I am trying to use the Australian Bureau of Statistics shapefile for Remoteness 2016 - downloading the ESRI shapefile.
I want to combine all of the polygons that are no Major Cities of Australia.
library(rgdal)
library(dplyr)
RA_2016 <- readOGR(".", layer = "RA_2016_AUST")
###to simplify only using NSW
RA_2016 <- RA_2016[RA_2016$STE_CODE16 == 1, ]
The data frame has 5 columns. I don't need any of this data once I have created a variable for whether it is a Major City or not.
MajorCity <- data.frame(10:14, c("Major City", "Regional", "Regional", "Regional", "Regional"))
names(MajorCity) <- c("RA_CODE16", "Bigsmoke")
RA_2016@data <- left_join(RA_2016@data, MajorCity)
What I want to do now is to merge the polygons that have MajorCity == "Regional". I do not need any of the original data from RA_2016. But I want it to remain a SpatialPolygonsDataFrame with the column "Bigsmoke".
In the next part of the code I am going to combine it with the Australian Bureau of Statistics' LGA data (basically so I can split LGAs into regional parts and major city parts - where they are split). So I think I need to keep that minimal amount of data.
Is there a good way to do this? Is there another post I have failed to find that will show me the way?
Here is how I would do that:
library(raster)
RA_2016 <- shapefile("RA_2016_AUST.shp")
RA_2016 <- RA_2016[RA_2016$STE_CODE16 == 1, ]
MajorCity <- data.frame(RA_CODE16=10:14, Bigsmoke=c("Major City", "Regional", "Regional", "Regional", "Regional"))
m <- merge(RA_2016, MajorCity)
x <- aggregate(m, "Bigsmoke")
x
#class : SpatialPolygonsDataFrame
#features : 2
#extent : 140.9993, 159.1092, -37.50508, -28.15702 (xmin, xmax, ymin, ymax)
#crs : +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
#variables : 1
#names : Bigsmoke
#min values : Major City
#max values : Regional
Avoid writing to slots "@", like you do here: left_join(RA_2016@data, MajorCity) That could change the order and the number of records such that the attributes ould no longer match the geometries