suleenwong / Housing_Data_EDA_Project

EDA and predicting house prices using Regression

EDA Project: King County Housing Data

^{Lake view with a sunset in Bellevue, King County. Source: unsplash.com}

Introduction

The goal of this project is to present to a fictitious stakeholder, our recommendations based on Exploratory Data Analysis (EDA) of the King County Housing Dataset.

Our stakeholder for this project is Mr. Zachary Brooks, with the following requirements:

Seller. Invests in historical houses, best neighborhoods, high profits, best timing within a year, should renovate?

Setup

This repository contains a requirements.txt file with a list of all the packages and dependencies you will need.

To install the environment you can use the following commands:

pyenv local 3.9.8
python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt

Before you can start with plotly in Jupyter Lab you have to install node.js (if you haven't done it before):

brew update
brew install node

About this repo

In this repository you will find:

• EDA_Project_Notebook.ipynb : Jupyter notebook with Exploratory Data Analysis (EDA), python code, visualizations, documentation

• EDA_Project_Slides.pdf : Presentation of the results of the EDA

• column_names.md : Descriptions of the columns