As mentioned in my previous post about Victoria I have been interested in exploring the distribution of Electronic Gaming Machines (aka poker machines, slot machines or pokies, depending on where you are from) in New South Wales.
I recently obtained pokies venue data from the NSW Government. The data is used in this post under a Creative Commons Attributions licence (‘© State of New South Wales (Department of Justice) . For current information go to www.justice.nsw.gov.au.’). My dataset was dated 5 December 2016, so the data may have changed since then. Another important thing to note is that The Star, Sydney casino is not included in this dataset.
This dataset gives the names, addresses and number of machines for venues with pokies in NSW. Using the Google Geocoding API, I was able to create a coordinate for each venue. This worked reasonably well but not perfectly. I then also had to do a lot of manual checking and correcting. So I can’t guarantee all locations are 100% accurate, but it should be pretty good.
Now that I had this data organised I had two questions. Is the distribution interesting to look at? And, what is the best/most interesting way to display the distribution?
Sydney is Australia’s largest city and has a lot of pokies. The relative concentration of venues makes it easier to display, and the underlying cultural geography of the city makes for interesting comparisons. So I decided to limit my first map to the Sydney area.
Plotting the data on a 2D map provided a decent impression of WHERE pokie venues were concentrated, but it was difficult to convey the NUMBER of pokies in these venues.
I decided that this would be an excellent opportunity to try out some 3D mapping options like those I have seen from Alasdair Rae and Anita Graser. Like these posts I have used Minoru Akagi’s very cool threejs plugin for QGIS.
In all of the maps below, each column represents one venue. There is a link to the interactive versions below the gifs.
On desktop you should be able to left click and drag to rotate, right click and drag to pan and scroll to zoom. On mobile you should be able to drag to rotate, pinch to zoom and three finger drag to pan (results might vary based on platform and device etc.)
This first map is simply the data presented on a fairly plain basemap.
This second version displays median family weekly income data for Sydney suburbs, using ABS 2011 Census State Suburbs dataset. The income data is broken up into three categories composed of equal numbers of suburbs. This was based on suburbs in and adjacent to the mapped area. This division is fairly arbitrary, however I was just looking to give a way to give some broad socioeconomic context and I feel it achieves this.
I plan on doing a few more things with this data, but didn’t want this post to get too long in the tooth. So watch this space.