This was an exploratory data analysis of Airbnb listings in New York City, completed as part of Udacity's Data Analyst Nanodegree Program. The datasets obtained were accurate as of 02 October 2017. It provides listing details such as the number of bed and bathrooms, reviews, ratings and price per night. There are a total of 44,317 listings with up to 96 features for each listing. For this project, I have conducted a deep-dive into 11 of these features.
The EDA was done entirely in R and exposed several interesting and peculiar insights. For instance, it seems that NYC listings with stricter cancellation policies tend to be more expensive on average. Of course, correlation does not imply causation. Nevertheless, this contradicts conventional logic in which hotels charge lower prices for a non-refundable rate.