I put my whole life into a single database

The takeaways at the very bottom of the page are valuable:

> Overall, having spent a significant amount of time building this project, scaling it up to the size it’s at now, as well as analysing the data, the main conclusion is that it is not worth building your own solution, and investing this much time. When I first started building this project 3 years ago, I expected to learn way more surprising and interesting facts. There were some, and it’s super interesting to look through those graphs, however retrospectively, it did not justify the hundreds of hours I invested in this project.

The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

/edit: quantified, not qualified

A simple back of the envelope calculation shows that Felix causes between 70 and 110 tonnes of CO2 emissions per year just from flying.

Paris accord says 1.5t per person per year, from all activities, Felix's flying alonre is ~10-15x current European yearly per person emissions and ~50-75x those compatible with +1.5C.

In my experience, tracking objective things like "nutrition" and "sleep hours" is immensely useful to reflect on what went wrong, and tracking subjective things like "mood" or "stress" is useless given hedonic adaptation or heavy swings that make problems obvious, and not need tracking.

What's key is be able to visualize metrics easily on the data and frictionless data entry, I've got a decent setup with iPhone Action + Obsidian + QuickAdd scripts on Obsidian Sync (mobile + laptop). for visualization I use Obsidian Bases and Obsidian notes that run Dataview code blocks and Chart.js, couldn't be happier.

I could track things that are not interesting to reflect on like vitamin D supplementation for accountability but I've never bothered, especially if it's taken ~daily.

I get that everyone wants to be cynical about this, but you really can't deny that both the visualization and sheer scale of data is impressive. The way the "my life in weeks" is done is also very cool, I'll be stealing that for myself.

Why don’t you just query Palantir DB by your human ID? It shows your entire life data and much more.

The value rarely shows up where you expected it to.

I kept a rough log of my sleep and mood for about a year with no specific goal. Mostly forgot about it. Then I had a weirdly bad few months and went back to look — turns out there was a pretty clear pattern I would've never noticed in the moment.

Maybe the framing of "was it worth it" is the wrong question. It's less like an investment with a return and more like keeping receipts. Useless 99% of the time, then suddenly you really need one.

> Back in 2019, I started collecting all kinds of metrics about my life. Every single day for the last 3 years I tracked over 100 different data types - ranging from fitness & nutrition to social life, computer usage and weather.

I know this is the type of person i would not like.

This was far more interesting than I first thought it would be when clicking the link. In particular, the place/time and life events and such being presented this way told a story and was fun.

I thought you created a database from scratch, got me excited! (I’m a db guy)

An interesting experiment, I think I'm too uncomfortable leaking data I don't yet know why someone would curate to me free of charge until I knew. If there was a FOSS suite like Home Assistant that would do a few of those things I might try it out, especially the weather (I would add air quality) correlation to mood and other subjective states.

Wow, this sounds amazing! I am a statistics and chart lover, I love tracking various types of data, but this? I can't even imagine how much time it must have taken to input all the data. Huge respect to you! Keep going.

This looks like it requires a heavy amount of discipline to track everything consistently over time. How do you build that into your daily routine?

The step count in NYC stands out like One World Trade Center compared to the rest of the building when looking at the skyline ;-)

I'd like to make the same but with Owntracks instead of Swarm and ActivityWatch instead of RescueTime.

No need to spy on him, he publishes everything.

It's all nice and all, but I'm just sitting here thinking "How can one afford all this flying around"?

I wonder how much time you spend daily on tracking things / data entry

I had an idea similar to this where you could add information about yourself and answer daily questions and get paid by companies who access this data. This could be an ethical way to share information benefitting all parties.

Taking “Know thyself” to a whole new level. I’d love to have these stats on me, if it could be done by inference, rather than conscious effort.

Hope they made backups :)

So it didnt end up working too well seeing that the latest data is from 4 years ago.

Stop bragging, mine fits into a csv file.

This might sound harsh but for someone who is keen on investing time to track so many things, you should invest some time in learning how to make better visualizations. A few tweaks here and there would really improve what you have.

Related to this, I highly recommend anyone to install github.com/ActivityWatch/activitywatch, it's an amazing tool to keep track of your computer use completely locally. I think there are lots of possibilities with data analysis/AI aimed to improved one self's life

Yeah, we've all put our whole lives into a single database. It's called the United States Government.

The value rarely shows up where you expected it to.

Maybe the framing of "was it worth it" is the wrong question. It's less like an investment with a return and more like keeping receipts. Useless 99% of the time, then suddenly you really need one.

This was far more interesting than I first thought it would be when clicking the link. In particular, the place/time and life events and such being presented this way told a story and was fun.

I thought you created a database from scratch, got me excited! (I’m a db guy)

This looks like it requires a heavy amount of discipline to track everything consistently over time. How do you build that into your daily routine?

The step count in NYC stands out like One World Trade Center compared to the rest of the building when looking at the skyline ;-)

I'd like to make the same but with Owntracks instead of Swarm and ActivityWatch instead of RescueTime.

No need to spy on him, he publishes everything.

It's all nice and all, but I'm just sitting here thinking "How can one afford all this flying around"?

Taking “Know thyself” to a whole new level. I’d love to have these stats on me, if it could be done by inference, rather than conscious effort.

Hope they made backups :)

The takeaways at the very bottom of the page are valuable:

The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

/edit: quantified, not qualified

A simple back of the envelope calculation shows that Felix causes between 70 and 110 tonnes of CO2 emissions per year just from flying.

Paris accord says 1.5t per person per year, from all activities, Felix's flying alonre is ~10-15x current European yearly per person emissions and ~50-75x those compatible with +1.5C.

Call all villagers and drag him to the struggle session!

Make him beg for rehabilitation!

Exactly, I stopped reading when I saw the flying stats. There are people who still haven't clocked where our climate is headed.

I get that you may have to see family abroad or maybe indulge for a holiday, but this is "I'm using an airplane to commute" kind of level.

And here I am trying to book my train tickets to go to London instead of flying even though it costs three times as much just to avoid a few kg of CO2 (among other things), it's making me angry.

yeah America treats flying as like taking a bus, so I am not at all surprised

Isn't this a drop in the ocean? Why would any 'normal' person forgo flying? How much CO2 emissions have 'world leaders' produced going to summits, or Taylor Swift and her fans flaying to concerts or war flights?

I could track things that are not interesting to reflect on like vitamin D supplementation for accountability but I've never bothered, especially if it's taken ~daily.

I think it's good to track mood swings, because it makes you notice them. After a while it makes you call out your own BS.

Why don’t you just query Palantir DB by your human ID? It shows your entire life data and much more.

can't afford a subscription

That made me laugh, but it was a sad laugh, because it is true.

I know this is the type of person i would not like.

You'll get crap here for it, but I agree. This is someone that has so little to worry about that he has to look for things. Then you look at his travel habits and jobs and you realize he's just one more rich bored guy showing off as best as possible.

