The goal of this project is to create an ETL pipeline (Extract, Transform, Load) that takes in a list of lakes in various US states and incrementally adds data about those lakes and the nearby homes for sale and filters everything down until we have a few candidate properties that are worth looking into.

Some filters we want to have for lakes

• lake size between 50 and 1000 acres
• lake can be natural or man-made (ie reservoir)
• lake should be 1-6 hours drive from hometown

Some filters we want to have for the property

• property should be "waterfront" or "lakefront", shouldn't be down the street or require driving/parking
• property should have 3 or more bedrooms
• property should be recently updated
• property should be listed between $100k and $500k USD

1. Using the scripts directory, we start with copy/pasted value from wikipedia's list of lakes for Ohio in get_lakes.py.
2. From there, we look up geocoding information to get lat/lon pairs for each lake based on the town name in geocode.py.
3. Finally, we upload the CSV with the lat/lon pairs to a new Google My Map, for visual analysis here.

1. Take a closer look at the artificial Ohio lakes
2. Add lists of lakes from nearby Pennsylvania, New York and Michigan
3. Instead of visualizing the lakes on a map, look each lake up to get its driving distance from hometown via some API (which one?)
4. Use the Zillow API to look up 3 bedroom properties in the area of each lake
5. Filter properties based on "waterfront", recently updated, price, etc