The main goal of this project is to help Airbnb clients to book the Airbnb listing of interest at the right time with the best possible "cheaper" price. Thus, saving the clients’ money and time! It starts with understanding the pricing algorithm of Airbnb homes in different cities that have different climate nature (i.e., can have different seasons at the same time of the year). That includes studying different questions:
- What is the seasonality of booking? So what is the best time during the year to book? Is it different among the three cities of interest? Also, from another angel I want to see how far in advance a customer should book?
- Are there particular neighborhoods showing some patterns for the average price of Airbnb homes?
- Are there any amenities that are more important than others, and what amenities that are correlated with each other?
- How can the bad reviews history affect the Airbnb market?
- Testing the correlation between the price and many other features such as the size of the apartment/house, sharing the property, etc!
Pre-requisites:
git clone https://github.com/nickbent/AirBnB.git \
&& cd AirBnB \
&& pip install -U -r requirements.txt \
&& pip install -e . \