I wonder how much time you spend daily on tracking things / data entry

Waiting for a neckband/choker wearable that can take transcription from my vocal cord nerve, so I can operate a chatbot silently. Yes, scientists have made impulse-to-speech lab equipment.

Just check one of the pie charts and it'll tell you!

Stop bragging, mine fits into a csv file.

There are exercises and supplements you can take that improve things slightly

To be fair, CSV files can be huge nowadays.

Don’t ask how I know…

A counter example:

I've been wearing an Apple Watch for close to 10 years. I've tracked my weight as well along those years but nothing crazy like OP. The Apple watch tracked plenty.

I had some strange symptoms and two doctors insisted I had a weak heart and potential heart failure. This was shocking! Turns out I do have a really "weak" rhythm, but heart failure is when your heart is progressively getting worse in it's pumping. I don't even remember which metric he looked at in my Apple health - but basically my heart has always been this way. A doctor looking at a single data point might think I have abnormally low blood pressure/heart rate, but if I've had this for 10 years with no change, the medical assessment is very different - it means nothing. Sometimes boring data is exactly what you need. For this reason, I will probably always wear an Apple watch (or equivalent) moving forward.

Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.

I had a similar epiphany a few years back when I started wearing a step-tracker/sleep monitor.

It was kinda interesting to see how many times I woke up, or track hours, but to be honest I realised after a few months that when my tracker said "You had good sleep", or "You had bad sleep" I was already aware - I woke up smiling, or grumpy depending on how I'd done.

I didn't ever look at the data and think "I want to go to bed now to catch up on the four hours I missed yesterday". I continued to have mostly consistent hours, but if I was doing something interesting I'd stay awake, and if I was tired I'd go to bed earlier naturally. The graphs and data wasn't providing anything of value, or encouraging me to change my behaviour in any significant way.

> it did not justify the hundreds of hours I invested in this project.

I agree with this but minimizing the cost changes the ROI.

Personally, I've discovered useful insights tracking various life metrics. But I also found quickly diminishing returns after a few weeks or months -- if an association isn't obvious within that timeframe it's either too much effort to isolate or too slow or small to matter.

At various points I've tracked calories, macronutrients, weight, allergens, supplements, sleep, exercise volume, exercise timing, nighttime screen use, spending/budget, air quality, and mood. Now I know what kind of cooking wrecks the air quality in my house, what foods I don't digest well, what various protein/carb/fat ratios look like on my plate, how much effort it takes to improve fitness, and that late exercise and alcohol wreck my sleep quality while blue screens have no measurable effect. But once I understand the associations I can alter my behavior and move on.

> The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

I would agree that continuing to track metrics every day long after they've stopped yielding interesting insights becomes a compulsion. But I think that's an argument for time-boxing the experiment rather than avoiding it altogether.

It's pure armchair psychology, but this type of project always makes me think about anxiety. Who really needs this level of self observation and control? At the same time, I really enjoy reading about it and I find the window into somebody else's world intriguing.

For me it's about managing ADHD-like (never diagnosed, and I don't care to assume) patterns, coupled with self-accountability. I have a self-improving dashboard (it kicks off Claude to propose additions based my positive/negative feedback on past attempts, and then builds them) that feels quite helpful. E.g. one of the things it added was fitbit integration that shoves my step count and resting heart rate in my face every day, and it's helped me drive my step count back up towards where I want it to be.

I do think it's not worth spending a whole lot of time on, though - hence why the first thing I did was add that mechanism to have Claude build it for me, with me mostly glancing at a plan and saying yes/no. It's the perfect thing to vibe-code - if it breaks, I revert a commit and it doesn't matter because nobody depends on it but me.

I have built a much more limited version of this that combines my journals, sketches, photos, geolocation etc. I found it useful for noticing patterns in my behaviour and in my irrationality. Journaling helped the most, because recording my feelings means acknowledging them and reviewing them.

Above all, it's just interesting. I enjoy reading about the day-by-day progression of a crush or my brutally honest feelings about a trip that produced stunning pictures. It weaves nuance into my history.

extensive tracking of self-related metrics to improve ones health is the equivalent to reading tons of self-help books to improve ones life/social skills/...

We already mostly know what makes people happy/healthy: personal connections, physical activity, healthy diet and some sort of purpose/goal in life that goes beyond day-to-day activities. The problem is that these things generally require (hard) work and can be unpleasant sometimes, so humans do what humans do and spend unreasonable amounts of time doing the more pleasant things such as reading and gathering info rather than applying these and what they already know. (That's not to say that a project like this can't be fun or lead to insights, especially across longer time spans, but i feel like all of the questions in the first paragraph have fairly obvious answers if you know yourself at all, that don't require extensive tracking of stats to get)

Cynical take: I didn't need to read to the bottom to know it was useless to track the correlation between drinking alcohol and dancing

I too learned this the hard way. I still haven't figured out why this is the case - like, is the inherent incidental irreducible complexity of human life too high, so it dominates majority of our actions?

Yep. Same goes for elaborate note-taking and productivity systems. The simpler, the less bookkeeping and cognitive overhead, the better.

Yeah, we've all put our whole lives into a single database. It's called the United States Government.

So it didnt end up working too well seeing that the latest data is from 4 years ago.

> it did not justify the hundreds of hours I invested in this project.

I agree with this but minimizing the cost changes the ROI.

> The whole "quantified self" movement might be more about OCD and perfectionism than anything else.

extensive tracking of self-related metrics to improve ones health is the equivalent to reading tons of self-help books to improve ones life/social skills/...

Cynical take: I didn't need to read to the bottom to know it was useless to track the correlation between drinking alcohol and dancing

Yep. Same goes for elaborate note-taking and productivity systems. The simpler, the less bookkeeping and cognitive overhead, the better.

Waiting for a neckband/choker wearable that can take transcription from my vocal cord nerve, so I can operate a chatbot silently. Yes, scientists have made impulse-to-speech lab equipment.

Just check one of the pie charts and it'll tell you!

There are exercises and supplements you can take that improve things slightly

To be fair, CSV files can be huge nowadays.

Don’t ask how I know…

A counter example:

I've been wearing an Apple Watch for close to 10 years. I've tracked my weight as well along those years but nothing crazy like OP. The Apple watch tracked plenty.

Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.

But you didn’t spend hundreds of hours on it, so when it did happen to be useful it seemed like an outsized benefit.

I would wager that for most people, most data about themselves will be useless and not worth collecting.

Of course you can’t know what data will be useless or not, so unless the cost of collecting it is minimal or nil (wearing a smart watch, writing down your weight each day/week), it’s probably not worth it.

Spending hundreds of hours to build a solution to capture all data about yourself to find interesting patterns has a huge assumption baked into it: that there are interesting patterns to find.

> Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.

Not sure if in your case the data was critical, since the doctor likely would have just had you wear a monitor for a while after to come to the same conclusion.

It's important to tell the readers how long you've been doing this - especially to those that also manage ADHD or ADHD-like symptoms.

