Airbnb Geospatial Analysis 🌍

This project is an exploration and analysis of Airbnb data with a focus on geospatial and exploratory data analysis. It includes interactive visualizations, statistical insights, and recommendations for users interested in Airbnb accommodations in specific countries and cities.

Table of Contents

• Introduction
• Getting Started
• Usage
• Exploratory Data Analysis
• Contributing
• License

Introduction

The Airbnb Geospatial Analysis project provides users with tools to analyze Airbnb data from various countries and cities. It offers features such as:

• Geospatial analysis to visualize Airbnb listings on a map.
• Exploratory Data Analysis (EDA) for understanding price distributions, top hotels, and more.
• Recommendations based on user-defined criteria, including price range.

Getting Started

To get started with this project, you can follow these steps:

1. Clone the repository to your local machine:

   git clone https://github.com/your-username/airbnb-geospatial-analysis.git

2. Install the required dependencies using pip : pip install -r requirements.txt

Usage

• Launch the Streamlit app by running main.py.
• Use the app to explore geospatial data, select countries and cities, set price filters, and view recommendations.
• Analyze the exploratory data analysis (EDA) visualizations for insights into Airbnb data.

Exploratory Data Analysis

The project includes an EDA section with several interactive visualizations, including:

• Price Analysis by Country and City.
• Distribution of Price by Country.
• Distribution of Price using Box Plot.
• Scatter Plot by Price and Availability.

Contributing

Contributions to this project are welcome! If you have ideas for improvements, new features, or bug fixes, please open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details