Project Title: Airbnb Price Analysis using Tableau
Project Overview: This project focuses on analyzing Airbnb rental prices based on multiple factors such as the number of bedrooms, zip codes, and yearly revenue trends. The goal is to help potential Airbnb hosts make informed decisions on pricing their properties and to provide insights into which areas and property types generate higher revenues.
Data Source: The dataset used for this analysis is from Airbnb, containing details about properties, their prices, locations, and the number of bedrooms.
Objectives:
- To analyze the average price of Airbnb rentals based on the number of bedrooms.
- To compare the rental prices across different zip codes.
- To visualize the revenue trends over time and identify high-performing zip codes.
Dashboard Components:
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Avg Price per Bedroom:
- Purpose: Display the average rental price for properties based on the number of bedrooms.
- Insights: Shows how the number of bedrooms affects the pricing of the Airbnb properties, with the average price increasing as the number of bedrooms increases.
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Price per Zipcode:
- Purpose: A bar chart and map displaying the distribution of rental prices across various zip codes.
- Insights: Allows users to identify which zip codes have higher rental prices, making it easier to target high-demand areas for renting out properties.
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Revenue of the Year:
- Purpose: A line graph visualizing the revenue trends over the course of a year.
- Insights: Highlights seasonal trends in rental prices, allowing hosts to adjust their pricing strategies based on peak and off-peak periods.
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Distinct Count of Bedroom Listings:
- Purpose: A summary of the number of listings categorized by the number of bedrooms.
- Insights: Provides a clear overview of the Airbnb market segmentation in terms of the number of bedrooms offered by different properties.
Key Findings:
- Bedrooms: The rental price significantly increases with the number of bedrooms, peaking at 6-bedroom properties, which command the highest average price.
- Zip Code 98109: This area has one of the highest average rental prices at $166, making it a prime location for hosting.
- Revenue Trend: The revenue generated from Airbnb rentals grows steadily over the year, with a noticeable spike in late Q3, indicating high demand during certain periods.
Tools & Techniques:
- Tableau: Used for data visualization and creating interactive dashboards.
- Calculated Fields: Implemented to compute averages and aggregate values such as “Average Price” and “Revenue of the Year.”
- Filters and Maps: Added to allow for dynamic exploration of the dataset based on bedroom count and zip codes.
Next Steps:
- Further Analysis: Conduct deeper analysis by incorporating additional variables such as property type (entire home vs. shared room) and host ratings.
- Predictive Analytics: Utilize machine learning models to predict future pricing trends based on historical data and external factors like local events or economic conditions.
Conclusion: This analysis provides Airbnb hosts with valuable insights into how they can optimize their pricing strategy based on location, number of bedrooms, and time of year. The dashboard offers an intuitive way to explore various aspects of the Airbnb market, making it easier for users to make data-driven decisions.