King County Housing Data Analysis - Predicting Sales Price

Purpose:

To develop a model that can predict the price of homes in Kings County based off of the different variables that are available to analyze.

Data Science Process Used:

I leveraged the OSEMN (Obtain, Scrub, Explore, Model, Interpret) process for this project. My notebook is organized into 5 parts, one for each step of this process.

The Dataset:

A modified version of the King County House Sales was used. The dataset can be found in the file "kc_house_data.csv", in this repo.

Key Questions investigated:

1. What is the impact of each variable on the price of homes in Kings County, and which should be used to best predict the price of homes?
2. What house features drive up price?
3. Which location is most desirable?
4. When is the best time to sell a house?
5. Do people prefer new or newly renovated houses to older homes?