# Hacking Life pt. 1: Defining a Data Diary

Trying to escape local optima on a random walk through life.

24.03.2021

Note: This is a WIP; I’ll build on this post from time to time when I make changes to the method, calculate new statistics or gain other new insights. Part 2 here

I’ve never really thought that the Quantified self movement was the right fit for me. There are certain things I’ve tried before, though. For example, I’ve tracked my calories rather successfully but only over a relatively short amount of time, and just in order to get a better feeling for my nutrition and wing it from there. But tracking stuff over a longer period of time? No thanks, I’m fine trying to keep my TODOs from taking over my life already…

However, I do, in general, try to optimize my life. I plan quite a bit in order to feel and be more fit, alert and productive: I try to sleep for eight hours in order to be alert the next day, I build habits that I know will benefit me, I try to eat healthily and exercise regularly because it makes me feel great. But how can I be so sure that eight hours is the right amount of sleep for me, or that my habits are actually sensible?

Today, I figured that it actually doesn’t have to be that much work to find out.

I will start a data diary which let’s me check on various correlations in my life, like How does the amount of sleep I get correlate with how productive I feel?, How do the people I spend my time with correlate with how happy I feel? or Is meditation correlated with my perceived stress levels?

I already journal every day to get a detailed insight into my life and reflect on things, but I believe a more data-driven approach will be a fun and effective addition. I know it’s a pretty coarse method, but I bet I can get some valuable insights out of this what, daily 1 minute investment?

## Defining a Data Diary

At first, I will need some data, so today I set up a Google sheets table, currently containing the following fields (I might add/remove fields eventually, as I see fit):

• The date,
• day of the week (generated from date),
• my perceived happiness, on a scale of 1-10,
• my perceived fitness, also from 1-10,
• my perceived productivity,
• my perceived stress level,
• the weather, $$w \in \{\mathrm{sunny}, \mathrm{rainy}, \mathrm{cloudy}\}$$, although I might supplement this with more detailed weather data which I can sideload using the date later on,
• the people I spent time with,
• how long I spent time with those people,
• a string list of activities I’ve performed,
• a string list of highlights of the day,
• the amount of hours I’ve exercised,
• the amount of hours I’ve spent outside,
• the healthfulness of the food I ate, on a scale of 1-10,
• how long I meditated,
• whether I stretched,
• the time I woke up,
• the time I went to bed,
• the hours of sleep I got, calculated from the two previous fields,
• for how long I’ve used my phone that day, tracked by an app.

I use Google sheets because – like any other spreadsheet program – it lets me calculate certain fields automatically, e.g. hours of sleep, and is easy to access. I plan to convert this sheet to a CSV file at a later time and launch some heavy statistics on it, but more on that once the data has thoroughly thrived. There’s not too much one could (or should) infer from a single sample.