The New York Airbnb Insights project aims to analyze and provide insights into Airbnb listings in the state of New York. For further details, please refer to the GitHub Repository linked here.

New York Airbnb Insights

Introduction

In the bustling metropolis and serene countryside of New York State, Airbnb has reshaped the lodging landscape. From cozy apartments in Brooklyn to spacious lofts in Manhattan, travelers have a plethora of options. This project, “New York Airbnb Insights,” delves into the treasure trove of data from Airbnb listings across New York State, uncovering trends, patterns, and nuances that underpin the dynamic hospitality scene.

Dataset Overview

The project harnesses the power of a comprehensive dataset named airbnb_data.csv. This dataset encapsulates vital information about Airbnb listings in New York. It contains the following columns:

• listing_id: The unique identifier for a listing
• description: The description used on the listing
• host_id: Unique identifier for a host
• neighbourhood_full: Name of boroughs and neighbourhoods
• coordinates: Coordinates of listing (latitude, longitude)
• listing_added: Date of added listing
• room_type: Type of room
• rating: Rating from 0 to 5.
• price: Price per night for listing
• number_of_reviews: Amount of reviews received
• reviews_per_month: Number of reviews per month
• availability_365: Number of days available per year
• number_of_stays: Total number of stays thus far

Exploratory Analysis

Descriptive Statistics

The analysis kicks off with descriptive statistics, unveiling fundamental metrics such as the average price per night, distribution of ratings, and average number of reviews per month. Noteworthy insights include an average price of $140.24 per night, with ratings distributed across the spectrum from 0 to 5.

Geospatial Analysis

Delving deeper, geographical analysis uncovers hotspots in the state. Brooklyn’s Bedford-Stuyvesant emerges as a bustling hub with a significant number of listings, while Manhattan’s Upper East Side exudes elegance with its upscale offerings.

Temporal Analysis

Temporal analysis sheds light on trends over time. Seasonal fluctuations in pricing and availability reveal insights into the ebbs and flows of the market, providing valuable foresight for hosts and travelers alike.

Host and Room Type Analysis

The project further investigates the dynamics between hosts and their listings. On average, hosts manage approximately 1.10 listings, with intriguing correlations between the number of listings and ratings or prices. Room type analysis showcases the dominance of entire places, catering to diverse traveler preferences.

Correlation Analysis

Correlation analysis delves into relationships between key variables. Surprisingly, there’s minimal correlation between price and ratings, while availability exhibits a modest positive correlation with the number of reviews.

Conclusion

The “New York Airbnb Insights” project unveils the intricate tapestry of New York’s hospitality scene. From the buzzing streets of Manhattan to the serene landscapes of the Catskills, Airbnb listings offer a myriad of experiences. Hosts can leverage these insights to optimize their offerings, while travelers can navigate the vibrant market with confidence. As New York continues to evolve, this project serves as a beacon, illuminating trends and insights for stakeholders in the hospitality industry.

Author

• LinkedIn: Mohammed Mebarek Mecheter
• Email: mohammedmecheter@gmail.com
• GitHub: Mohammed Mebarek Mecheter