https://github.com/jonocarroll/runkeepr

Extract, plot, and analyse Runkeeper(TM) data.
https://github.com/jonocarroll/runkeepr

data-analysis data-mining gis gpx rstats runkeeper

Last synced: about 1 month ago
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Extract, plot, and analyse Runkeeper(TM) data.

• Host: GitHub
• URL: https://github.com/jonocarroll/runkeepr
• Owner: jonocarroll
• Created: 2016-05-16T11:00:59.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-02-04T13:02:44.000Z (almost 3 years ago)
• Last Synced: 2024-05-01T12:41:11.507Z (7 months ago)
• Topics: data-analysis, data-mining, gis, gpx, rstats, runkeeper
• Language: R
• Size: 11.5 MB
• Stars: 9
• Watchers: 3
• Forks: 2
• Open Issues: 5
• Metadata Files:
  • Readme: README.md

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README

        
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#  runkeepR

Extract, plot, and analyse Runkeeper(TM) data.

## Installation:

Assuming the TravisCI badges above are green (_i.e._ the current build is stable) this package can be installed via

    devtools::install_github("jonocarroll/runkeepR")

    

or

    pacman::p_load_gh("jonocarroll/runkeepR")

## Usage

load the installed package

    library(runkeepR)

    

You can get a zipped export of your Runkeeper(TM) data from the [logged-in settings page on Runkeeper's website](https://runkeeper.com/exportDataForm), _e.g._ `runkeeper-data-export-12517482-2016-05-20-1550.zip`.

    



    

Save the `.zip` file to a directory (e.g. `~/runkeepR-test/`) and unzip the contents (mainly `.gpx` files and a couple of `.csv` files). Set this directory as your working directory in `R`.

    setwd("~/runkeepR-test/") ## set directory to location of .gpx files

Loading and processing the route information contained in the `.gpx` and `.csv` files into a data.frame is as simple as

    

    routes <- load_tracks(".")

    save(routes, file="saved_routes.rds") ## save the data to avoid re-processing

The data can be plotted either with `ggplot` 

    load("saved_routes.rds")

    plot_ggplot(routes, center="Adelaide, Australia", zoom=14)



or `leaflet`; this plots all paths but is clever about which ones to load depending on the current viewport, so it's faster. 

    load("saved_routes.rds")

    plot_leaflet(routes)





Summary statistics can be viewed 

    summarise_runs(routes, dashboard=FALSE)

and presented in a `shinydashboard`

    summarise_runs(routes)

summarised either monthly 



or daily



Not affiliated with Runkeeper(TM). Runkeeper(TM) logo © FitnessKeeper 2016