AirBnb Data Analysis

To directly see the analysis results, check this Medium article.

Table of Contents

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

Installation

The code was tested with:

1. Python 3.8
2. Ubuntu 20.4
3. Conda 4.12

Create a conda environment:

conda create --name airbnb-data-analysis python=3.8
conda activate airbnb-data-analysis

Install Python dependencies:

pip install -r requirements.txt

Project Motivation

In our data analysis we have used the dataset described in the Used Data section to compare different Airbnb properties across The Netherlands. We wanted to answer to the following questions:

1. Which city has the highest price tag? What about their neighborhoods?
2. What city and neighborhoods are in most demand?
3. Are reviews for more expensive houses better?
4. What are the factors that affect a property's price?

Used Data

We have used the public data given by Airbnb. More concrete we chose to perform our analysis on the biggest cities from The Netherlands:

• Amsterdam
• Rotterdam
• The Hague

NOTE: The code is actually generic and could be run on any other cities from Airbnb. But the scope of our analysis was to compare how Airbnb is performing in The Netherlands.

Data Folder Structure

The notebooks expect the data in the following format:

data/
      - Amsterdam/listings.csv
      - Rotterdam/listings.csv
      - The Hague/listings.csv

NOTE: As long as you follow this folder structure you can add any other city.

File Descriptions

Our data analysis is performed into the netherlands.ipynb file, which follows the CRISP-DM methodology.

NOTE: We did more business & data understanding by using their data exploration system.

Results

The results of our data analysis is presented in detail in a Medium article called This Is What You Should Know When Travelling to the Netherlands With Airbnb

Licensing, Authors, and Acknowledgements

Must be really grateful for Airbnb that they exposed their data to the public! You can find the Licensing for the data here. Otherwise, we are more than happy to use this code as you like!