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,
NULLfor 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
