rsa.shapefiles

This package simplifies the process of loading and visualising spatial data for South Africa in R. Shapefiles encompass various administrative levels, such as provinces, districts, municipalities, main places, and subplaces, using Census 2011 demarcations.

The main dataset of interest subplaces data frame is embedded in the package. _id columns represent unique numeric identifiers, while _name columns provide descriptive names. _mdb columns present string identifiers corresponding to the demarcations of the Municipal Demarcation Board of South Africa for provinces, districts, and municipalities.

subplaces is structured hierarchically on the basis of _id values, with the exception of districts. Consider, for example, the subplace “Wemmershoek”:

• subplace_id: 167007001
• mainplace_id: 167007
• municipality_id: 167
• province_id: 1

Installation

This package requires a working installation of sf.

You can install the development version from this Github repository via the remotes package in R.

# install.packages("remotes")
# install.packages("sf")
remotes::install_github("WihanZA/rsa.shapefiles")
library(rsa.shapefiles)
library(sf)

Examples

Loading and filtering data

rsa.shapefiles::subplaces %>%
  filter(grepl("Stellenbosch", municipality_name)) %>%
  distinct(
    mainplace_name,
    subplace_name
  ) %>%
  head()
## # A tibble: 6 × 2
##   mainplace_name subplace_name  
##   <chr>          <chr>          
## 1 Franschhoek    Wemmershoek    
## 2 Tennantville   Tennantville SP
## 3 Klapmuts       Bennetsville   
## 4 Klapmuts       Klapmuts SP    
## 5 Klapmuts       Weltevrede Park
## 6 Klapmuts       Mandela City

Plotting data

library(ggplot2)

ggplot() +
  theme_void() +
  geom_sf(data = rsa.shapefiles::subplaces, color = "grey50")

Aggregating data with st_union

# From subplaces to provinces
provinces <- rsa.shapefiles::subplaces %>%
  group_by(province_id) %>%
  summarise(
    geometry = st_union(geometry),
    .groups = "drop"
  )

But st_union may take a long time to run, so you can use the pre-aggregated provinces data frame instead, as in the example below.

ggplot() +
  theme_void() +
  # use subplace fill
  geom_sf(
    data = rsa.shapefiles::subplaces,
    aes(fill = stringr::str_sub(subplace_id, 6, 9)),
    color = NA,
    show.legend = FALSE
  ) +
  # use province borders
  geom_sf(
    data = rsa.shapefiles::provinces,
    color = "white",
    fill = NA,
    linewidth = 1
  ) +
  scale_fill_viridis_d(option = "magma", begin = 0.15)

Acknowledgements

• The definitions and demarcations used in Census 2011 are detailed in the corresponding metadata, published by Statistics South Africa (2012).

• The wiki by konektaz offers a useful summary of the hierarchical structure of spatial layers: South Africa Census 2011 spatial metadata

• The original shapefiles were sourced from the OpenUp Data Portal at this link: Census 2011 Boundaries Subplace Layer