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Same dataset as "House Sales in King County, USA", but with treated content and with a split version (train-test) allowing direct use in machine learning models.
We have 14 columns in the dataset, as it follows:
- date: Date of the home sale
- price: Price of each home sold
- bedrooms: Number of bedrooms
- bathrooms: Number of bathrooms
- living_in_m2: Square meters of the apartments interior living space
- nice_view: A flag that indicates the view's quality of a property
- perfect_condition: A flag that indicates the maximum index of the apartment condition
- grade: An index from 1 to 5, where 1 falls short of quality level and 5 have a high quality level of construction and design
- has_basement: A flag indicating whether or not a property has a basement
- renovated: A flag if the property was renovated
- has_lavatory: Check for the presence of these incomplete/secondary bathrooms (bathtub, sink, toilet)
- single_floor: A flag indicating whether the property had only one floor
- month: The month of the home sale
- quartile_zone: A quartile distribution index of the most expensive zip codes, where 1 means less expansive and 4 most expansive.