Stats

These are some of my personal stats, collected from different sources and aggregated with my DETERRED package. They were last updated on [REDACTED].

Programming

Programming languages

WakaTime is a service that tracks hours spent on programming, which I’ve used since late 2018. It allows exporting all your data for analysis, as all services should, but it’s a proprietary service. If you want to reproduce this, you might also want to look at a compatible self-hosted implementation called Wakapi.

My numbers are somewhat skewed towards org-mode because I switch to it all the time when I’m programming, and because I haven’t configured WakaTime to account for AI usage.

Below are my top recorded languages:

And the same data, but grouped by year:

The chart below shows, for each month, the average age of the projects I worked on.

AI use

So far, my AI usage would have cost $[REDACTED] at API prices (although I have, of course, used subscription plans). Below is the breakdown by month.

And the breakdown by token use:

Emacs use

Emacs is the best thing to ever be created by an intelligent being in the whole Universe. Here’s the percentage of my screen time I spent using Emacs:

This data was collected by ActivityWatch.

Reading and listening

Music

This chart shows the number of hours I’ve spent listening to music using Google Play Music and later MPD.

Here’s that data split between albums that first appeared in my collection that year vs. those that had appeared in earlier years:

Podcasts

Here’s the approximate number of hours I’ve spent listening to podcasts in AntennaPod.

It’s not quite accurate: the number for 2022 is understated because unsubscribing from some podcasts deleted their stats; the rest of the numbers might be inflated because they include time skipped by fast-forwarding as listening time. It also doesn’t include podcasts I’ve listened to via YouTube or The Economist app. But it will do.

Here’s the same data broken down by language:

And here are my top 15 podcasts, or most of them, anyway:

Articles

I read stuff on the Internet mostly via a read-it-later workflow, currently using a solution called Readeck.

I was inspired by Tiago Forte’s article, which he has since deleted, though it remains available in the Internet Archive. So far I’ve read [REDACTED] articles.

And the same data broken down by language:

Messengers

I would prefer email, but alas.

Here’s the number of messages I sent and received per year:

And here’s the combined number of sent and received messages, stacked by platform:

Social media

Here’s my social media activity grouped by month. Darker bands mean more activity.

Movement

Public transport

Here’s my public transport use since January 2025:

Bicycle

This is the distance covered by bicycle each month. Regrettably, the data only starts this year.

University

Since January 2024 I’ve been to the uni [REDACTED] times.

Here’s this data broken down by transport type since January 2025:

Work

This is me trying not to work on weekends, with varying success. Since I started recording, I’ve had [REDACTED] free weekends out of [REDACTED], and [REDACTED]/[REDACTED] in the last 4 quarters.

This data comes from org-clock, which is a time-tracking feature built into Emacs.

Photos

Below is the number of photos I’ve taken per year. So far I’ve taken [REDACTED] photos. This comes from digiKam.