Loading and plotting of various Quantified Self data sources.

You can see an example notebook with fake data built in CI down below.

Note: This code is only used by me, as far as I know, but I encourage you to try it out anyway, and report or send PRs for any issues you encounter. I will try to keep it tidy and somewhat usable.

The code in this repository generally loads data from some source into a Pandas dataframe, and provides tools to process, aggregate, and plot the data.

This makes it a useful toolkit for exploratory data analysis with Jupyter notebooks, for example.

Types of data supported:

• Time tracking data (from ActivityWatch, Toggl, SmarterTime)
• Sleep data (from Fitbit, Oura, Whoop)
• Heartrate data (from Fitbit, Oura, Whoop)
• Location data (from Google Location History)
  • Includes basic plotting of time spent in a certain location.
  • Includes function for computing the colocation time of two location histories (time spent together).
• Habit data (from HabitBull)
  • Includes a calendar plot.
  • Easy to adapt to any other habit app that supports CSV export
• Drug consumption (from QSlang)

Can load data from:

• ActivityWatch
• Fitbit
• Whoop
• Oura
• EEG devices (WIP)
• ...and more (see src/quantifiedme/load/)

It also contains a bunch of useful tools for aggregating or otherwise deriving data from the sources, including helper tools for combining multiple sources for the same type of data (see src/quantifiedme/derived).

There is currently only one example notebook.

• Dashboard - Preview at: https://erik.bjareholt.com/quantifiedme/Dashboard.html
  • Uses ActivityWatch and SmarterTime data from multiple devices (desktop, laptop, phone) to create a unified overview of time spent.
  • Used by me as a sort of personal-productivity dashboard.
  • Plots things like:
    • hours worked per day (and on what)
    • which categories are consuming most of my time on a 30-day and 365-day basis
    • how much I make in "fictional salary" over time (by assigning an hourly wage to each category)

I also have a collection of private notebooks for exploratory analysis, which I hope to share later.

The configuration is used to specify where data files are located, as well as a few settings.

An example configuration file is provided in config.example.toml.

• HPI ("Human Programming Interface") by @karlicoss