Table of Contents

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

Installation

Codes are written in python versions 3.* and Libraries used in this project:

1. numpy
2. pandas
3. matplotlib
4. seaborn
5. datetime
6. sklearn
7. xgboost

Project Motivation

For this project, I was interested in using Airbnb-Istanbul Data from 2020 to better understand:

1. What is the price depends on?
2. Super Hosts
3. Is listings prices are predictable?

File Descriptions

The listings.csv.gz file is the airbnb-istanbul 2020 data i used in this project.

There is one notebook available here to showcase work related to the above questions. Markdown cells were used to assist in walking through the thought process for individual steps. Also there is an html file which shows the after notebooks code run.

Results

The main findings of the code can be found at the post available here

Licensing, Authors, Acknowledgements

Must give credit to Airbnb for the data. You can find the Licencing for the data and other descriptive information at the Airbnb link available here .