airbnb_small {bayesrules}R Documentation

Chicago AirBnB Data

Description

The AirBnB data was collated by Trinh and Ameri as part of a course project at St Olaf College, and distributed with "Broadening Your Statistical Horizons" by Legler and Roback. This data set, a subset of the airbnb data in the bayesrules package, includes the prices and features for 869 AirBnB listings in Chicago, collected in 2016.

Usage

airbnb_small

Format

A data frame with 869 rows and 12 variables. Each row represents a single AirBnB listing.

price

the nightly price of the listing (in USD)

rating

the listing's average rating, on a scale from 1 to 5

reviews

number of user reviews the listing has

room_type

the type of listing (eg: Shared room)

accommodates

number of guests the listing accommodates

bedrooms

the number of bedrooms the listing has

minimum_stay

the minimum number of nights to stay in the listing

neighborhood

the neighborhood in which the listing is located

district

the broader district in which the listing is located

walk_score

the neighborhood's rating for walkability (0 - 100)

transit_score

the neighborhood's rating for access to public transit (0 - 100)

bike_score

the neighborhood's rating for bikeability (0 - 100)

Source

Ly Trinh and Pony Ameri (2018). Airbnb Price Determinants: A Multilevel Modeling Approach. Project for Statistics 316-Advanced Statistical Modeling, St. Olaf College. Julie Legler and Paul Roback (2019). Broadening Your Statistical Horizons: Generalized Linear Models and Multilevel Models. https://bookdown.org/roback/bookdown-bysh/. https://github.com/proback/BeyondMLR/blob/master/data/airbnb.csv/


[Package bayesrules version 0.0.2 Index]