Predicting Real Estate Prices

  • id — unique identified for a house
  • dateDate — house was sold
  • pricePrice — is prediction target
  • bedroomsNumber — of Bedrooms/House
  • bathroomsNumber — of bathrooms/bedrooms
  • sqft_livingsquare — footage of the home
  • sqft_lotsquare — footage of the lot
  • floorsTotal — floors (levels) in house
  • waterfront — House which has a view to a waterfront
  • view — Has been viewed
  • condition — How good the condition is ( Overall )
  • grade — overall grade given to the housing unit, based on King County grading system
  • sqft_above — square footage of house apart from basement
  • sqft_basement — square footage of the basement
  • yr_built — Built Year
  • yr_renovated — Year when house was renovated
  • zipcode — zip
  • lat — Latitude coordinate
  • long — Longitude coordinate
  • 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

Obtain

Scrub

Explore

Question 1: Does renovation have a noticeable effect on price?

Question 2: Is there a difference in price between a house built in a given time period versus a house renovated in that same time period?

Question 3: Is there a difference in price based on geographical location in King’s County?

Heat map of the houses using latitude and longitude of the data in terms of price

Multicolinearity

Model

Interpret

Closing Remarks

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John Kundycki

John Kundycki

Data Scientist | Health Enthusiast | Learner

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