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https://github.com/iusztinpaul/airbnb-data-analysis
Airbnb data analysis on the biggest cities in The Netherlands following the CRISP-DM methodology.
https://github.com/iusztinpaul/airbnb-data-analysis
airbnb data datanalysis datascience machine-learning numpy pandas python
Last synced: about 3 hours ago
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Airbnb data analysis on the biggest cities in The Netherlands following the CRISP-DM methodology.
- Host: GitHub
- URL: https://github.com/iusztinpaul/airbnb-data-analysis
- Owner: iusztinpaul
- Created: 2022-06-27T06:26:32.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2022-07-30T13:37:48.000Z (over 2 years ago)
- Last Synced: 2023-03-10T11:33:10.905Z (over 1 year ago)
- Topics: airbnb, data, datanalysis, datascience, machine-learning, numpy, pandas, python
- Language: Jupyter Notebook
- Homepage:
- Size: 3.56 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# AirBnb Data Analysis
To directly see the analysis results, check this [Medium article](https://medium.com/@p.e.iusztin/this-is-what-you-should-know-when-travelling-to-the-netherlands-with-airbnb-aaa19cef4615).
### Table of Contents
1. [Installation](#installation)
2. [Project Motivation](#motivation)
3. [Used Data](#data)
4. [File Descriptions](#files)
5. [Results](#results)
6. [Licensing, Authors, and Acknowledgements](#licensing)
## Installation
The code was tested with:
1. Python 3.8
2. Ubuntu 20.4
3. Conda 4.12
Create a conda environment:
```shell
conda create --name airbnb-data-analysis python=3.8
conda activate airbnb-data-analysis
```
Install Python dependencies:
```shell
pip install -r requirements.txt
```
## Project Motivation
In our data analysis we have used the dataset described in the [Used Data](#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](http://insideairbnb.com/get-the-data/). 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](http://insideairbnb.com/amsterdam/).
## 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](https://medium.com/@p.e.iusztin/this-is-what-you-should-know-when-travelling-to-the-netherlands-with-airbnb-aaa19cef4615)
## 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](http://insideairbnb.com/data-policies).
Otherwise, we are more than happy to use this code as you like!