Analyzing My 2020 Google Location History Data | by Justin Spitzer | Dec, 2020


The first thing I did was start to look at the data for “places,” which listed the address of the location where Google said I had arrived. Not surprisingly, my home address appeared at the highest frequency each month. I also plotted here the frequency of arrivals to each of the two work locations I work out of:

Dataframe showing frequency of visits for each location per month (address names redacted for privacy).

In addition to seeing where I traveled, I wanted to dig into the coordinate data provided in the Google location data to find out how far I traveled.

Google location history data provides start and end coordinates for each logged location.
Driving made up approximately 94% of the distance I traveled, followed by flying and walking. It’s important to keep in mind that the walking distance is inaccurate — there’s no way I walked 209 miles in July.

Google has a lot of data on us. If you’re like me and have your location data enabled on your phone, despite the fact that we’re not actively searching for most places we go, every one of those places is being logged, down to the method used to get there. Compiling this data across millions of active monthly users gives Google a lot of data to work with. The accuracy of ETAs and traffic delays down to the minute starts to make sense when thinking about the powerful models and thousands of terabytes of data Google processes daily.

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