Project-Proposal
Team Members: Benjamin Nelson, Jonathan Randolph, Lei Kang, Patricia Mayer
Project Outline:
We plan to analyze housing costs and their relations to a variety of factors, with a focus on weather data, for apartments, houses, and other housing variants.
Research Questions:
How does price (or price/area?) relate to:
- Likelihood of flooding/Cost of flood insurance?
- Average lot size?
- Crime rates?
- Proximity to amenities (Bars/restaurants)?
Data Sets to be Used:
- https://www.zillow.com/
- https://raw.githubusercontent.com/OpenDataDE/State-zip-code-GeoJSON/master/tx_texas_zip_codes_geo.min.json
- https://search.onboard-apis.com/propertyapi/v1.0.0/property
- https://opendata.arcgis.com/datasets/8d515a90e80840b3bc7a3ada352b0d15_0.geojson
- https://maps.googleapis.com/maps/api/place/nearbysearch/json
Rough Breakdown of Tasks:
- Filter datasets to be used
- Pull useful data from datasets
- Further refine questions
- Explore data
- Create figures showing relation of housing prices to each
Final-Insights
- House square footage matters to the price you'll pay; but the lot has little effect.
- Flooding has some effect on the price; but requires more research.
- The more you pay, the more likely you are to have non-violent crime happening in your area. Violent crime rates stay about the same.
- The more restaurants in an area, the more the average cost.
- And lastly, downtown Houston is expensive.