There are more than 15k listings of Airbnb in the training set and below is the data dictionary:

Listing ID - unique id of the listing
Listing Name - this is the name of the listing, this is anonymized in the dataset and you can feel free to drop this variable from the data
Host ID - unique ID of the listing host
Host Name - name of the host who manages/owns the listing
Host Since - date since they have been hosting on Airbnb
Host Response Time - Avg time taken by the host to respond to any query they get
Host Response Rate - Avg response rate to the queries that the host receives for their listing
Is Superhost - this field says whether the host is superhost or not. Superhost implies the best-rated host badge given by Airbnb based on the overall listing experience
neighbourhood - provides information about neighbourhood of the listing
Neighborhood Group - provides information about neighbourhood group of the listing
City
Postal Code
Country Code
Country
Latitude
Longitude
Is Exact Location
Property Type
Room Type
Accomodates
Bathrooms
Bedrooms
Beds
Square Feet
Guests Included
Min Nights
Reviews
First Review
Last Review
Overall Rating
Accuracy Rating
Cleanliness Rating
Checkin Rating
Communication Rating
Location Rating
Value Rating
Instant Bookable
Business Travel Ready
Price - price is the target variable

Saving Prediction File & Sample Submission

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below:

Listing ID	Price
22604662	89
26069778	65
20192066	25
33736793	49
2807047	45
4658713	69
16718167	31
402538	39
25882805	70
7373561	79
34277998	35
15715245	25

Etc.

Note that the header name should be ‘prediction’ else it will throw an evaluation error.

Notebook Submission

Steps to follow to submit your notebook:

Go to the Notebook section on this challenge page
Click on the 'Upload Notebook' button on top left corner as shown in the image below:
Make sure to make the visibility of your notebook as 'public' while uploading the notebook.
Provide Notebook Title, Summary, add some tags, go to next, chose a file and click on Upload.

Acknowledgement

Note: To make the data challenge ready, certain changes have been made to the dataset by the contributor. Also, please note, this is not an official challenge hosted by Airbnb. It is hosted for educational purposes for the community to learn from real-world datasets.

Dataset credits: Thanks Murray Cox for putting this data together under the Inside Airbnb Data initiative.

Data Sprint #47: Airbnb Berlin Price Prediction

Challenge Starts

Registration Ends

Challenge Ends