As a frequent Airbnb guest in Vancouver BC, Seattle WA, and Portland OR, I wanted to learn more about Airbnb listings in these cities. More specifically, I wanted to know more about the price of listings and better understand guest satisfaction.

I used the most recent AirBnb data available for all three cities (February 2020) from InsideAirBnb and cleaned and analyzed it using standard Python tools.

• Data wrangling
• Analyis and modeling

In the analysis, I set out to explore answers to the following questions:

1. How do listing prices relate to location?
2. How do listing prices change over time?
3. How does overall guest satisfaction relate to location?
4. How do listing prices in neighbourhoods relate to guest satisfaction?
5. Which listing features are most closely related to guest satisfaction?

For a summary of results, see this blog post. Notebooks and code are also available on GitHub