vacations
  • 2020 clearly shows the impact of COVID
Sources: Swarm Top Cities over the years 7 years of data - Last updated on 2021-12-12

Top Categories of Checkins

Each check-in at a given category is tracked, and summed up over the last years

  • In 2020 and 2021, check-ins at Offices went down to zero due to COVID, and a distributed work setup
Sources: Swarm Top Categories of Checkins 7 years of data - Last updated on 2021-12-12

Maximal temperature each day of the year

Historic weather data based on the location I was at on that day based on my Swarm check-ins. Days with no data are rendered as white

  • Summer 2019 I spent in New York City, while 2020 and 2021 I spent in Vienna. The graph shows the summer in NYC to reach higher temperatures
  • Week 36 in 2021 I spent in Iceland, therefore significantly lower temperatures
  • End of November in 2019 I spent in Buenos Aires, therefore way higher temperatures
  • December 2019 I spent in Columbus, Ohio, being the coldest week of the year
Sources: Visual Crossing historic weather data, Swarm Maximal temperature each day of the year 3 years of data - Last updated on 2022-01-01

Weather conditions per year

Historic weather data based on the location I was at on that day based on my Swarm check-ins.

  • 2019 I experienced more cloudy weather than the following years
Sources: Visual Crossing historic weather data, Swarm Weather conditions per year 3 years of data - Last updated on 2022-01-01

Alcoholic Beverages per day

Alcohol drinks per day. Days with no data are rendered as white

  • Unless there are social obligations, or there is a party, I usually drink 0 alcoholic drinks
  • Friday and Saturday nights are clearly visible on those graphs
  • 2021 and summer/winter of 2019 also show the Wednesday night party in Vienna
  • Q2 and Q4 2020 clearly show the COVID lockdowns, as well as Q2 2021
  • Summer of 2021 all bars and dance clubs were open in Vienna
Sources: Manually Alcoholic Beverages per day 2.5 years of data - Last updated on 2022-01-01

Workouts in the gym

Each green square represents a strength-workout in the gym, I try my best to purchase day passes at gyms while traveling

  • During the first lockdown in Q2 2020 I didn't have access to a gym, and didn't track home-workouts
  • In 2021 I tend to work out less often on Sunday, the day I visit my family's place
  • In Q4 2021 I had a cold for a longer time
  • I went from ~50 workouts per year in 2014/2015 to ~200 per year in 2018 - 2021
Sources: Manually Workouts in the gym 7 years of data - Last updated on 2022-01-01

Living Style

From late 2017 to early 2020 I lived without a permanent home address, staying at various Airbnbs or taking over a few weeks of a lease from a friend

Sources: Manually Living Style 7 years of data - Last updated on 2022-01-01