Why? Because those individuals tend to spin something up, tell everyone about it (online, and offline) and then stop doing it few days later.

The result then ends up being a false signal for others in the same boat. People who read it, feel a spark of recognition ("someone like me actually figured this out"), and then invest real time, energy, maybe money, into replicating something the author themselves quietly abandoned two weeks later.

Just a small heads up from someone who used to get burned in the past :)

I had a similar epiphany a few years back when I started wearing a step-tracker/sleep monitor.

Eh, I found several interesting things from various tracking tools. Take a nap? Sleep is destroyed this night. Exercise in the evening? Same. Not something I’d pay attention to without noticing the chart afterwards.

There’s also the motivation factor. I’m not sure of the total %, but I certainly did some exercising just to fill the daily goal. Nothing life-changing, but for the price of a cheapo apple watch se once every 5 years or so, more than worth it.

It’s not unlike simplistic time tracking on my iphone. I spent a lot of time on bullshit websites. Obviously I knew it was happening, but the sheer magnitude was surprising. It’s akin to acute pain letting you know there’s a health problem vs something brewing in the background that you are vaguely aware of, but have no motivation to truly care about - one is far more noticeable than the other

Same. I had a Garmin for about 6 months and I eventually just stopped wearing it and sold it. Knowing how many steps I took today, checking it several times a day to see if I was meeting my goal, knowing how many vertical feet I skied.. none of this data ended up meaning anything to me.

Being aware, and being aware that you are aware are very similar things that are subtly different.

I was aware that alcohol affects your next day, even a little. That's because people always say that alcohol is bad for you (surprise surprise). I heard this, so you could say that I was aware. I generally thought about this as "a hangover is bad for you." and was somewhat dismissive of the "even a single drink has a bad effect" mantra.

I did some experimenting, and slowly realized that even a single drink can indeed have an impact on the next day. It's not a hangover, but an impact that I could feel nonetheless. I needed to do some light stats and a lot more journaling to build this awareness. I am now aware that I am aware.

Yours is qualitatively different because you’re not quantifying your life.

A good thing.

> Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.

Not sure if in your case the data was critical, since the doctor likely would have just had you wear a monitor for a while after to come to the same conclusion.

Yours is qualitatively different because you’re not quantifying your life.

A good thing.

Call all villagers and drag him to the struggle session!

Make him beg for rehabilitation!

can't afford a subscription

That made me laugh, but it was a sad laugh, because it is true.

But you didn’t spend hundreds of hours on it, so when it did happen to be useful it seemed like an outsized benefit.

I would wager that for most people, most data about themselves will be useless and not worth collecting.

Spending hundreds of hours to build a solution to capture all data about yourself to find interesting patterns has a huge assumption baked into it: that there are interesting patterns to find.

Right, but you don't necessarily need to spend hundreds of hours to capture most of this; the data is already out there. If there were a tool that could collect it all in one place and give you insights with minimal effort that would be pretty neat.

Like anything else, I think it comes down to having a good use case.

I've gotten deep into weightlifting/bodybuilding over the past couple of years, and that's the kind of hobby where micro-optimizations and data tracking can have a pretty big impact on results (and sort of necessary, you can't fly blind with things like diet, especially)

E.g. I track and weigh everything I eat, take body measuraments on a weekly basis, Dexa scans every few months, etc - for me it's worth it because I know what I want to do with the data. If I didn't have a goal, all that tracking would clearly be overkill.

It's important to tell the readers how long you've been doing this - especially to those that also manage ADHD or ADHD-like symptoms.

Why? Because those individuals tend to spin something up, tell everyone about it (online, and offline) and then stop doing it few days later.

Just a small heads up from someone who used to get burned in the past :)

I have data going back many years, but this recent effort is a few months old at this point. It's however notably an iteration that has reduced the amount of time I spend on collating and reviewing data, by automating away most of my previous manual effort, including most of the coding, and so I do suspect I'll stick with this for a very long time. A significant part of the prompt to the Claude part of it is to focus a substantial portion of plans on how to automate little things that costs me time, and it's doing a decent job at that.

I've absolutely not figured it out, but I now have an agent throwing stuff at the wall (with guidance from read access to e.g. my journal and a few other data sources) to figure it out for me, and it's gotten steadily better.

Being aware, and being aware that you are aware are very similar things that are subtly different.

> an impact that I could feel nonetheless. I needed to do some light stats and a lot more journaling to build this awareness.

If you could feel it why beed the stats?

Exactly, I stopped reading when I saw the flying stats. There are people who still haven't clocked where our climate is headed.

I get that you may have to see family abroad or maybe indulge for a holiday, but this is "I'm using an airplane to commute" kind of level.

And here I am trying to book my train tickets to go to London instead of flying even though it costs three times as much just to avoid a few kg of CO2 (among other things), it's making me angry.

Surprise surprise. Felix is as rich and out of touch as most rich and out of touch people.

Depends where you take the train to London, it is a much nicer experience anyhow than going to airports and people should consider that as well (ignoring climate stuff)!

On the price, the very annoying thing is that fuel for planes is not taxed! Changing this would require quite some effort (falls under some specific laws, that are old and nobody wants to touch, etc.) but I think everybody should just ask "honest tax on fuels!" as this will make less people say (or thin) "but climate change is a hoax". Planes are just unfair competition to other transport due to taxes!

> And here I am ...

Reminds me of the soggy straw memes floating around now. I've been having those why bother? thoughts as well.

yeah America treats flying as like taking a bus, so I am not at all surprised

> yeah America treats flying as like taking a bus, so I am not at all surprised

What does this have to do with Felix?

Couple of things: 1) NO ONE is suggesting any one forego flying altogether, or skipping their once-a-year overseas vacation or periodic family visit. 2) THIS level of flying is not normal and is exactly the kind of harmful behavior people have in mind when they complain about frequent flyers. 3) Whinging about summits and Taylor Swift is just a bad faith red herring argument. Obviously less flying is better, no matter by who. To the extent it's related to the topic at all, it bolsters the case for less air travel.

Why do anything for the greater good at all then? (Also there's a big gap between "forgo flying" and "fly every 2 weeks for 7 years")

Everything any one person does is a 'drop in the ocean'. Thankfully, we organize and do things collectively very well - it's in our fundamental nature going back to non-human ancestors, and there is a long, rich history of how much we accomplish. Alsmost nothing that has ever been accomplished has been done without a lot of people doing it together.

I think it's good to track mood swings, because it makes you notice them. After a while it makes you call out your own BS.

As someone with Schizoaffective Disorder Bipolar Type, if you are not diagnosed with a mood disorder, tracking "swings in you mood" when you have no clinical disorder seems like a disorder of its own.

I have had people tell me they were "manic". Then I showed them videos I took when I was manic and they see what I mean when I tell them they are not manic.

We have come to a place where we do not want even normal fluctuation in mood, and that is a illness of its own, but it is a cultural illness.

Surprise surprise. Felix is as rich and out of touch as most rich and out of touch people.

