Skip to content

ErikBjare/quantifiedme

Folders and files

NameName
Last commit message
Last commit date

Latest commit

e7dfcbe · Jun 25, 2024
Nov 21, 2023
Nov 8, 2023
Aug 14, 2022
May 22, 2023
Nov 8, 2023
Jun 25, 2024
Nov 21, 2023
May 10, 2019
Feb 2, 2022
Aug 14, 2022
Nov 8, 2023
Feb 29, 2020
Nov 8, 2023
May 23, 2023
Mar 23, 2023
Nov 8, 2023
Jun 25, 2024
Jun 17, 2024

Repository files navigation

QuantifiedMe

Build codecov

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.

Features

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).

Notebooks

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.

Configuration

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.

Related projects

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