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Timeline analysis of your social media use and fitness data

This repo is a Python script that gets your LinkedIn and Fitbit data into the same schema. This should be flexible enough to incorporate more sources going forward.

The schema is stored in a namedtuple called Event

  • source -- either Fitbit or LinkedIn
  • metric_name -- things like comments, shares, hrv, hr, etc
  • timestamp -- the timestamp when this metric occured
  • metric_value -- the double value of the metric
  • content -- the content of the comment or share for LinkedIn, NULL for Fitbit

Request your Fitbit data from https://www.fitbit.com/settings/data/export After you get your export, dump it into data/fitbit and unzip it. (this usually takes 30ish minutes)

Request your LinkedIn data from https://www.linkedin.com/psettings/member-data (this can take up to TWO DAYS!) After you get your export, unzip an dump it into data/linkedin in the root of this repo

After you have both exports in the right place,

Run pip install -r requirements.txt to install Pandas if you don't have pandas installed

update your YOUR_FITBIT_NAME to whatever it shows in your path. Mine was ZacharyWilson

Once that is updated. Run the script with python runner.py

This will create three datasets output/all_events_on_timeline.csv output/daily_aggregates.csv output/pivoted.csv

You can use the pivoted.csv to create fancy charts like this in Tableau. My data is in the repo at zachs_pivoted_data.csv this