Me in 2014/2015.

2015 was a defining year for me…

• Step tracking with Fitbit
• Time Tracking with RescueTime
• Getting Things Done by David Allen

Two Years Later in 2017

My personal example of improved health and Self

Quantified Self

• (def.) Measuring or documenting something about your self to gain meaning or make improvements.
• Related: Self-tracking, Biohacking, Data-driven life…

Why Track a Life?: Benefits of Self-Tracking

• Improved Health.
• Better Time Management
• Augment your memory.
• Save and better invest your money
• Achieve goals. Support habits. Manage projects
• Understand your mood, energy level and stress.
• Curiosity? Learn stuff about yourself.
• Personal Data is the Future.

Source: https://github.com/markwk/qs_mind_map

Popular Forms of Tracking

• Wearables (Apple Watch, Fitbit, Oura): steps, sleep, heart Rate (one in five Americans own a heart rate sensor today)
• Mood Tracking Apps, like MoodNotes
• Time Tracking (inc computer usage with RescueTime)
• Calendar, Projects and Tasks
• Strava, RunKeeper and many other sport apps
• Media Consumption: TV, music, articles, books…
• Weight
• Others: Money, Blood, DNS, Microbiome…

Tools for Self-tracking, QS, and Lifelogging

github.com/markwk/awesome-quantified-self

Opportunities

In the tracking an data space

1. Enabling and tracking new data points => Accessibility, new sensors, cheaper testing, new tracking apps, etc.
2. Deriving insight and meaning from existing data => More data, data accessibility, better data science and machine learning

My Contributions and Work

ENABLING AND TRACKING NEW DATA POINTS

• PodcastTracker.com
• PhotoStats.io
• BioMarkerTracker.com

DERIVING INSIGHT AND MEANING FROM EXISTING DATA

• Quantified Self (QS) Ledger

Writings: www.markwk.com, datadrivenyou.com

Data-Driven Life Tip #1:

Where to start with tracking a life?

Start with a Question or a Goal

TRACK IT!

github.com/markwk/qs_ledger

Built with Python 3 and Jupyter Notebooks

Current Integrations (1/4):

• Apple Health: fitness and health tracking and data analysis from iPhone or Apple Watch.
• AutoSleep: iOS sleep tracking data analysis of sleep per night and rolling averages.
• Fitbit: fitness and health tracking and analysis of Steps, Sleep, and Heart Rate from a Fitbit wearable.
• GoodReads: book reading tracking and data analysis for GoodReads.
• Google Calendar: past events, meetings and times for Google Calendar.

Current Integrations (2/4):

• Google Sheets: get data from any Google Sheet which can be useful for pulling data from IFTTT integrations that add data.
• Habitica: habit and task tracking with Habitica’s gamified approach to task management.
• Instapaper: articles read and highlighted passages from Instapaper.
• Kindle Highlights: Parser and Highlight Extract from Kindle clippings, along with a sample data analysis and tool to export highlights to separate markdown files.

Current Integrations (3/4):

• Last.fm: music tracking and analysis of music listening history from Last.fm.
• Oura: oura ring activity, sleep and wellness data.
• RescueTime: track computer usage and analysis of computer activities and time with RescueTime.
• Pocket: articles read and read count from Pocket.
• Strava: activities downloader (runs, cycling, swimming, etc.) and analysis from Strava.

Current Integrations (4/4):

• Todoist: task tracking and analysis of todo’s and tasks completed history from Todoist app.
• Toggl: time tracking and analysis of manual timelog entries from Toggl.
• WordCounter: (Mac Only) extract wordcounter app history and visualize recent periods of word counts.

Installation

• Use local Python 3 setup OR install Anaconda Distribution.
• pip or conda install Pandas, NumPy, Matplotlib and Seaborn
• For each project refer to its readme or notebook documentation for any specific dependencies.

Code Organization

Each project has:

1. NAME_downloader - notebook works with service API or raw data to get and process your data.
2. NAME_data_analysis - notebook slices, dices and visualizes your data into different charts on different time dimensions.

Basic Usage:

• Choose a tracking service
• Setup integration (with developer keys when necessary)
• Download and process your data
• Configure and run data analysis and visualization

Deeper Dive into Code and Usage

SEE: github.com/markwk/python4selftrackers

My Year in Numbers:

• 3,878,369 steps taken and logged.
• 26 blog posts published on www.markwk.com.
• 1559.72km kilometers (969.16 miles) run
• 94 days (of time) on computer according to RescueTime
• 84 days (of time) on projects according to manual time tracking
• 2212 completed tasks in Todoist across more than a dozen projects.

A Year in Media

• 18,657 book pages read accross 60 books, according to GoodReads
• 1785 articles reading via Pocket and Instapaper
• 16,855 songs listened to and “scrobbled” in 2018 using Last.fm.
• My top genres were Synthwave, Electronic and Synthpop. My top track was Cold summer by Le Matos. And my “favorite” artist was Le Cassette.

2,991 photos taken (Tracked via PhotoStats.io)

Data-Driven Life Tip #2:

Engage with your data.

What should I track?

Four Essential Areas for Everyone to Track

• Health
• Time
• Goals, Projects and Tasks
• Money

How to Track?

A COUPLE RECOMMENDATIONS

• Health:
  • Blood Tests
  • Sleep
  • (and maybe Heart Rate Variability)
• Time: RescueTime
• Money: Mint.com or Personal Capital
• Goals, Projects and Tasks: Todoist

My Steps Towards Data-Driven Self-Improvement

• Set a Goal
• Track It
• Research the area.
• Make Lifestyle Changes
• And track those too, i.e. track your commitment and follow-through
• Check-in, Evaluate and Engage with your data
• Repeat

Online References

• Original Post: http://www.markwk.com/2019/01/year-in-data.html
• QS Ledger Code: github.com/markwk/qs_ledger
• QS Mind Map github.com/markwk/qs_mind_map
• QS Tools: github.com/markwk/awesome-quantified-self

Published References

Find me online at www.markwk.com!