Data visualization is defined as a graphical representation that contains information and data. By using visual elements such as charts, graphs, and maps, data visualization techniques provide an accessible way to view and understand trends, outliers, and patterns in the data. Data visualization is how data scientists communicate their findings to stakeholders. Here I visualize data using home sales data.
Rooms: Number of rooms
Price: Price in dollars
Method: S - property sold; SP - property sold prior; PI - property passed in; PN - sold prior not disclosed; SN - sold not disclosed; NB - no bid; VB - vendor bid; W - withdrawn prior to auction; SA - sold after auction; SS - sold after auction price not disclosed. N/A - price or highest bid not available.
Type: br - bedroom(s); h - house,cottage,villa, semi,terrace; u - unit, duplex; t - townhouse; dev site - development site; o res - other residential.
SellerG: Real Estate Agent
Date: Date sold
Distance: Distance from CBD
Regionname: General Region (West, North West, North, North east …etc)
Propertycount: Number of properties that exist in the suburb.
Bedroom2 : Scraped # of Bedrooms (from different source)
Bathroom: Number of Bathrooms
Car: Number of carspots
Landsize: Land Size
BuildingArea: Building Size
CouncilArea: Governing council for the area