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Analyzing Airbnb listings in New York City by exploring trends in #, availability, and neighborhoods across the city’s five boroughs. This analysis includes creating SQL queries in PostgreSQL and data visualizations in Tableau with the hope of discovering more about the short-term rental market.

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brianwei01/Airbnb-NYC

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Airbnb NYC Listings Analysis

Link to dashboard:

Tools Used

  • SQL (PostgreSQL)
  • Tableau

The Data

The datasets were sourced from the Inside Airbnb website, which provides detailed information on Airbnb listings in cities worldwide. This data includes a wide range of attributes such as listing IDs, host details, neighborhood locations, room types, #, availability, and more. The data is regularly updated and offers a comprehensive view of Airbnb activity across the city’s five boroughs, making it an ideal source for analyzing trends in the Airbnb market.

Analysis

The analysis involved several steps, starting with a thorough exploration of the data using SQL queries in PostgreSQL's pgAdmin 4 to understand the structure, check for missing values, and calculate basic statistics. This was followed by more detailed analyses to uncover trends in #, room types, and neighborhood activity. Key insights were then visualized in Tableau, with dashboards showcasing individual listings on a map of New York City, and neighborhood-level trends in # and availability.

About

Analyzing Airbnb listings in New York City by exploring trends in #, availability, and neighborhoods across the city’s five boroughs. This analysis includes creating SQL queries in PostgreSQL and data visualizations in Tableau with the hope of discovering more about the short-term rental market.

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