House Sales in King County, USA Project on Data Analysis with Python course on Coursera provided by IBM.
Contents: About the Dataset Module 1: Importing Data Module 2: Data Wrangling Module 3: Exploratory Data Analysis Module 4: Model Development Module 5: Model Evaluation and Refinement
Instructions: In this assignment, as a Data Analyst working at a Real Estate Investment Trust. The Trust would like to start investing in Residential real estate. You are tasked with determining the market price of a house given a set of features. You will analyze and predict housing prices using attributes or features such as square footage, number of bedrooms, number of floors, and so on.
About the Dataset: 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)