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Dataset

  • format: .csv
  • name: house_price.csv

Independent Variables

  • id - Unique ID for each home sold
  • date - Date of the home sale
  • bedrooms - Number of bedrooms
  • bathrooms - Number of bathrooms, where .5 accounts for a room with a toilet but no shower
  • sqft_living - Square footage of the apartments interior living space
  • sqft_lot - Square footage of the land space
  • floors - Number of floors
  • waterfront - A variable for whether the apartment was overlooking the waterfront or not
  • view - An index from 0 to 4 of how good the view of the property was
  • condition - An index from 1 to 5 on the condition of the apartment,
  • grade - An index from 1 to 13, where 1-3 falls short of building construction and design, 7 has an average level of construction and design, and 11-13 have a high quality level of construction and design.
  • sqft_above - The square footage of the interior housing space that is above ground level
  • sqft_basement - The square footage of the interior housing space that is below ground level yr_built - The year the house was initially built
  • yr_renovated - The year of the house’s last renovation
  • zipcode - What zipcode area the house is in
  • sqft_living15 - The square footage of interior housing living space for the nearest 15 neighbors
  • sqft_lot15 - The square footage of the land lots of the nearest 15 neighbors

Dependent Variables

  • price - Price of each home sold

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This .ipynb is our final project given by professor.

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