montreal-dots.R

library(cancensus)
library(tidyverse)
library(sf)
library(tmap)
library(tmaptools)
options(cancensus.api_key = "your key goes here")

montreal <- get_census(dataset = "CA16", regions = list(CMA = "24462"), 
                       vectors = c("v_CA16_1364", "v_CA16_1367"), level = "CT", 
                       geo_format = "sf", labels = "short")
                       

english_dots <- montreal %>%
  st_transform(32618) %>%
  mutate(english = as.integer(v_CA16_1364 / 200)) %>%
  mutate(english = ifelse(is.na(english), 0, english)) %>%
  st_sample(., .$english) %>%
  st_sf()
  
url <- "path to your desired basemap tileset"

osm <- read_osm(bb(montreal), type = url)

b1 <- tm_shape(osm) + 
  tm_raster() + 
  tm_shape(english_dots) + 
  tm_dots(alpha = 0.4, col = "red") + 
  tm_layout(title = "English as first language in the Montreal area") + 
  tm_credits("1 dot = 200 people. Data source: 2016 Canadian Census via the R cancensus package")

save_tmap(b1, "img/english.jpg")

french_dots <- montreal %>%
  st_transform(32618) %>%
  mutate(french = as.integer(v_CA16_1367 / 200)) %>%
  mutate(french = ifelse(is.na(french), 0, french)) %>%
  st_sample(., .$french) %>%
  st_sf()

b2 <- tm_shape(osm) + 
  tm_raster() + 
  tm_shape(french_dots) + 
  tm_dots(alpha = 0.4, col = "#1C5BA2") + 
  tm_layout(title = "French as first language in the Montreal area") + 
  tm_credits("1 dot = 200 people. Data source: 2016 Canadian Census via the R cancensus package")

save_tmap(b2, "img/french.jpg")