Affordable & Safe Housing in Seattle, WA
In our problem statement, we have a group of athletes who are planning to live in Seattle for several weeks. They would need to find several flats, so it’s desirable that they are located nearby to make the collective work-outs easier. Additional preferences include presence of a park nearby and low criminality in that district because they are planning to be outside very often (jogging in the evenings, etc). Also, the apartments should be affordable, but the factor of low criminality is valued higher by our clients.
The target audience for this report are:
- potential buyers, who can roughly estimate which neighborhoods are more desired (and the models used for analysis should be easily adjustable),
- real estate builders and planners who can decide what kind of neighborhoods are more attractive on the market to maximize selling price of newly built flats,
- and of course, to this course’s instructors and learners who will grade my project,
- anyone who is curious how Python can be applied to easily crawl web pages; parse CSV or JSON files; create powerful visualizations of data as scatter plots, heat maps, density plots using matplotlib, seaborn and map visualizations using Folium; process data using lists, dictionaries, pandas DataFrames.
Full text of this report is available by the following link