AirBnB Listing Hotspots in NewYork City

Photo credits (Pinterest)

Introduction

Considered by many as the cultural hub of the world, the City of New York is certainly a locality, a lot of people aspire to end up at.

Be it the formidable skyline consisting of the empire state building, the endless hustle and bustle of the financial districts, or the calmness and serenity of the Central Park, there is certainly an Aura this city possesses which attracts people from all over the world.

Therefore this attraction has certainly allowed AirBnbs to flourish in this city and that is what I will be going through in this article. Taking actual data from AirBnB, I will share some interesting insights I observed and share what I feel are the potential hotspots for people who are interested in opening a listing in this city.

1. What are the highest number of listings by a host?

AirBnB policies allow hosts to have multiple listings if they meet the general requirements. This is something that a lot of people or real estate companies do. In the image below you will find the highest listing by individual hosts. The host ids are anonymized to keep things privacy compliant.

We can see the top host has over 300 listings. From the dataset it is also possible to find the name of this host and it could be seen that this host is a real estate company in New York and that is why it logically makes sense to be able to have so many listings for an individual host. NOTE: I have kept the names hidden from this article for anonymity but for anyone interested to find out, can do so with the dataset.

2. What is the average breakdown of price and its distribution in different neighborhood groups?

Every neighborhood has a personality that distinguishes it or makes it standout. Some are more high end and modern while others might have some other historical aspects about it. In the plot and table below, we see the breakdown of the total listings and the price in different neighborhoods which will provide us with some interesting results.

The total listings and the price breakdown

1. Manhattan has the most expensive listings.
2. Bronx has the cheapest listings
3. Staten Island has the lowest amount of listings.

Average prices and its distribution per neighborhood

It is interesting to note that there is more variation in prices in Brooklyn and Manhattan. This basically means you can potentially find cost friendly or more luxurious listings in these neighborhoods. Whereas in the other 3 neighborhoods the listings generally show less price fluctuations.

3. Percentage breakdown of the types of listings in different neighborhoods

The data provided consists of 3 types of listings.

1. Entire home/Apartment
2. Private room
3. Shared room

Here we see the percentage distribution of different room types in different neighborhoods. For someone considering to open a listing, it would be useful to know what sort of listings are in demand in different areas. In the image below I have broken down the percentage distribution of different room types in each neighborhood.

Percentage breakdown of room types in different neighborhoods

1. Around 60% of the listings in Manhattan are Entire Homes
2. Around 60% of the listings in Bronx and Queens are private rooms
3. Brooklyn and Staten Island have almost an equal amount of Apartments and private room listings.
4. Listings of shared rooms are relatively low in all neighborhoods

We have seen earlier that Manhattan has the highest average price listings as well. This correlates with the information provided here as having the largest percentage of listings to be apartments, the average price in the neighborhood is going to be the highest which is true.

4. Hotspots to open AirBnB listings

Now we will look at the neighborhoods that can be good localities to list an AirBnb. To do this, I am taking into account the following features present in the dataset.

1. Number of reviews: This provides a good insight into how frequently listings in a neighborhood are visited.
2. Number of listings: This lets us know if a neighborhood has a very high number of listings demanding more competition or relatively lesser listings.
3. Mean/Median price of neighborhood: For my analysis, I have taken the median price to cater for the outliers.

Using the above 3 features, I calculate the “yield” of a neighborhood. The yield can be depicted by the formula below:

yield = (number of reviews / total number of listings) * (median price)

Based on the above calculations I mapped the top neighborhoods that provide the highest yield. NOTE: Since some neighborhoods have very few listings, they do not provide a robust sample space to make deductions. Therefore I have taken into account neighborhoods with at least 50 listings.

Highest yield providing neighborhoods

1. Springfield Gardens in Queens is the top potential hotspot.
2. Remaining majority of the neighborhoods are either in Brooklyn or Manhattan.

Heatmap of top neighborhoods

Conclusion

In this article I have provided some insights about AirBnB listings in the city of NewYork and given suggestions for potential hotspot areas for opening an AirBnb. To end this article I would like to summarize my findings during this analysis.

1. The hosts with the highest number of listings. The highest lister had over 300 listings.
2. The average price and price distributions for each neighborhood. Manhattan is on average the most expensive area to host a listing and has the most variation in terms of prices.
3. Percentage distribution of the different types of room in each neighborhood. Bronx and Queens have a higher percentage of private rooms and Manhattan has a higher percentage of Apartment listings.
4. Top neighborhoods to open an AirBnB listing. Springfield Gardens in Queens and South Slope in Brooklyn are two of the hottest potential hotspots to open a listing.

If anyone is interested in having a look at the code, please feel free to check out my Github repository. I hope you found the article interesting and you found some ideas in case you are looking to open a listing in the city of New York :)