This Jupyter Notebook is a hands-on project performed during the data analysis course by IBM/Coursera.
- Jupyter Notebook
- Python 3
- Python libraries: Pandas, Numpy, Matplotlib, Sklearn
This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. id : A notation for a house
date: Date house was sold
price: Price is prediction target
bedrooms: Number of bedrooms
bathrooms: Number of bathrooms
sqft_living: Square footage of the home
sqft_lot: Square footage of the lot
floors :Total 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 code
lat: Latitude coordinate
long: Longitude coordinate
sqft_living15 : Living room area in 2015(implies-- some renovations) This might or might not have affected the lotsize area
sqft_lot15 : LotSize area in 2015(implies-- some renovations)