Airbnb Data Analysis Dashboard

This repository contains a Shiny dashboard designed to analyze Airbnb data in the U.S. The dashboard provides visual insights into host behavior, room types, pricing trends, and geographical influences, offering users a detailed understanding of Airbnb's market dynamics.

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Try It Out

View the live dashboard here

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Project Structure

The project is organized into three primary components: ui, server, and www, all integrated into the app.R file.

Directory Structure:

server

The server folder contains logic for each tab and handles the backend operations of the dashboard.

• home.R: Server logic for the home page.
• interaction1.R: Server logic for correlation heatmap visualization.
• interaction2.R: Server logic for geographical distribution visualization.
• interaction3.R: Server logic for average Airbnb price per state visualization.
• interaction4.R: Server logic for room type pricing analysis.
• report.R: Server logic for displaying the project report.

ui

The ui folder defines the layout and design for each tab in the dashboard.

• contact.R: Contact information layout.
• home.R: Introduction and project overview layout.
• interaction1.R: Layout for correlation analysis.
• interaction2.R: Layout for geographical distribution analysis.
• interaction3.R: Layout for average price per state.
• interaction4.R: Layout for room type pricing analysis.
• report.R: Layout for displaying the project report.
• sidebar.R: Layout for the collapsible sidebar navigation.

www

The www folder stores static files, preprocessed data, and styling.

• AB_US_2023.csv: Original Airbnb dataset.
• processed_state_avg_price.csv: Preprocessed data for visualizing average price per state.
• reportRcomp.pdf: PDF report generated from the analysis.
• style.css: Custom CSS for styling the dashboard.

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Dashboard Features

1. Home Page:
   Introduces the project, dataset, and navigation instructions.

   • Displays an overview of the analysis.
   • Highlights key insights, such as pricing trends, geographical patterns, and room type distribution.

2. Key Interactions:

   • Interaction 1: Correlation heatmap showing relationships between variables like price, reviews, and minimum nights.
   • Interaction 2: Geographical distribution of Airbnb listings, highlighting popular neighborhoods.
   • Interaction 3: Average price per state visualization, with data preprocessing for fast rendering.
   • Interaction 4: Room type pricing distribution, allowing dynamic threshold filtering.

3. Report Tab:
   A detailed PDF report is embedded for users to view or download.

4. Contact Tab:
   Displays professional contact information and links.

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How It Works

Preprocessing for Efficiency

To enhance deployment speed, the dataset is preprocessed, and results (like average price per state) are saved in a CSV file (processed_state_avg_price.csv). The dashboard reads this preprocessed data for visualization, avoiding the need for intensive computations during runtime.

Deployment

The dashboard is deployed via ShinyApps.io, ensuring accessibility and scalability.

How to Run Locally

1. Clone the Repository:

git clone https://github.com/sinsniwal/airbnb-trends
cd airbnb-trends

2. Install Dependencies: Make sure you have R and the required libraries installed. Use the following command in R to install dependencies:

install.packages(c("shiny", "shinydashboard", "readr", "dplyr", "ggplot2", "plotly", "sf", "tigris", "viridis"))

3. Run the App: Open RStudio or your terminal, navigate to the project directory, and run:

library(shiny)
runApp("app.R")

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Example Visualizations

Screenshot: Average Price per State

Screenshot: Room Type Pricing Distribution

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Feel free to clone the repository, modify the code, and explore the Airbnb data in your own way!