Analyzing user driving pattern data - data-analysis

Question

so I have a lot of GPXs of users driving data from a game project where object which are placed on the road and then the user collects it. I want to somehow analyze these data to find out how users tend to drive given different objects, which ones draw them the most, which ones draw least. I have not done any data analysis before, so how can I analyze these data to get this sort of information? This might sound very novice, but yeah any help is appreciated.

Answer 1

You would probably like to do this in Python if you are novice, and then you can use a library like this one (gpxpy) to explore your data.
That is a GPX parser, I believe it will provide you with the data you like to see.
In their documentation you can see that you can use it like that :
import gpxpy
import gpxpy.gpx
# Open a file
gpx_file = open('yourfile.gpx', 'r')
# Parse the file
gpx = gpxpy.parse(gpx_file)
# Iterate over the tracks
for track in gpx.tracks:
for segment in track.segments:
for pt in segment.points:
print(f'Point at ({pt.latitude},{pt.longitude}) -> {pt.elevation}')
for waypoint in gpx.waypoints:
print(f'waypoint {waypoint.name} -> ({waypoint.latitude},{waypoint.longitude})')
for route in gpx.routes:
print('Route:')
for pt in route.points:
print(f'Point at ({pt.latitude},{pt.longitude}) -> {pt.elevation}')
Once you have those points you can calculate the distances, speeds, etc. from the coordinates.