The key attraction of this map is ability to filter information according to number of bedrooms (1,2,3, any), type of property (house or unit) and according to some predefined scenarios like: "long term growth", "incoming cash flow", "balanced" or "custom strategy". The last option activates two additional filters allowing users to specify desired capital growth over 5 years and rental yields (since these filters are linked care needs to be taken in interpreting the results!).
The map allows choosing between two thematic layers: "5 year growth rate" or "rental yields" (information is rendered according to applied filters). There is a legend with a key to different colours which is updated automatically as filters change. Individual polygons respond to mouse-over events - activating a display with summary statistics for the suburb as well as labelling the suburb with full name and postcode number. Click on the suburb polygon updates information in the table under the map.
Response from the server and drawing the polygons on the map can be quite slow at times (indicating a struggle of CartoDB and/ or Google infrastructure this application is built on) and there is no time reference for published information but overall, it is a very informative and well executed implementation.
Realestate.com.au is using RP Data information and similarly to APM, this source also indicates that median unit price in Darling Point, NSW has fallen in the last 5 years – however only by 10%, which is half of APM’s rate but still a negative result. All this despite city wide median price for units rising by more than 12% over the last year. That would imply that median price in Darling Point must have had a huge drop from 2010 peak if it is still 10-20% below 2008 price…
I will have to dig deeper into this issue since this case highlights serious limitation of using median prices to gauge movement in property price at a local level.
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