This repository is for sharing the code for the contribution of Lionel Hertzog and Nadja Simons to the visualization award of the GfÖ meeting in Marburg 2016.
Below is a short description of the repository.
This folder contains all the data used to make the map. Two R-scripts are provided to import the transport data (Data_ import.R) and to format the data (Data_preparation.R).
This folder contains the R code to create the static map.
This folder contains the code to run the ShinyApp, if you want to run the App locally download this folder then run shinyAppDir("path-to-folder/VizAward_shiny") from R.
The repository also contains a pdf of the bus network of Marburg and an Rproject file for the data preparation.
All code was developed and tested on both a Windows system and a Linux system. It was developed with R version 3.3.0 (2016-05-03) -- "Supposedly Educational". You might need to update your R version to run some of the functions.
The following R packages need to be installed:
library(plyr) --> data handling library(dplyr) --> more data handling, piping (%>%) library(tidyr) --> more data management
library(sp) --> handle spatial objects library(maps) --> free maps of the world library(mapdata) --> world maps library(RgoogleMaps) --> get google maps library(raster) --> handle raster data library(rgdal) --> input/output, projections of spatial data library(rgeos) --> geometry operations on spatial data
library(shiny) --> for the shiny application library(leaflet) --> creating maps with for shiny. You need to download the github version (instruction in the code) library(RCurl) --> to load data directly from github library(viridis) --> colour palette
Most code is writing with pipes, read the pipe symbol e.g. in "dataset %>% my_function() %>% plot()" as "apply the function on the dataset and provide the output of this function for the plot".