Depends where you take the train to London, it is a much nicer experience anyhow than going to airports and people should consider that as well (ignoring climate stuff)!

> And here I am ...

Reminds me of the soggy straw memes floating around now. I've been having those why bother? thoughts as well.

> yeah America treats flying as like taking a bus, so I am not at all surprised

What does this have to do with Felix?

Why do anything for the greater good at all then? (Also there's a big gap between "forgo flying" and "fly every 2 weeks for 7 years")

Strongly agree with this. I’ve been using Apple’s “mood” log for about two years now, and it is extremely helpful for me to have a concrete view of the history of my general affect.

“This entire month I’ve been feeling good, I want to pinpoint why,” or “it’s clear since stressor X entered my life, my affect is lower; how can I resolve this?”

These long term trends are harder for me to track without data. It might be easy for others, but not me!

I have had people tell me they were "manic". Then I showed them videos I took when I was manic and they see what I mean when I tell them they are not manic.

We have come to a place where we do not want even normal fluctuation in mood, and that is a illness of its own, but it is a cultural illness.

Like anything else, I think it comes down to having a good use case.

How long have you been tracking? Can you share an insight you've had from your data?

I've been weight lighting for ten years and initially tried to track things (down to how many reps I did of which exercise, with how much weight) and quickly came to the conclusion that is want worth it for me.

> an impact that I could feel nonetheless. I needed to do some light stats and a lot more journaling to build this awareness.

If you could feel it why beed the stats?

It's like any good cryptographic challenge - easier to validate the answer than to come up with it from scratch

Strongly agree with this. I’ve been using Apple’s “mood” log for about two years now, and it is extremely helpful for me to have a concrete view of the history of my general affect.

“This entire month I’ve been feeling good, I want to pinpoint why,” or “it’s clear since stressor X entered my life, my affect is lower; how can I resolve this?”

These long term trends are harder for me to track without data. It might be easy for others, but not me!

It's like any good cryptographic challenge - easier to validate the answer than to come up with it from scratch

How long have you been tracking? Can you share an insight you've had from your data?

I agree re: fuel taxes, but it’s a complete nonstarter: passengers would be voting against their wallets, and airlines would lobby against it since it’s a vote against their business model.

Maybe for some it's a lot more extreme than for others, but even if it's not so dramatic as to be categorized as a mental illness wouldn't you want to know if, say, there were a direct correlation between whether you went for your morning run and your mood later in the day?

I agree re: fuel taxes, but it’s a complete nonstarter: passengers would be voting against their wallets, and airlines would lobby against it since it’s a vote against their business model.

Felix is currently in Vienna, AT

Upcoming trips	From	To

Felix feels happy, excited 😃 (3 hours ago)

Felix ate today

54kcal of 2920

54g carbs of 350g

24g protein of 200g

16g fat of 80g

Food	Amount
Club Mate	500 ml
Chicken Breast	500c
Rice	200g
Show all food entries

Weight	81.8kg / 180.4lbs today
Height	1.93m (6'4")
Slept	9 hours (last night)
Last Workout	2 days ago
Computer Time	12,677 hours (since 2013)
Inbox	40 emails
Personal Todo Items	173 tasks
Unique Website Visitors	162,457 (since August)
Database size	380,000 data entries

Most recent photos

Last code commit: an hour ago

on GitHub repo KrauseFx/krausefx.com

Background: Why I put my whole life into a single database

Back in 2019, I started collecting all kinds of metrics about my life. Every single day for the last 3 years I tracked over 100 different data types - ranging from fitness & nutrition to social life, computer usage and weather.

The goal of this project was to answer questions about my life, like

How does living in different cities affect other factors like fitness, productivity and happiness?
How does sleep affect my day, my fitness level, and happiness?
How does the weather, and the different seasons affect my life?
Are there any trends over the last few years?
How does computer time, work and hours in meetings affect my personal life?

Since the start of this project, I collected ~380,000 data points, with the biggest data sources being:

Data Source	Number of data entries	Type of data
RescueTime	149,466	Daily computer usage (which website, which apps)
Foursquare Swarm	126,285	Location and POI data, places I've visited
Manually entered	67,031	Fitness, mood, sleep, social life, health, nutrition, energy levels, TV, stress, ...
Manually entered date ranges	19,273	Occupation, lockdown status, living setup
Weather API	15,442	Temperature, rain, sunlight, wind
Apple Health	3,048	Days of steps data

Naturally after I started collecting this data, I wanted to visualize what I was learning, so I created this page. Initially, the domain whereisFelix.today (now renamed to howisFelix.today) started as a joke to respond to friends asking when I’d be back in NYC or San Francisco. Rather than send them my schedule, I’d point them to this domain. However, now it’s more than my location: it’s all of me.

Rules I setup for the project

Use a single database, owned and hosted by me, with all the data I’ve collected over the years
Be able to easily add and remove questions on the fly, as I learn what’s beneficial to track
Full control of how the data is visualized
Works well for frequent flyers with mixed time zones
100% fully open source, MIT licensed and self-hosted

I selected 48 graphs to show publicly on this page. For privacy reasons, and to prevent any accidental data leaks, the graphs below are snapshots taken on a given day.

Number of Data Entries over Time

Visualization of the number of data entries in FxLifeSheet over the last 10 years, and where the data came from.

Initially (2014) the only data used was RescueTime and Foursquare Swarm location data
Once I started the FxLifeSheet project in April 2019, I manually tracked 75 data entries every day, ranging from mood, sleep, social life, to fitness data
I was able to retrospectively fetch the historic weather data based on my location on a given day
I also implemented other import sources, like fetching my historic weight and the number of steps from Apple Health

Number of Data Entries over Time

10 years of data - Last updated on 2022-01-01

Days tracked my Mood to be Happy & Excited

On days where I tracked my mood to be "happy" & "excited", the following other factors of my life were affected

50% more likely to have pushed my comfort zone
44% more likely to have meditated that day
33% more excited about what's ahead in the future
31% more likely to drink alcohol that day (parties, good friends and such)
28% more time spent reading or listening to audio books
26% more likely to have worked on interesting technical challenges
26% warmer temperature that day
20% more likely to have learned something new that day
45% less time spent in video & audio calls that day

Manually

Days tracked my Mood to be Happy & Excited

2.5 years of data - Last updated on 2022-01-01

Flying Stats - General

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

The stats clearly show the impact of COVID starting 2020
Sunday has been my "commute" day, flying between San Francisco, New York City and Vienna

JetLovers, Swarm

Flying Stats - General

7 years of data - Last updated on 2022-01-01

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 actually much time there

JetLovers, Swarm

Flying Stats - Top

7 years of data - Last updated on 2022-01-01

My Life in Weeks

Inspired by Your Life in Weeks by WaitButWhy, I use Google Sheets to visualize every week of my life, with little notes on what city/country I was in, and other life events that have happened.

