canadamaps

General idea

The idea is to avoid “duplications”, for example instead of adding a provinces map or others, we provide functions to sum Census Divisions in all possible cases.

library(ggplot2)
library(canadamaps)

ggplot(data = census_divisions) + 
  geom_sf(aes(geometry = geometry)) +
  labs(title = "Canada's Census Divisions")

# same idea as the same plot, different aggregation
#
# ggplot(data = get_agricultural_divisions()) + 
#   geom_sf(aes(geometry = geometry)) +
#   labs(title = "Canada's Census Agricultural Regions")
# 
# ggplot(data = get_economic_regions()) + 
#   geom_sf(aes(geometry = geometry)) +
#   labs(title = "Canada's Economic Regions")
# 
# ggplot(data = federal_electoral_districts) + 
#   geom_sf(aes(geometry = geometry)) +
#   labs(title = "Canada's Federal Electoral Districts")
# 
# ggplot(data = get_provinces()) + 
#   geom_sf(aes(geometry = geometry)) +
#   labs(title = "Canada's Provinces")

Using real data

We start by loading the required packages.

library(readr)
library(dplyr)
library(sf)

Let’s say I want to replicate the map from Health Canada, which was checked on 2023-08-02 and was updated up to 2023-06-18. To do this, I need to download the CSV file from Health Canada and then combine it with the provinces map from canadamaps.

url <- "https://health-infobase.canada.ca/src/data/covidLive/vaccination-coverage-map.csv"
csv <- paste0("data_processing/", gsub(".*/", "", url))
if (!file.exists(csv)) download.file(url, csv)

vaccination <- read_csv(csv) %>% 
  filter(week_end == as.Date("2023-06-18"), pruid != 1) %>% 
  select(pruid, proptotal_atleast1dose)

vaccination <- vaccination %>% 
  left_join(get_provinces(), by = "pruid") %>% # canadamaps in action
  mutate(
    label = paste(gsub(" /.*", "", prname),
                  paste0(proptotal_atleast1dose, "%"), sep = "\n"),
  )

An initial plot can be done with the following code.

# colours obtained with Chromium's inspector
colours <- c("#efefa2", "#c2e699", "#78c679", "#31a354", "#006837")

ggplot(vaccination) +
  geom_sf(aes(fill = proptotal_atleast1dose, geometry = geometry)) +
  geom_sf_label(aes(label = label, geometry = geometry)) +
  scale_fill_gradientn(colours = colours, name = "Cumulative percent") +
  labs(title = "Cumulative percent of the population who have received at least 1 dose of a COVID-19 vaccine") +
  theme_minimal(base_size = 13)

What if we want a Lambert (conic) projection? We can change the CRS with the sf package but please read the explanation from Stats Canada.

vaccination$geometry <- st_transform(vaccination$geometry,
  crs = "+proj=lcc +lat_1=49 +lat_2=77 +lon_0=-91.52 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs")

ggplot(vaccination) +
  geom_sf(aes(fill = proptotal_atleast1dose, geometry = geometry)) +
  geom_sf_label(aes(label = label, geometry = geometry)) +
  scale_fill_gradientn(colours = colours, name = "Cumulative percent") +
  labs(title = "Cumulative percent of the population who have received at least 1 dose of a COVID-19 vaccine") +
  theme_minimal(base_size = 13)

Finally, we can use a different ggplot theme.

ggplot(vaccination) +
  geom_sf(aes(fill = proptotal_atleast1dose, geometry = geometry)) +
  geom_sf_label(aes(label = label, geometry = geometry)) +
  scale_fill_gradientn(colours = colours, name = "Cumulative percent") +
  labs(title = "Cumulative percent of the population who have received at least 1 dose of a COVID-19 vaccine") +
  theme_void() +
  theme(
    legend.position = "top",
    plot.title = element_text(hjust = 0.5)
  )

Units of aggregation

Census Division

The finest division in this package is the Census Division (CDs) which can be of the next types (reference: https://www.statcan.gc.ca/en/subjects/standard/sgc/2011/sgc-tab-d).

Language form of CD type	Abbreviation for English language publications	Title for English language publications	Abbreviation for French language publications	Title for French language publications	Abbreviation for bilingual publications	Title for bilingual publications
Bilingual	CDR	Census division	CDR	Division de recensement	CDR	Census division / Division de recensement
Bilingual	CT	County	CT	Comté	CT	County / Comté
English only	CTY	County	CTY	County	CTY	County
English only	DIS	District	DIS	District	DIS	District
English only	DM	District municipality	DM	District municipality	DM	District municipality
French only	MRC	Municipalité régionale de comté	MRC	Municipalité régionale de comté	MRC	Municipalité régionale de comté
English only	RD	Regional district	RD	Regional district	RD	Regional district
English only	REG	Region	REG	Region	REG	Region
English only	RM	Regional municipality	RM	Regional municipality	RM	Regional municipality
French only	TÉ	Territoire équivalent	TÉ	Territoire équivalent	TÉ	Territoire équivalent
Bilingual	TER	Territory	TER	Territoire	TER	Territory / Territoire
English only	UC	United counties	UC	United counties	UC	United counties

The division type is specified in the census_divisions table.

Census Agricultural Regions

Census Agricultural Regions (CARs) can be obtained as sums of CDs. Excluding some special cases for Northwestern Territories, Nunavur and Yukon that we clarified over email communication, the source to match CDs to CARs was obtained from Census of Agriculture Reference Maps and manually organized in a spreadsheet (https://github.com/pachadotdev/canadamaps/tree/main/data_xlsx).

Economic Regions

Economic Regions (ERs) can be obtained as sums of CDs. The only special case is the Halton, which belongs to two economic zones and it’s the only CD that has to be carefully separated (i.e. see https://github.com/pachadotdev/canadamaps/blob/main/data_processing/02_census_divisions_and_derivatives.R).

Federal Electoral Districts

These cannot be obtained as sums of CDs, therefore these are stored in their own table federal_electoral_districts.

pachadotdev / canadamaps