Repository files navigation

Create artistic visualisations with your exercise data (Python version).

This is a port of theR strava package toPython.

Install via pip:

python3 -m pip install stravavis

For development:

git clone https://github.com/marcusvolz/strava_pycd strava_pypip install -e.

Then run from the terminal:

stravavis --help

A plot of activities as small multiples. The concept behind this plot was originallyinspired bySisu.

A map of activities viewed in plan.

A plot of activity elevation profiles as small multiples.

Elevation profiles superimposed.

Calendar heatmap showing daily activity distance, using thecalmap package. Requires "activities.csv" from thebulk Strava export.

Activities shown as horizontal lines by time of day and day of year, facetted by year.Requires "activities.csv" from the bulk Strava export.

The process for downloading data is described on the Strava website here:[https://support.strava.com/hc/en-us/articles/216918437-Exporting-your-Data-and-Bulk-Export#Bulk],but in essence, do the following:

1. Log in toStrava
2. Select "Settings" from the main drop-downmenu at top right of the screen
3. Select "My Account" from the navigation menu to theleft of the screen.
4. Under the"Download or Delete Your Account"heading, click the "Get Started" button.
5. Under the "Download Request", heading, click the "Request Your Archive" button.Don't click anything else on that page, i.e. particularly not the "Request AccountDeletion" button.
6. Wait for an email to be sent
7. Click the link in email to download zipped folder containing activities
8. Unzip files

The main function for importing and processing activity files expects a path to adirectory of unzipped GPX and / or FIT files. If required, thefit2gpx package provides useful tools forpre-processing bulk files exported from Strava, e.g. unzipping activity files (see UseCase 3: Strava Bulk Export Tools).

df=process_data("<path to folder with GPX and / or FIT files>")

Some plots use the "activities.csv" file from the Strava bulk export zip. For thoseplots, create an "activities" dataframe using the following function:

activities=process_activities("<path to activities.csv file>")

plot_facets(df,output_file='plot.png')

plot_map(df,lon_min=None,lon_max=None,lat_min=None,lat_max=None,alpha=0.3,linewidth=0.3,output_file="map.png")

plot_elevations(df,output_file='elevations.png')

plot_landscape(df,output_file='landscape.png')

plot_calendar(activities,year_min=2015,year_max=2017,max_dist=50,fig_height=9,fig_width=15,output_file="calendar.png")

plot_dumbbell(activities,year_min=2012,year_max=2015,local_timezone='Australia/Melbourne',fig_height=34,fig_width=34,output_file="dumbbell.png")