Postal codes in two Canadian regions

pkgs <- c("tidyverse", "cansim", "cancensus", 
          "sf", "tmap",  "readxl", "writexl")

devtools::update_packages(pkgs, dep = TRUE) # update install 

pkgs2 <- c(pkgs, "foreign", "here") # included in Base R
inst = lapply(pkgs2, library, character.only = TRUE) # load them

options(cansim.cache_path = here(".data-raw"))

options(cancensus.api_key='YOUR CANADA CENSUS API COMES HERE')

options(cancensus.cache_path = here(".data-raw"))

References

• making Maps for Canada’s Provisions and Census Divisions in R

• 2016 Census - Boundary files

• Canada Map

# 01. create a list of CD/CSD  ----
# list_cansim_tables(refresh=TRUE) # run once in a while; this may take a minute.
list_full <- list_census_vectors(dataset = 'CA16')

region_toronto <- list_census_regions(dataset = "CA16") %>% 
  filter(region %in% c("3521", "3519", "3520", "3518")) %>% 
  as_census_region_list()

region_vancouver <- list_census_regions(dataset = "CA16") %>% 
  filter(region %in% c("5915022", "5915015", "5915025", "5915055", "5915046", "5915051", 
                       "5915029", "5915034", "5915043", "5915036", "5915038", "5915004", 
                       "5915011", "5915802")) %>% # plus V6T V6S
  as_census_region_list()

# 02. import shapefile into R as sf ---- 
lcd  <- st_read(".data-raw/lcd_000b16a_e.shp") # Census divisions
lcsd <- st_read(".data-raw/lcsd000b16a_e.shp") # Census subdivisions
lfsa <- st_read(".data-raw/lfsa000b16a_e.shp") # Forward Sortation Areas

# 03. create a list of zipcodes ----
lcd_toronto    <- lcd %>% filter(CDUID %in% region_toronto[[1]]) 
lcsd_vancouver <- lcsd %>% filter(CSDUID %in% region_vancouver[[1]]) 
lfas_pt <- lfsa %>% st_centroid(of_largest_polygon = TRUE) 

lfas_toronto <- lfas_pt[lcd_toronto, ] 
lfas_vancouver <- lfas_pt[lcsd_vancouver, ]  

tmap_mode("view")

Vancouver

# 04. draw maps ---- 
lfsa %>% 
  filter(CFSAUID %in% lfas_vancouver$CFSAUID) %>% 
  tm_shape() + 
  tm_borders(col = "white", lwd = 1) + 
  tm_fill(col= "blue", alpha = 0.3) + 
  tm_text("CFSAUID", size = 0.8) +
  tm_shape(lcsd_vancouver) + 
  tm_borders(col = "white", lwd = 1) + 
  tm_fill(col= "red", alpha = 0.3) + 
  tm_text("CSDNAME", size = 1, col = "black")

Toronto

lfsa %>% 
  filter(CFSAUID %in% lfas_toronto$CFSAUID) %>% 
  tm_shape() + 
  tm_borders(col = "white", lwd = 1) + 
  tm_fill(col= "blue", alpha = 0.3) + 
  tm_text("CFSAUID", size = 0.8) + 
  tm_shape(lcd_toronto) + 
  tm_borders(col = "red") + 
  tm_fill(col= "red", alpha = 0.3) + 
  tm_text("CDNAME", size = 1, col = "black")

# 05. export as an .xlsx ---- 
as_tibble(lfas_toronto) %>% 
  rbind(as_tibble(lfas_vancouver)) %>%
  mutate(metro = ifelse(PRNAME == "Ontario", "Toronto", "Vancouver")) %>% 
  select(metro, CFSA = CFSAUID) %>% 
  write_xlsx(".data-final/cfsa_Canada.xlsx")