In longwei66/mountainbikeR: A package for mountainbikers to access and visualise ride data through strava API

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(mountainbikeR)
library(kableExtra)

the mountainbikeR package

Here we will write few words about the mountainbikeR package.

Initialization, create a mountainbikeR object.

my_mbr <- mountainbiker_initializer$new(
     my_app_name = Sys.getenv("STRAVA_APP_NAME")
     , my_client_id = Sys.getenv("STRAVA_CLIENT_ID")
     , my_client_secret = Sys.getenv("STRAVA_CLIENT_SECRET")
     , my_app_scope = "read,read_all,activity:read_all"
     , cache = TRUE

)

We can now check few informations about our connection.

my_mbr$token$credentials$token_type
my_mbr$token$credentials$expires_at
substr(my_mbr$token$credentials$access_token,1,4)
my_mbr$token$credentials$athlete$sex

Getting some activities

Using the get_activities method of the object we can get a list of activities.

# List activities
some_activities_1 <- my_mbr$get_activities(
  activities_per_page = 200
  , page_number = 1
  #, after_date = "2018-01-01"
    )
some_activities_2 <- my_mbr$get_activities(
  activities_per_page = 200
  , page_number = 2
  #, after_date = "2018-01-01"
    )

some_activities <-rbind(
  some_activities_1
  , some_activities_2
  )

# Fields available
names(some_activities)

# Display some of the data
head(some_activities$moving_time)
head(some_activities$type)

library(ggplot2)
g <- ggplot(data = some_activities[ type %in% c("Ride", "Run")])
g <- g + geom_point(
  mapping = aes(
    col = moving_time
    , y = total_elevation_gain
    , x = average_heartrate
    , shape = commute
    , size = distance
    )
  , alpha = 0.7
  )
g <- g + scale_color_gradient(low = "green", high = "red", na.value = "grey")
g <- g + facet_grid(facets = . ~ type , scales = "free_x")
g

longwei66/mountainbikeR documentation built on April 16, 2020, 6:23 p.m.