The first 14 years I didn't really get much done
I can highly recommend taking a few weeks (or even months) off between jobs (if you have the possibility)
Yellow area indicates no active full-time employment
Shades of blue indicate my full-time employments
Shades of red is formal education
You can create your own version using my template

Manually

My Life in Weeks

27.5 years of data - Last updated on 2022-02-24

Average Daily Steps over Time

Average daily steps measured through the iPhone's Apple Health app. I decided against using SmartWatch data for steps, as SmartWatches have changed over the last 8 years.

I walked a total of 22,830,860 steps over last 8 years
I walk more than twice as much when I'm in New York, compared to any other city
In NYC I had the general rule of thumb to walk instead of taking public transit whenever it's less than 40 minutes. I used that time to call friends & family, or listen to audio books
Although Vienna is very walkable, the excellent public transit system with subway trains coming every 3-5 minutes, has caused me to walk less
San Francisco was always scary to walk

Apple Health

Average Daily Steps over Time

8 years of data - Last updated on 2022-01-01

Correlation: Weight and Resting Heart Rate

This graph clearly shows the correlation between my body weight and my sleeping/resting heart rate. The resting heart rate is measured by the Withings ScanWatch while sleeping, and indicates how hard your heart has to work while not being active. Generally the lower the resting heart rate, the better.

I started my lean bulk (controlled weight gain combined with 5 workouts a week) in August 2020
My resting heart rate went from 58bpm to 67bpm (+9bpm) from August 2020 to March 2021 with a weight gain of +8.5kg (+19lbs) as part of a controlled lean-bulk combined with a 5-day/week workout routine
The spike in resting heart rate in July & August 2021 was due to bars and nightclubs opening up again in Austria
After a night of drinking, my resting/sleeping heart rate was about 50% higher than after a night without any alcohol
The spike in resting heart rate in Oct/Nov/Dec 2021 was due to having bronchitis and a cold/flu, not getting correct treatment early enough

Withings ScanWatch, Withings Scale

Correlation: Weight and Resting Heart Rate

1.5 years of data - Last updated on 2022-02-09

How healthy have I been over the Years?

Every day I answered the question on how healthy I felt. In the graph, the yellow color indicates that I felt a little under the weather, not sick per se. Red means I was sick and had to stay home. Green means I felt energized and healthy.

During the COVID lockdowns I tended to stay healthier. This may be due to not going out, no heavy drinking, less close contact with others, etc. which resulted in me having better sleep.
Usually during excessive traveling I get sick (cold/flu)
Q4 2021 I had bronchitis, however, I didn't know about it at the time and didn't get proper treatment
Overall I'm quite prone to getting sick (cold/flu)

Manually

How healthy have I been over the Years?

2.5 years of data - Last updated on 2022-01-01

Days with more than 4 Alcoholic Drinks

On days where I had more than 4 alcoholic beverages (meaning I was partying), the following other factors were affected

21x more likely to dance
80% more likely to take a nap the day of, or the day after
60% more time spent with friends
40% warmer temperatures, and 40% less precipitation. There weren't many opportunities for parties in Winter due to lockdowns in the last 2 years. Also, people are more motivated to go out when it's nice outside.
25% more steps

Manually

Days with more than 4 Alcoholic Drinks

2.5 years of data - Last updated on 2022-01-01

Mood over the Years

My FxLifeSheet bot asks me 4 times a day how I'm feeling at the moment.

This graph groups the entries by month, and shows the % of entries for each value (0 - 5) with 5 being very excited, and 0 being worried.
I designed the ranges so that 0 or 5 are not entered as much. 0 is rendered as dark green at the top, whereas 5 is rendered as light green at the bottom.
For privacy reasons I won't get into some of the details on why certain months were worse than others.

Manually

Mood over the Years

4 years of data - Last updated on 2022-01-01

Location History

Every Swarm check-in over the last 7 years visualized on a map, including the actual trip (flight, drive, etc.)

Swarm

Location History

7 years of data - Last updated on 2022-01-01

Location History - Cities

Every Swarm check-in over the last 7 years visualized, zoomed in

Swarm

Location History - Cities

7 years of data - Last updated on 2022-01-01

Most visited POIs, grouped by City

Each time I did a check-in at a place (e.g. Coffee, Restaurant, Airport, Gym) on Foursquare Swarm at a given city, this is tracked as a single entry.

Swarm

Most visited POIs, grouped by City

7 years of data - Last updated on 2022-01-01

Number of Check-Ins grouped by City

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

Swarm

Number of Check-Ins grouped by City

7 years of data - Last updated on 2022-01-01

Top Categories of Check-Ins

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
Airports being the #4 most visited category was a surprise, but is accurate. A total of 403 airport check-ins, whereas a flight with a layover would count as 3 airport check-ins
Earlier in my life, I didn't always check into 'commute' places like public transit and super markets

Swarm

Top Categories of Check-Ins

7 years of data - Last updated on 2022-01-01

Number of Swarm Check-Ins over Time

Number of Foursquare Swarm check-ins on each quarter over the last 10 years. I didn't use Foursquare Swarm as seriously before 2015. Once I moved to San Francisco in Q3 2015 I started my habit of checking into every point of interest (POI) I visit.

Q3 2015 I moved to San Francisco, however I couldn't use Swarm yet, since my move was a secret until the official announced at the Twitter Flight conference
Q2 2020 clearly shows the impact of COVID with Q3 already being open in Austria
Q3 2021 the vaccine was already widely available and I was able to travel/visit more again
My time in New York was the most active when it comes to check-ins. When I'm in NYC, I tend to eat/drink out more, and grab to-go food, which I do way less in Vienna

Swarm

Number of Swarm Check-Ins over Time

10 years of data - Last updated on 2022-01-01

Location History

Every Swarm check-in visualized on a map. Only areas where I've had multiple check-ins are rendered.

Swarm

Location History

7 years of data - Last updated on 2022-01-01

Days in Full Lockdown

Number of days per year that I've spent in full lockdown, meaning restaurants, bars and non-essential stores were closed.

I escaped parts of the Austrian lockdown by spending time in the US when I was already vaccinated
Surprisingly 2021 I spent more days in a full lockdown than in 2020, even with vaccines available

Manually

Days in Full Lockdown

3 years of data - Last updated on 2022-01-01

Effects of the Lockdowns

How was my life affected by the recent COVID lockdowns? As lockdown day I classify every day where places like restaurants, gyms and non-essential stores were closed.

200% more time spent in audio & video calls with friends (non-work related)
60% more likely to follow my meal plan (macros & calories)
24% less steps
40% less alcoholic beverages
50% colder temperatures: Lockdowns tended to happen in Autumn and Winter
100% less likely to dance

Manually

Effects of the Lockdowns

3 years of data - Last updated on 2022-05-23

Alcoholic Beverages per Day

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

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

Manually

Alcoholic Beverages per Day

2.5 years of data - Last updated on 2022-01-01

Alcoholic Beverages per Month

Each bar represents a month, the graph shows the number of alcoholic beverages on a given day, with '5' being 5 or more drinks.

