Airbnb-Listing-Chicago

Data source: http://insideairbnb.com/get-the-data.html (Chicago)

1. calendar.csv - Information about the availability calendar for each listing
2. listings.csv - Detailed listings data, including various features of each listing such as number of bedrooms, bathrooms, etc.

Goal:

1. Predicting of Airbnb listing prices
2. Analyze which variables would affect AirBnB rentals Based on these results, hosts are provided with the pricing strategy while guests would more understand how to choose their desirable rentals.

Outline:

1. Exploratory data analysis of the calendar data
2. Exploratory data analysis of the listing data
3. Data preprocessing and feature creation/selection of the listing data
4. Model building based on the listing data with several regressors
5. Model tuning
6. Feature importance

If the file is not loaded, please see: https://nbviewer.jupyter.org/github/fylinhub/Airbnb-Listing-Chicago/blob/master/Airbnb_listing_chicago.ipynb