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Data Analysis with Python - final assignment

House Sales in King County, USA

This Jupyter Notebook is a hands-on project performed during the data analysis course by IBM/Coursera.

Prerequisites

  • Jupyter Notebook
  • Python 3
  • Python libraries: Pandas, Numpy, Matplotlib, Sklearn

Csv

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)

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