Unless there are social obligations, or there is a party, I usually drink 0 alcoholic drinks
In May 2019, the 0 bar is rendered to be 55%, meaning on 55% days of that month I didn't drink any alcohol
July 2021 Austrian night life was fully open up again, with most COVID restrictions being lifted

Manually

Alcoholic Beverages per Month

2.5 years of data - Last updated on 2022-01-01

Gym Workouts

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 count home-workouts as gym visits
In 2021 I tended 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

Manually

Gym Workouts

7 years of data - Last updated on 2022-01-01

Food Tracking - Macros

On weeks where I have a routine (not traveling), I track most of my meals. Whenever I scale my food, I try to guess the weight before to become better at estimating portion sizes.

Tracking macros precisely is the best way to lose/gain weight at a controlled and healthy speed
When I first started tracking macros, additionally to already working out regularly, is when I started seeing the best results
It takes a lot of energy to be consistent, but it's worth it, and it will make you feel good (e.g. feeling good about using a spoon to eat plain Nutella if you have the macros left)
Gaining and losing weight is pretty much math, if you track your macros and body weight

MyFitnessPal

Food Tracking - Macros

4 years of data - Last updated on 2022-02-17

Gym Workouts grouped by Month

Percentage of days I went to the gym

During the first lockdown in Q2 2020 I didn't have access to a gym, and didn't count home-workouts as gym visits
Generally I hit the gym 5 days a week when I'm at home, but as shown on this graph it ends up being less, mostly due to traveling, and occasional colds

Manually

Gym Workouts grouped by Month

2.5 years of data - Last updated on 2022-01-01

Fitness Bulk & Cut Season

I'm following a pretty regular bodybuilding routine, a 3-day workout split, and a normal bulk & cut seasons

During times where fitness isn't high up on my priority list, I usually switch to maintenance
During a cut, I have a slight kcal deficit of about 300kcal, to not negatively impact the rest of my life
During the bulk, I aim to gain about 300g of body weight per week
During a cut, I tend to track my meals more precisely than during a bulk or while maintaining
Purple = Cut
Brown = Bulk
Blue = Maintenance

Manually

Fitness Bulk & Cut Season

4 years of data - Last updated on 2022-01-01

Weight History of 8 Years

Historic weight, clearly showing the various bulks and cuts I've made over the years. Only the last 5 years are rendered in this graph, with the last 3 years having tracked my weight way more frequently.

Lowest recorded weight was 69kg/152lbs in 2014 (age 20)
Highest recorded weight was 89.8kg/198lbs in 2021 (age 27)
I gained 20kg (44lbs) while staying under 12% body fat on 193cm (6"4)

Withings Scale

Weight History of 8 Years

9 years of data - Last updated on 2022-02-17

Bulk & Cut Phase visualized

I usually have slow bulk & cut phases, where I gain and lose weight at a controlled speed, combined with tracking my meals.

I only track my weight if I didn't drink alcohol the night before, and after getting a full night's sleep, since otherwise the weight fluctuates a lot
Generally, you can pretty much calculate your weight on a certain date, if you consistently track your meals, and correctly calculated your macros

Withings Scale, weightgrapher.com

Bulk & Cut Phase visualized

1 years of data - Last updated on 2022-01-01

Days with more than 15,000 Steps

On days where I walked more than 15,000 steps (I walked an average of 9200 steps a day the last 3 years)

60% more time spent with friends in real-life
50% warmer temperature that day
40% more likely to socialize with friends before going to sleep
35% more likely to be a weekend day
20% less likely to take a nap that day
30% less likely to correctly track my macros (food)
30% less time spent in work calls/meetings
30% less anxious
40% less likely to meditate
40% less time spent writing code
40% less likely to be a rainy day
50% less time spent watching TV
95% less likely to be a day in lockdown

Apple Health

Days with more than 15,000 Steps

2.5 years of data - Last updated on 2022-01-01

How does longer Sleep Duration affect my Day?

On days where I had a total sleep duration of more than 8.5 hours, the following other factors were affected

65% more likely to have cold symptoms
60% more likely to have headache
40% more social media usage
30% more likely to be a rainy day
20% more likely to be a weekend
15% more likely to have bad/stressful dreams
12% colder weather on average
20% less likely to hit the gym that day
24% less energy
Overall, it's clear that days with a longer sleep duration tend to be significantly worse days. This is most likely due to the fact that I try to sleep a maximum of 8 hours, and if I actually sleep more than usually because I'm not feeling too well, or even sick

Withings Scan Watch, Manually

How does longer Sleep Duration affect my Day?

2.5 years of data - Last updated on 2022-01-01

Air Quality in various Rooms

I used the Awair Element at home in Vienna, in every room over multiple days

Overall, the air quality in Vienna is excellent. Just opening the windows for a few minutes is enough to get a 100% air score
The smaller the room, the more difficult it is to keep the CO2 levels low
The only room where I'm still struggling to keep the CO2 levels low is my bedroom, which is small, and doesn't offer any ventilation. Keeping the doors open mostly solves the high CO2 levels, however comes with other downsides like more light
Probably obvious for many, but I didn't realize ACs don't transport any air into the room, but just moves it around
Opening the windows for a longer time in winter will cause low humidity and low temperatures, so it's often not a good option
I didn't learn anything from the Chemicals and PM2.5 graphs

Awair

Air Quality in various Rooms

1 years of data - Last updated on 2022-02-09

RescueTime Computer Usage Categories

Using RescueTime, I tracked my exact computer usage, and the categories of activities in which I spend time with.

Over the last 7 years, I went from spending around 10% of my time with communication & scheduling, to around 30%
Over the last 7 years, I went from spending around 33% of my time with software development, to less than 10% (now that I'm not currently full-time employed)
All other categories stayed pretty much on the same ratio over the last 7 years
Total amount spent on my computer went down significantly after having left my job late 2021
Tracking productivity levels automatically is difficult to get right, as it's hard to classify certain activities.
Day to day I'm using Timing App which has a significantly nicer user experience, however I just had many additional years of data on RescueTime
I highly recommend every professional to track their computer usage. It's surprising to see how many hours a day you actually get on your computer, and how much of it is considered productive. Timing App shows the amount of hours of the day on the Mac's status bar, and it's been extremely useful

RescueTime

RescueTime Computer Usage Categories

7 years of data - Last updated on 2022-01-01

How does Summer affect my Life?

Summer (being from 21st June to 23rd September) has the following effects on my life:

Chances of taking a freezing cold shower goes up by 100%
I walk 33% more steps in Summer
30% more likely to hit the gym
23% more alcoholic beverages (there were no lockdowns in Summer)
20% less time spent reading news & opinions (as per RescueTime classifications)
40% less likely to be sick
40% less time spent on Entertainment on my computer (as per RescueTime classifications)
30% less likely to have bad dreams

Manually

How does Summer affect my Life?

