Airbnb-analysis-Paris

Airbnb Data Analysis for Paris

Table of contents

1. Project Overview
2. Project Components
3. Installation
4. File Description
5. Motivation
6. Acknowledgements
7. Restuls

1. Project Overview

Airbnb is hottest startup company in 21st century. The company provides the service of matching unoccupied and unused apartments as a platform. By growing importance of "Sharing Economy", Airbnb's service is expanding to other fields. After Covid-19 crisis, Tourism and Hotel business are facing a financial crisis.I analyze the influence of Airbnb on the Paris, Most visited destination by international tourism.

2. Project Components

1. Exploring datasets
2. Business understanding
3. Visualize the datasets and observation
4. result

3. Installation

• The code should run with no issues using Python versions 3.*.
• No extra besides the built-in libraries from Anaconda needed to run this project
• Data Processing & Machine Learning Libraries: NumPy, SciPy, Pandas, Sciki-Learn
• Data Visualization: Matplotlib, Seaborn

4. File descriptions

• listings_df = The dataset contains detailed Listings data for Paris.
• calendar_df = The dataset contains detailed Calendar data for Listings in Paris.
• reviews_df = The dataset contains detailed review data for Listings in Paris.

5. Motivation

• Prices Overview
• Listings count Overview
• Occupancy rate
• Impact of Corona virus on listings and prices

6. Acknowledgements

This project is part of the Data Science Nanodegree from Udacity. The data is provided by Inside AirBnB, you can download the data from here

7. Results

I have written a blog post for this project here This repository contains an analysis of AirBnB Data of Paris in the years 2019 and 2020.
Analysis follows CRISP-DM process!