FIU Python The AirBnB Platform & Book Accommodations Project

Description

How to begin:
Decide on the dataset you will be using and identify some potential questions of
interest ahead of time.
Read/Import the dataset into your programming environment.
Carry out basic exploration of the dataset so you can thoroughly understand what the
dataset represents, and how it is structured, including any relevant details.
Carry out the analysis of the question(s) identified, paying attention to the process
that you followed to answer these questions for your report
Ideas of what could be done next. View yourself as an analyst in an organization.Considering the problem you tried to solve, where would you suggest the organization moves from here? Are there other related questions that could help expand your answers? Are there other data sources that could be combined to improve your analysis? In short, what’s next now that you understand the data fully and have attempted to answer these questions?
These are question from the project outline:
How does room type affect an Airbnb’s host potential review score?
Does the neighborhood affect an Airbnb host review score rating? 
What are the most popular amenities Airbnb host offer on their postings? 
How do different types of Airbnb accommodations (e.g. private rooms, entire homes, shared rooms) vary in terms of review score (With new dataset we can add price and popularity)?
Any Geographical or neighborhood-based trends of Airbnb rentals?
Average price of Airbnb rentals of neighborhoods within certain cities? 3
https://drive.google.com/drive/folders/1WUVJRzptog46MLO0vHpEB8G67Gl14rbw

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