openjourney

The openjourney package allows to query trip durations between cooordinates within Switzerland. It wraps the Open Journey Planer API provided by opentransportdata.swiss. It allows to query trip times between multiple locations in a structured manner and use them for data analysis.

Installation

You can install the the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("tlorusso/openjourney")

library(openjourney)
library(tidyverse)
#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
#> ✓ ggplot2 3.3.2     ✓ purrr   0.3.4
#> ✓ tibble  3.1.0     ✓ dplyr   1.0.5
#> ✓ tidyr   1.1.3     ✓ stringr 1.4.0
#> ✓ readr   1.4.0     ✓ forcats 0.5.0
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag()    masks stats::lag()
library(sf)
#> Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 7.0.0
library(tidygeocoder)
library(xml2)

Usage

API-Token

To be able to query the API a token is needed. A public key is available in the documentation which can be used for a limited number of queries. Private keys with higher rate limits can be created on opentransportdata.swiss.

In our example we’ll use the public key.

token1 <- paste("Bearer", "57c5dbbbf1fe4d000100001842c323fa9ff44fbba0b9b925f0c052d1", sep = " ")

Query trip durations

Lets get some coordinates for some sample locations.

# get coordinates of some locations
coords <- geo(address = c("Zürich Schwamendingerplatz, Switzerland",
                          "Zürich Stadelhofen, Switzerland",
                          "Uster Bahnhof, Switzerland",
                          "Bern Hauptbahnhof, Switzerland",
"Bahnhof Stettbach, Switzerland"),
method ='osm')

Plot trip durations

ggplot(trips, aes(duration_min,
                  paste0(origin_id, "\n - ", destination_id),
                  size=transfers))+
  geom_point()+
  theme_minimal()+
  scale_fill_viridis_c()+
  labs(y="", x="Trip duration (minutes)")+
  scale_x_continuous(limits=c(0,100))
#> Warning: Using size for a discrete variable is not advised.
#> Warning: Removed 1 rows containing missing values (geom_point).