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Geocoding & reverse geocoding the 2017 regular season games of the LA Chargers; I also decided to plot each game location on GoogleMaps just for added fun.
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NOTE:
1. I'm pretty certain that there is a better way to plot each location on the map.
2. I had to provide numerical variations to each game in order for them to show up 'correctly';
boolean values (my initial attempt) did not work as intended.
3. Because of home games, or games played in at same stadium, there is some plot overlapping;
I used different values in order to highlight each game played in the same location.
4. There were a few issues, notably, those that deal with getting the correct address to be returned
by Google, etc., but perhaps they are minor in nature and easily fixed.
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CONCLUSIONS:
Working with GoogleMaps in jupyter is quite fun and provides some interesting possibilities; think, bioinformatics, species plotting (my next adventure), ecosphere plotting, business locations/branches, etc. There are lots of possibilities that go well beyond this simple demonstrative example.
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SOURCE:
I got the idea of GeoMapping the games from Big Endian Data.
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