Main script for Dutch quality-of-life-o-meter Shiny app

main.R

# Set working directory to folder containing the current running script
setwd(dirname(rstudioapi::getActiveDocumentContext()$path))

# Clear working space
rm(list=ls())

# Check whether required packages are availale and if not, install them
if(!("readxl" %in% rownames(installed.packages()))) {
  install.packages("readxl")}
if(!("raster" %in% rownames(installed.packages()))) {
  install.packages("raster")}
if(!("rgdal" %in% rownames(installed.packages()))) {
  install.packages("rgdal")}
if(!("sp" %in% rownames(installed.packages()))) {
  install.packages("sp")}
if(!("sf" %in% rownames(installed.packages()))) {
  install.packages("sf")}
if(!("leaflet" %in% rownames(installed.packages()))) {
  install.packages("leaflet")}
library("readxl")
library("raster")
library("rgdal")
library("sp")
library("sf")
library("leaflet")

# Check if data folder exists, and if not create folder
if (dir.exists("data") == FALSE) 
  {dir.create("data")}

# Download, unzip, delete zip and load the Municipalities borders 2016
download.file(url = 'https://data.overheid.nl/OpenDataSets/LBM2016/Gemeente2016.zip', destfile = 'Gemeente2016shp.zip', method = 'auto')
unzip('Gemeente2016shp.zip', exdir = "./data")
unlink('Gemeente2016shp.zip')

# Download, unzip, delete zip and load the Gemeente data 2016
download.file(url = 'https://data.overheid.nl/OpenDataSets/LBM2016/Gemeente.zip', destfile = 'Gemeente2016XLS.zip', method = 'auto')
unzip('Gemeente2016XLS.zip', exdir = "./data")
unlink('Gemeente2016XLS.zip')

# Read first excelsheet of excel file
GemeenteStand121416 <- read_excel("./data/Gemeente/dimensiescore_gemeente (stand).xlsx", 1)

# Load shape file of municipalities boundaries
Mun_boundaries <- readOGR(dsn = "./data/Gemeente2016/", layer = "gem_2016")

# Select municipalities scores of year 2016
GemeenteStand16 <- GemeenteStand121416[which(GemeenteStand121416$JAAR == "2016"), ]

# Create data frame
GemeenteStand2016df <- data.frame(GemeenteStand16)

# Change first column of GremeenteStand2016df 'GBD' into 'GM_CODE' in order to merge with shapefile
colnames(GemeenteStand2016df)[1] <- "GM_CODE"

# Before merging, check if number of rows corresponds, if TRUE, proceed
if (nrow(Mun_boundaries) != nrow(GemeenteStand2016df)){
  print ("Number of rows unequal, merge failed")
  }  else {
    # Merge shapefile with GemeenteStand2016 based on common variable 'GM_CODE'
      MunScores2016_long <- merge(Mun_boundaries, GemeenteStand2016df, by='GM_CODE');
    # Select only required columns
      MunScores2016 <- subset(MunScores2016_long, select= c(GM_CODE, GM_NAAM, AANT_INW, RLBRMTR : RLBFYS))
    # Rename columns 
      colnames(MunScores2016@data) <- c("Municipality_Code", "Municipality_Name", "Population",
                                  "Total_Score_2016", "Housing_Score_2016",
                                  "Population_Score_2016", "Provisions_Score_2016",
                                  "Safety_Score_2016", "PhysicalEnvironment_Score_2016")
    # Write final MunScores2016 to file
      write.csv(MunScores2016, file = "./data/MunScores2016.csv")
    # Save MunScores2016 as shapefile again
      shapefile(MunScores2016, "./data/MunScores2016.shp", overwrite = TRUE)
      }


#Transform shapefile to WGS84
MunScores2016 <- spTransform(MunScores2016, CRS("+proj=longlat +datum=WGS84 +no_defs"))
shapefile(MunScores2016, "./data/MunScores2016wgs84.shp", overwrite = TRUE)



######################### Visualization

#Create colour palette for map colours
pal <- colorNumeric(
  palette = "Greens",
  domain = MunScores2016$Total_Score_2016,
  n = 6)



# Format popup data for leaflet map.
popup_dat <- paste0("<strong>Municipality:</strong>", 
                    MunScores2016$Municipality_Name, 
                    "<br><strong>Quality-of-life-o-meter says: </strong>", 
                    MunScores2016$Total_Score_2016)