X-Git-Url: http://git.vanrenterghem.biz/R/project-au-taxstats.git/blobdiff_plain/8a23a6086193c79ff00a532f2b4d893e741e7ba9..26a2a71b8ad239147ec5bc61915ec1237832bd87:/AU-taxstats.R

diff --git a/AU-taxstats.R b/AU-taxstats.R
index 8bbcb26..1ca7b75 100644
--- a/AU-taxstats.R
+++ b/AU-taxstats.R
@@ -41,14 +41,13 @@ 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
 
 POA_SAs <- st_intersects(x=sa3, y=POA, sparse=FALSE)
 taxstats.POA$`Total.Income.or.Loss..`[is.na(taxstats.POA$`Total.Income.or.Loss..`)] <- 0
 taxstats.POA$`Total.Income.or.Loss.no.`[is.na(taxstats.POA$`Total.Income.or.Loss.no.`)] <- 0
-# Perform matrix multiplication to obtain the income metrix per SA3
+# Perform matrix multiplication to obtain the income metrics per SA3
 # Total income will be incorrect, as the POAs intersect with multiple SA3s
 sa3$TotalIncome <- as.vector(POA_SAs %*% as.matrix(taxstats.POA$`Total.Income.or.Loss..`))
 sa3$TotalIncomeEarners <- as.vector(POA_SAs %*% as.matrix(taxstats.POA$`Total.Income.or.Loss.no.`))
@@ -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)