unzip(zipfile = "data/1270055001_sa3_2016_aust_shape.zip", exdir = "data/")
sa3 <- st_read(dsn = "data/", layer = "SA3_2016_AUST", stringsAsFactors = FALSE)
-# This doesn't work
-#taxstats.sa3 <- merge(x = taxstats, y = sa3, by.x = "Postcode", by.y = "POA_CODE16", all.y = TRUE)
# Create a matrix of intersecting postal codes and SA3's
plots <- function() {lapply(cities, function(x){
plot <- ggplot(dplyr::filter(sa3, data.table::`%like%`(GCC_NAME16, x) )) +
geom_sf(aes(fill = incomeperearningcapita, color = incomeperearningcapita)) +
- scale_fill_viridis(name = "") +
- scale_color_viridis(name = "") +
+ scale_fill_viridis(name = "",
+ limits = c(min(sa3$incomeperearningcapita, na.rm = TRUE),max(sa3$incomeperearningcapita, na.rm = TRUE))) +
+ scale_color_viridis(name = "",
+ limits = c(min(sa3$incomeperearningcapita, na.rm = TRUE),max(sa3$incomeperearningcapita, na.rm = TRUE))) +
coord_sf(datum = NA) + # Work around https://github.com/tidyverse/ggplot2/issues/2071 to remove gridlines
labs(title = paste0(x," \nincome distribution"),
subtitle = "2014/15, in 1000s AUD",