This is a quick weekend try of the house price prediction competition on kaggle

• See https://www.kaggle.com/harlfoxem/housesalesprediction for project
• See https://www.kaggle.com/harlfoxem/housesalesprediction/data for the data file

I have used a whole load of libraries to get this repo going, plus the SQL Alchemy ORM to create a DB table to query and a google maps api heatmap animation

mkdir house_price_prediction
git clone {get git address from above}
virtualenv house_price_prediction

cd house_price_prediction
source bin/activate
pip install -r requirements.txt

In the first cell, after the imports you will see some creds that need filling.

1. db_name - The db name of a postgres db that you have read write access to
2. db_host The host of the postgres db
3. db_username The username with read write access to the db
4. db_password The password for the above user
5. gmaps.configure(api_key="") This is a google maps API key (See https://developers.google.com/maps/documentation/javascript/get-api-key)

jupyter nbextension enable --py gmaps
jupyter notebook

and you are good to go!!