Python For Self-Trackers: How To Become A Data-Driven You
summary
Argues personal data can change habits and gives concrete tools and results: Python code on GitHub pulls Fitbit, Kindle clippings, YouTube history and RescueTime into a quantified self ledger and a unified timestamp for analysis. Reports tracking outcomes: 2,179 hours on the computer, 4.2 million steps in a year, 298 hours of podcasts, 2.4 days spent on YouTube in one month. Builds Kindle parser, podcast recorder, photo CV app and a blood biomarker DB, uses HRV daily to monitor stress and runs weekly 30‑minute reviews.
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chapters (17)
- 0:00Start
- 1:50Personal Example
- 5:40How To Measure a Life
- 6:24The Quantified Self
- 7:25Examples of Self Tracking
- 11:23Hrv Heart Rate Variability
- 12:03Evernote
- 12:44Why Do People Self Track
- 13:29The Benefits of Self Tracking
- 14:55Continuous Blood Glucose Monitor
- 18:29Why Python
- 18:58The Quantified Self Ledger
- 22:57Data Processing
- 26:05How To Become a Data-Driven You
- 29:05Deep Work
- 32:22Sleep
- 37:38Weekly Review
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