Only loop through the graphs twice.
[R/project-au-taxstats.git] / AU-taxstats.R
index 8bbcb263b533e828f8b023e61505cdc8f11207fa..92577c60ba327ee07320311808efefc4ddfdc686 100644 (file)
@@ -41,7 +41,6 @@ if(!file.exists("data/SA3_2016_AUST.shp"))
   unzip(zipfile = "data/1270055001_sa3_2016_aust_shape.zip", exdir = "data/")
 
 sa3 <- st_read(dsn = "data/", layer = "SA3_2016_AUST", stringsAsFactors = FALSE)
-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
 
@@ -65,8 +64,10 @@ cities = c("Perth","Melbourne","Sydney","Adelaide","Brisbane")
 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",
@@ -80,4 +81,4 @@ plots <- function() {lapply(cities, function(x){
 })
 }
 
-saveGIF(plots(),movie.name = "AUCitiesIncomeDistribution.gif", interval = 2)
+saveGIF(plots(),movie.name = "AUCitiesIncomeDistribution.gif", interval = 2, loop = 2)