There should be no necessary libraries to run the code here beyond the Anaconda distribution of Python. The code should run with no issues using Python versions 3.*.
For this project, I was interestested in using Airbnb data from 2016/2017 to better understand:
- When is there more (or less) availability in Boston and Seattle? Is there a difference between the two cities?
- When is it cheaper to stay in Boston or Seattle? Is there a difference between the two cities?
- Do neighborhoods influence prices? And the score rating?
- What features do the top rated (score rating +90) properties have in common? What is different from the other properties?
There are 4 notebooks available here to showcase work related to the above questions. Each of the notebooks is exploratory in searching through the data pertaining to the questions showcased by the notebook title. Markdown cells were used to assist in walking through the thought process for individual steps.
There are 2 .csv files with data for each city. The calendar file with the availability data and the listings file with the listing of the available attributes of the properties
The main findings of the code can be found at the post available here.
The data is in the public domain. You can find other information at the Kaggle link available here for Boston and Seattle. Feel free to use the code here as you would like!
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