2.5 years of data - Last updated on 2022-01-01

How does Winter affect my Life?

Winter (being from 21st Dec to 20th March) has the following effects on my life:

Online shopping time going up by 100%, most likely due to the last Winters having spent in lockdown
Chances of having cold symptoms goes up 45%
35% less likely to take a freezing cold shower
Unsurprisingly, I'm exposed to less solar energy in Winter, make sure to get enough Vitamin D

Manually

How does Winter affect my Life?

2.5 years of data - Last updated on 2022-01-01

Days spent in each Country

Percentage of days spent in each country over the last 4 years

International travel has slowed down significantly since COVID started
Traveling without a stop home for more than 3 weeks gets exhausting for me, I prefer doing more shorter travels instead

Manually

Days spent in each Country

4 years of data - Last updated on 2022-01-01

Living Style

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

Manually

Living Style

7 years of data - Last updated on 2022-01-01

Cold Symptoms

Number of days each month where I had cold symptoms (dark green [1] = day with cold symptoms), which I classify as having a runny nose, feeling light-headed or having light ear pain.

Clearly the cold months of 2019 and 2021 I had significantly more days with cold symptoms
Winter 2021 was a full lockdown, I assume this reduced the risk of getting sick
October and November 2021 I had bronchitis, without getting the proper treatment

Manually

Cold Symptoms

2.5 years of data - Last updated on 2022-01-01

What are Weekends like?

Weekends for me naturally involve less working time, more going out, and social interactions, as well as visiting family members outside the city

150% more computer time spent on "Entertainment", which is mostly coming from occasionally playing Factorio or Age Of Empires with friends at LAN-Party gatherings
74% more time spent watching TV
60% more time spent with friends IRL
55% more dancing, when going out
45% more likely to have a headache, due to drinking alcohol the night before
25% less gym visits, mostly due to family gatherings and not being in the city
45% less likely to properly track my macros/meals, mostly due to family gatherings and going out

Manually

What are Weekends like?

2.5 years of data - Last updated on 2022-01-01

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

Turns out, days in Summer are warmer than days in Winter
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

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

Visual Crossing historic weather data, Swarm

Weather Conditions per Year

3 years of data - Last updated on 2022-01-01

CO2 Emissions from flying

My radiation exposure, as well as CO2 emissions from all my flights over the last 7 years

Nomadlist

CO2 Emissions from flying

7 years of data - Last updated on 2022-04-28

Resting Heart Rate based on location

I noticed myself feeling more refreshed whenever I spent a night at my childhood bedroom at my parents' on the countryside.

On average, my sleeping heart rate when sleeping at my parents' home is less than when sleeping at my own place in Vienna
All nights above 70 bpm are usually associated with either drinking alcohol in the evening, being sick, or sleeping for only a short amount of time (e.g. before a flight)
Even removing all 70+ bpm nights, there is a clear difference between nights spent at my own place in the city, compared to the nights spent on the countryside

Withings ScanWatch, Manual

Resting Heart Rate based on location

1 years of data - Last updated on 2022-05-30

Spotify Listening Duration over Time

Spotify tracks every single interaction on their end, including every single song you've ever listened to, and if you finished or skipped each song.

Since 2013, I've listened to a total of 480,155 minutes of music, that's 8,002 hours, or 334 days
That's 202,148 songs, however I only finished 49% of them
End of 2013 I didn't have an active Spotify subscription, due to issues accessing it from Austria
During some areas in my life, I listened to Cercle/Coccolino Deep sets on YouTube, therefore using Spotify less
I stored a total of 312 Spotify Discover Weekly playlists, every single one since December 2015
As part of this script, I built a tool to create a playlist of the 500 most listened to songs, as well as the first 500 songs listened to
In total, I have paid 1,080 EUR for Spotify Premium

Spotify

Spotify Listening Duration over Time

9 years of data - Last updated on 2022-05-01

Number of Instagram Stories per Day

Since I've built instapipe.net, I have all my Instagram Stories available in my own database. The blue 'Monthly' area shows the monthly average of IG stories posted, while the green shows the 'Quarterly' average and purple the 'Yearly' average.

April 2019 I built instapipe while traveling in Hong Kong and South Korea
November 2019 I had a deadline at work, as well as being sick for a few days
March 2020, the start of COVID, shows a clear downwards trend the following months until June when Austria opened up again
September 2021 I was on a roadtrip through Iceland, posting many pictures & videos
Overall you can see a clear downwards trend of the purple 'Year' line over the last 3 years
Since April 2019, I have published a total of 1,906 Instagram stories, averaging 1.6 Stories per day

Number of Instagram Stories per Day

3 years of data - Last updated on 2022-06-01

How does High Temperature affect my Life?

On days with a maximum temperature of more than 26 Celsius (78.8 Fahrenheit), the following other factors were affected

80% more likely to take a freezing cold shower
37% more likely to hit the gym
26% more daily steps
20% more alcoholic beverages
15% more likely to go out in the evening
13% less likely to take a nap
20% less time in a code editor
21% less likely to be sick
Generally lower stress/anxiety levels
100% less likely to be in a COVID related lockdown

Visual Crossing historic weather data, Manually

How does High Temperature affect my Life?

2.5 years of data - Last updated on 2022-01-01

GitHub Open Source Contributions

GitHub open source contributions visualized using GitHub's own contribution graph. The graphs only count code commits to open source repositories.

I started fastlane September 2014, and worked on it until early 2018
Early 2018 I started working on fastlane.ci which slowly got shut down over time by Google
January 2019 I decided to leave Google, as fastlane.ci wasn't going anywhere
Early 2019 I worked on instapipe.net and this very project via FxLifeSheet
Second half of 2019, until Summer 2021 I worked at Root on commercial software, which doesn't show up on those graphs
End of 2021 I resumed work on FxLifeSheet to build this very page

GitHub

GitHub Open Source Contributions

11 years of data - Last updated on 2022-01-01

Investment Management & Simulations

Every second week I track my current investments and cash positions. It shows me how to most efficiently re-balance my investments in case they're off track, while also minimizing the occuring trading fees.

I have a burndown chart, which visualizes how my networth would grow/drop over time in various scenarios
I have a graph that ensures I have the right target distribution of high, medium and low risk positions
Whenever I take on a potential new project/role, I simulate the various outcome scenarios that could happen over the next few years
For obvious reasons, I can't include more of the graphs and simulations I have available

Manually

Investment Management & Simulations

8 years of data - Last updated on 2022-02-09

Annual Money Flow

Inspired by a Reddit finance community, I had been creating annual money flow charts to clearly see how much money I earned, where I spent how much, and how much I saved. The chart below isn't mine (for privacy reasons), but just an example I created.

