Airbnb Seattle Data Analysis

Table of Contents

1. Installation
2. Motivation
3. File Descriptions
4. Results
5. Licensing, Authors, and Acknowledgements

Installation

This project uses Python 3, besides Jupyter Notebook. The list of libraries to run this project are:

• Pandas
• Numpy
• MatplotLib
• Seaborn
• XGBoost

Motivation

In this project, I want to investigate the AirBnB dataset from Seattle to answer the following questions:

1.How much is the average price of different room types, property types, and neighborhoods in Seattle data and which amenities are provided by the host in more expensive listings?

2.How different features of a listing can be related to the review scores left by customers?

3.How different features can be realted to predict the price of a listing based on the data modeling results?

File Descriptions

There are three files in Files directory of this project that investigates different questions that we want to answer.

Data for this project is included in Data directory.

Results

The report of this study can be found here.

Licensing, Authors, Acknowledgements

Credit to AirBnB for providing the data. You can find the Licensing for the data and other descriptive information at the Kaggle link available here. This code is free to use.