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Airbnb-Price-Analysis

Table of Contents

  1. Installation
  2. Project Motivation
  3. File Descriptions
  4. Results

Installation

libraries needed by this project are provided by the Anaconda distribution of Python. he code should run with no issues using Python versions 3.*.

Project Motivation

In this project, I look into Airbnb Seattle Data to housing price and ratings and try to answer the following research questions: Q1: How can we predict the housing price? Q2: How price and rating relate with each other? Q3: What’s the factor that drives higher prices?

File Descriptions

The project consists of two files, one dataset file and one jupyter notebook file: listings.csv contains the Airbnb Seattle dataset Airbnb Seattle article.ipynb contains the analysis, visaulisations, the models and the conclusion.

Result

The result is presented in the following Medium article .

Licensing, Authors, Acknowledgements

Data Source can be acquired from Kaggle

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