For detail analysis, please follow the link: locdam.github.io/Airbnb-Analysis/
This project analyze the U.S. Airbnb Open Data in www.kaggle.com.
Since 2018, Airbnb has emerged as an unique and distinct exploration in the hospitality field. It branched out in a much different way compare to the tradition hospitality industry. Also, as a person who has been working as a host in Airbnb recently, this is a great opportunity to take a deep dive hoping to learn and predict some behavior that can further benefit my business.
This data contains multiple columns decribing many factors such as hostname, listing id, listing name, latitude, longtitude, price, room type, minimum number of nights, number of reviews, last review date, reviews per month, availability, host listings and city.
Among these columns, I will spend the most time in the price, room type, minimum of nights, city. I hope these columns will paint me a clearer picture in this industry. Also, I hope to see many surprises reusults and plots to prove that my prediction is wrong and from there I can learn more new things.
My hope after this project is to predict the behavior of customers based on the given features by answering these questions (and potentially more)
- How the location (to me I believe the most important factor) will effect the business?
- How the price difference and the comparison within small range of neighbor or between the cities will make any effect?
- What difference, and how big the difference of room choices (condo, house, room, ect.) will effect the customers?
- What is the most number of nights that get booked the most, in each regions and why?
- During which time of the year will there be the most booking? (I expect it will be Summer, but we will see)
- Base on the answers to the previous questions (and more), what can I learn to implement to my own business and what prediction should I make?
- Also, this data is last updated in 2020, hence, it will has different changes compared to current market. Then how much and what are the difference? What changed the most after 2 years of pandemic?