Not owning an apartment, and living in Airbnbs as a nomad I actually spent less money. This was due to not having to buy any furniture, appliances, etc. but also because the number of items I could buy for myself was limited, as everything was limited to be able to fit into 2 suitcases. Additionally I didn't have to pay any rent whenever I traveled for my job, or during conferences.
Misc. subscriptions/expenses are adding up quickly
Having an End-Of-Year summary from your credit card provider, and always using your card when possible, is a great way to get those numbers
Creating this chart is still a lot of work, as you have to keep in mind that some expenses are not solely yours, but you might have covered for a group (e.g. booked a larger Airbnb), or got reimbursed

Chase Credit Card Year Summary, sankeymatic.com, Manually

Annual Money Flow

5 years of data - Last updated on 2022-02-09

More Details on how this works

This project is custom-built for my own personal use, the resulting code is 100% open source on KrauseFx/FxLifeSheet. There are 3 components to this project:

• 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.

Each row has a timestamp, key and value.

The timestamp is the time for which the data was recorded for. This might differ from imported_at which contains the timestamp on when this entry was created. Additionally I have a few extra columns like yearmonth (e.g. 202010), which makes it easier and faster for some queries and graphs.
The key describes what is being recorded (e.g. "weight", "locationLat", "mood"). This can be any string, and I can add and remove keys easily on the fly in the FxLifeSheet configuration file without having to modify the database.
The value is the actual value being recorded. This can be any number, string, boolean, etc.

Early on in the project I made the decision not to associate an entry to a specific day due to complexities when traveling and time zones, since the idea was just to detect trends using the collected data. It became clear that detecting trends is only a small part of what can be done with the data, so I wrote a script to associate each entry to the correct date.

• Data Inputs

To populate the data, I manually answer questions multiple times a day through a Telegram bot. These questions span from fitness or health (e.g. nutrition, exercise, sleep, etc.) to questions about my life (e.g. how I’m feeling, how much time I spend on social media, etc.). The extensible use of the Telegram API made this easy, and even allowed me to customize the keyboard to have predefined replies based on the question asked.

Additionally I can fill-out date ranges with specific values, for example lockdown periods, and bulking/cutting fitness seasons.

• 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. You can find the full source code on KrauseFx/FxLifeSheet - visual_playground.

But what about privacy?

I actually published many privacy projects for iOS. That little green/orange LED that’s rendered on iOS when you record something? Yep, that was me! So why this project?

Much of the data visualized here, is data many larger companies already have about you. Why shouldn’t you have it as well?
The data is stored in my own, private database, not connected to any service
The data shown above seems very personal but doesn’t actually expose any sensitive information. For example, disclosing your current location, your home address, or stores and places you frequently visits is sensitive and potentially dangerous. Even looking at the map of my movement data, you won’t get any more information that what most people have in their public Twitter bio.

Can I use this for my life?

Yes, you could. However, setting up FxLifeSheet is a bit of a challenge and requires engineering skills and time. Some of the features are specific to my life (like the services I use), and so you’d have to modify parts of the codebase. This project is 100% open source MIT licensed, so you can use, and modify everything to your liking. However, I don’t plan on productionizing this project, nor providing any support on GitHub for it.

Realistically, if you want to get started with QuantifiedSelf, you can use one of the services availalbe. I’d recommend looking for the following:

Make sure you get full access to the data, as a data export, or a public API
See how the project maintainers react to feedback. Do they listen to their users, and address issues?
How much time do you want to invest tracking your data?
What’s their business model? Are they sustainable and charge money for their service?
Don’t use anything that’s only available as an app: In my experience apps tend to be their own data silo, their feature sets are limited, and analyzing data on the big screen is way more efficient.

Conclusion

I’ve always been fascinated by tracking my own data, and seeing it visualized. While I can’t pinpoint the reason why, I remember having this fascination growing up, asking myself questions like How many steps did I walk in my life?, and Did I turn right more often or left?.

Having read many articles similar to r/QuantifiedSelf/, I really loved the visualizations, but disliked the fact that almost all solutions were data-silos (e.g. standalone iOS apps, Gyroscope, …) without having full control over the data, nor how it’s visualized. Because the data collection spans multiple years, I was apprehensive to rely on any startup or service that runs the risk of being shut down. Additionally, every individual may have differences in how they want to visualize or analyze the data.

Apple was in a great position to improve the current state with Apple Health, but they completely failed with their implementation on both the APIs, as well as the actual Health app.

One aspect I overestimated is the number of days you will track: If you want to look into how many steps you walked in a given city, you’ll quickly notice the number of days in each city already being quite low. You’d then also slice the data by season or temperature, since you naturally walk less on very cold days, ending up with only a handful of days outside your main residence.

Overall, having spent a significant amount of time building this project, scaling it up to the size it’s at now, as well as analysing the data, the main conclusion is that it is not worth building your own solution, and investing this much time. When I first started building this project 3 years ago, I expected to learn way more surprising and interesting facts. There were some, and it’s super interesting to look through those graphs, however retrospectively, it did not justify the hundreds of hours I invested in this project.

I’ll likely continue tracking my mood, as well as a few other key metrics, however will significantly reduce the amount of time I invest in it.

I’m very happy I’ve built this project in the first place, as it gave me a much better awareness of everything going on in my life. I’m excited to have built this website to wrap-up this project and show-case some of the outcomes to the public.

2025 Update: I’ve stopped collecting data and working on this project, but I will keep this page alive.

Hacker Times

Hacker Times

I put my whole life into a single database

Discussion

Discussion

Felix is currently in Vienna, AT

Felix feels happy, excited 😃 (3 hours ago)

Felix ate today

Most recent photos

Background: Why I put my whole life into a single database

Number of Data Entries over Time

Days tracked my Mood to be Happy & Excited

Flying Stats - General

Flying Stats - Top

My Life in Weeks

Average Daily Steps over Time

Correlation: Weight and Resting Heart Rate

How healthy have I been over the Years?

Days with more than 4 Alcoholic Drinks

Mood over the Years

Location History

Location History - Cities

Most visited POIs, grouped by City

Number of Check-Ins grouped by City

Top Categories of Check-Ins

Number of Swarm Check-Ins over Time

Location History

Days in Full Lockdown

Effects of the Lockdowns

Alcoholic Beverages per Day

Alcoholic Beverages per Month

Gym Workouts

Food Tracking - Macros

Gym Workouts grouped by Month

Fitness Bulk & Cut Season

Weight History of 8 Years

Bulk & Cut Phase visualized

Days with more than 15,000 Steps

How does longer Sleep Duration affect my Day?

Air Quality in various Rooms

RescueTime Computer Usage Categories

How does Summer affect my Life?

How does Winter affect my Life?

Days spent in each Country

Living Style

Cold Symptoms

What are Weekends like?

Maximal Temperature each Day of the Year

Weather Conditions per Year

CO2 Emissions from flying

Resting Heart Rate based on location

Spotify Listening Duration over Time

Number of Instagram Stories per Day

How does High Temperature affect my Life?

GitHub Open Source Contributions

Investment Management & Simulations

Annual Money Flow

More Details on how this works

But what about privacy?

Can I use this for my life?

Conclusion