Load GPS data from GPX files into Python as a pandas DataFrames. Initial parsing done using the gpxpy package. Trajectory plotting on a map available using folium or mplleaflet (optional).

pip install gpxo

import gpxo
track = gpxo.Track('ExampleTrack.gpx')

track.data is a pandas DataFrame containing time, position, elevation etc.; usual pandas methods can be used to analyze, manipulate and plot data.

Load, inspect and plot GPX data using the Track class, with the following methods and attributes.

• smooth(): smooth position and elevation data (see gpxo.smooth() below),
• plot(): plot trajectory data using a combination of shortnames (see shortnames below); also takes matplotlib.pyplot.plot() arguments/kwargs,
• closest_to(): find index of point in trajectory closest to a (lat, long) point.
• folium_map(): plot trajectory on a map, using the folium package,
• mplleaflet_map(): plot trajectory on a map, using mplleaflet.show(),

• file: pathlib.Path from which data originates
• data (pandas DataFrame): containing at least the keys 'latitude (°)', 'longitude (°)', and if available 'elevation (m)', 'time'; by default, the table will also include 'distance (km)', 'compass (°)', 'duration (s)', 'velocity (km/h)', calculated if possible during instantiation.

Outside of the Track class, the following standalone function is also available:

• compass(pt1, pt2): compass bearing (°) between pt1 (lat1, long1) and pt2 (lat2, long2),
• closest_pt(pt, trajectory): index of closest pt in trajectory (latitudes, longitudes) to specified pt (lat, long),
• smooth(x, n, window): smooth 1-d array with a moving window of size n and type window.

See Jupyter Notebook Examples.ipynb (https://github.com/ovinc/gpxo/blob/master/Examples.ipynb) for a detailed example using real GPX data.

Quick example 1: Plot distance versus time and velocity versus position for a given track:

import gpxo
track = gpxo.Track('ExampleTrack.gpx')
track.plot('td', '--k')    # matplotlib styles can be given
track.plot('dv', c='red')  # matplotlib kwargs can be passed
track.data  # pandas dataframe with all data

Quick example 2: show the path of a GPX file on a map using the folium package:

import gpxo
track = gpxo.Track('ExampleTrack.gpx')
mymap = track.folium_map(color='red', tiles='OpenTopoMap')
mymap.show_in_browser()

Quick example 3: show the path of a GPX file on a map with color-coding corresponding to elevation, using mplleaflet (see Troubleshooting section below in case of error):

import gpxo
track = gpxo.Track('ExampleTrack.gpx')
track.map(plot='scatter', c=track.elevation, cmap='plasma')

In case of the following error:

'XAxis' object has no attribute '_gridOnMajor

when using the mplleaflet_map() method, try downgrading Matplotlib to version <= 3.3.2 or install a forked version of mplleaflet (see jwass/mplleaflet#75).

Python >= 3.6

(automatically installed by pip if necessary)

• numpy
• pandas
• matplotlib
• importlib-metadata
• gpxpy (https://github.com/tkrajina/gpxpy)
• vincenty (https://github.com/maurycyp/vincenty)

Optional:

• folium
• mplleaflet (https://github.com/jwass/mplleaflet)

Olivier Vincent

(ovinc.py@gmail.com)

BSD 3-Clause (see LICENCE file)