melbourne housing dataset.csv from kaggle.
this was using that older dataset (link to kaggle) with 9 features. coordinates were polled from Google’s geocoding API based on the address in the dataset. I believe the updated dataset provides coordinates too, possibly using the same method described.
showing different ranges of number of rooms per unit
‘if i’m looking for houses that are between 5 to 7 rooms, the newest ones are the light yellow ones on the northeast edge of the city.’
other details that are inherent by linking an excel datasheet to coordinates in the real world:
height of property, contour of surrounding land
flow of water through property and general direction of water flow. (flash floods, landslides possibly?)
pictures around the site (from Google Street View)
of course, different methods of transport to and from the city
weather data at a given time (historical data is paywalled, so i couldn’t access it)
soil conditions and suitability for certain forms of construction
…and some really zoomed out GIS level datasets (i’m still wondering what to do with them.)