This is an experiment of implementing the Wellbeing Toronto map using R.

Diabetes data

The diabetes prevalence values are calculated by as “Percent of People With diabetes, Both sexes, Age-Adjusted”. The values are taken from the The Wellbeing Toronto Heath Dataset. The explanation on how the data were collected is here.

Since this file has multiple sheets and not formatted for machines, we copied the data sheet of 2008 to “./data/WB-Health-2008.csv” for later use.

Polygon data

First we need to download the polygon data file in the WGS84 Coordinates Reference System. The block of code below does the downloading and unzipping.

fileurl <- "http://opendata.toronto.ca/gcc/neighbourhoods_planning_areas_wgs84.zip"
download.file(fileurl, './data/neighbourhoods_planning_areas_wgs84.zip', method ='curl')
unzip(zipfile = "./data/neighbourhoods_planning_areas_wgs84.zip", exdir = "./")

The following code basically reads the shape file and diabetes data file into 2 R objects. Then we merged them into 1 file to display using Leaflet. Finally we configured the choropleth map using continuous colour gradient.

library(rgdal)
## Loading required package: sp
## rgdal: version: 1.0-4, (SVN revision 548)
##  Geospatial Data Abstraction Library extensions to R successfully loaded
##  Loaded GDAL runtime: GDAL 1.11.2, released 2015/02/10
##  Path to GDAL shared files: /Library/Frameworks/R.framework/Versions/3.2/Resources/library/rgdal/gdal
##  Loaded PROJ.4 runtime: Rel. 4.9.1, 04 March 2015, [PJ_VERSION: 491]
##  Path to PROJ.4 shared files: /Library/Frameworks/R.framework/Versions/3.2/Resources/library/rgdal/proj
##  Linking to sp version: 1.1-1
library(leaflet)
TOhood <- readOGR("./data", layer = "NEIGHBORHOODS_WGS84", verbose = FALSE)
TOhood.data <- read.csv("./data/WB-Health-2008.csv")
TOhood@data$AREA_S_CD <- as.integer(TOhood@data$AREA_S_CD)
TOhood2 <- merge(TOhood, TOhood.data, by.x = "AREA_S_CD", by.y = "Neighbourhood.Id", sort = FALSE)
pal <- colorNumeric(palette = "Blues",
  domain = TOhood2[['Diabetes.Prevalence']]
  )
TOhood_popup <- paste0("<strong>Neighbourhood: </strong>",
                       TOhood2@data$AREA_NAME,
                       "<br><strong>Diabetes Prevalence: </strong>",
                       TOhood2[['Diabetes.Prevalence']]
                       )
stamen_tiles <- "http://{s}.tile.stamen.com/toner-lite/{z}/{x}/{y}.png"
stamen_attribution <- 'Map tiles by <a href="http://stamen.com">Stamen Design</a>, under <a href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a>. Data by <a href="http://openstreetmap.org">OpenStreetMap</a>, under <a href="http://www.openstreetmap.org/copyright">ODbL</a>.'

TOhoodMap <- leaflet(data = TOhood2) %>%
  addTiles(urlTemplate = stamen_tiles,
           attribution = stamen_attribution) %>%
  setView(lng=-79.38318, lat=43.65323, zoom = 11) %>%
  addPolygons(fillColor =
                ~pal(TOhood2[['Diabetes.Prevalence']]), 
                fillOpacity = 0.7, 
                color = "#BDBDC3", 
                weight = 1, 
                popup = TOhood_popup) %>%
  addLegend("bottomright", 
            pal = pal, 
            values =~Diabetes.Prevalence,
            title = "Diabetes Prevalence",
            opacity = 1
            )

Now if you click on each neighbourhood in the map below, you will be able to see the name of the neighbourhood and diabetes prevalence in the popup window!