Airbnb is a privately-owned accommodation rental website which allows house owners to rent out their properties to guests looking for a place to stay. Airbnb enables a marketplace where people can rent lodging in residential properties. The main idea is a house-sharing service that offers an opportunity for travellers to get cheaper accommodation wherever they travel to. As of 15 September 2019, hosts have earned more than $80bn sharing their homes and spaces on Airbnb. The offers range from shared rooms to full condos/houses and can offer unique and differentiated options as compared to normal traditional hotels. Airbnb has 31 offices across the world and have hosted 400 million guests since its launch. Opportunity for homeowners to make more money from their homes by sharing with travellers. Airbnb offers complete independence to its hosts to decide on the price for their properties, however with only minimal attributes to leverage upon and compare similar previous listings in their neighbourhood, the hosts find it difficult to come up with a competitive price. With the number of hosts using Airbnb increasing, coming up with the right price to remain competitive in a host’s neighbourhood is important. On the other side, guests can also find places to stay at a reasonable price and understand the seasonal demands. Airbnb has also seen a potential growth with the number of rentals/listings in its website subsequently increasing each year. Through our analysis, we want to address the following: • What time of the year are Airbnb’s most popular in San Francisco? Are specific holiday seasons more popular? • What are the most important characteristics of a listing, and how do they influence price? • Understand the rental landscape in San Francisco through various static and interactive visualisations. • How fast is Airbnb growing in San Francisco? • The exploration results could refer useful knowledge for hosts who search for comparable price and make their listing stand out. • Predict the Airbnb Listing Price in San Francisco • We wanted to do a project that addresses a common issue that could either benefit an organization or the general public. The challenge that Airbnb hosts face is determining the optimal nightly rent price. • Since Airbnb is a marketplace, the amount a host can charge on a nightly basis is closely linked to the dynamics of the marketplace. • Moreover, we wanted to pick a dataset that gives us some scope to perform various analysis. Therefore, we chose the topic AirBnb Rental Listings for San Francisco, United States.

Airbnb, Inc. is an American vacation rental online marketplace company based in San Francisco, California, United States. Airbnb offers arrangements for lodging, primarily homestays, or tourism experiences. The company does not own any of the real estate listings, nor does it host events; it acts as a broker, receiving commissions from each booking. Reference Since 2008, guests and hosts have used Airbnb to travel in a more unique, personalized way.

Airbnb, Inc. is an american vacation rental online marketplace company based in San Francisco, California, United States. Airbnb offers arrangement for lodging, primarily homestays, or tourism experiences. The company does not own any of the real estate listings, nor does it host events; it acts as a broker, receiving commissions from each booking. In this project we are trying to predict whether a listing would receive high booking or not.

About Dataset New York City Airbnb Data Cleaning Airbnb, Inc is an American company that operates an online marketplace for lodging, primarily homestays for vacation rentals, and tourism activities. Based in San Francisco, California, the platform is accessible via website and mobile app. Airbnb does not own any of the listed properties; instead, it profits by receiving commission from each booking. The company was founded in 2008. Airbnb is a shortened version of its original name, AirBedandBreakfast.com. About Dataset Context Since 2008, guests and hosts have used Airbnb to travel in a more unique, personalized way. As part of the Airbnb Inside initiative, this dataset describes the listing activity of homestays in New York City

Context Airbnb, Inc. is an American vacation rental online marketplace company based in San Francisco, California, United States. Airbnb offers arrangements for lodging, primarily homestays, or tourism experiences. The company does not own any of the real estate listings, nor does it host events; it acts as a broker, receiving commissions from each booking. Reference Since 2008, guests and hosts have used Airbnb to travel in a more unique, personalized way. Objective Imagine you are Data Scientist who would help find the price for lodging or homestays based on different attributes mentioned in their listings. Oh wait, what are listings? Listings can include written descriptions, photographs with captions, and a user profile where potential guests can get to know a bit about the hosts.And you are given the listings of one of the most popular cities in central Europe: Amsterdam. Now your job is to build a machine learning model that will automatically predict the price for lodging or homestays