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项目作者： nkibrislioglu

项目描述 ：
Predicting price and customer satisfaction: Airbnb data
高级语言： Jupyter Notebook
项目地址: git://github.com/nkibrislioglu/AIRBNB-Hosts-Need-to-knows.git


AIRBNB-Hosts-Need-to-knows

Table of Contents

  • Libraries
  • Project Motivation
  • File Descriptions
  • Results
  • Licensing, Authors, and Acknowledgements

Libraries

The libraries used in this repository are:

  • pandas
  • numpy
  • matplotlib
  • datetime
  • seaborn
  • sklearn

Project Motivation

Aribnb is a world wide
This project aims to analyze airbnb data in Seattle to provide airbnb hosts a general picture about what airbnb data says. There are three questions I am trying to explore within this project:

  • How prices changes according to time and neighborhood?
  • Which factors helps us to predict the price?
  • Which factors helps us to predict the customer satisfaction?

In this project I hope to help airbnb hosts who are trying to decide prices and improve their guests’ satisfaction.

File Descriptions

There is one notebook (named “UdacityP1”) available here to showcase work related to the above questions. This notebook consists of three parts adressing each research question. The detailed descriptions are available within the notebook.

Results

The main findings of the code can be found at the post available here: @nkibrislioglu/need-to-know-for-airbnb-hosts-5165320d1447?sk=2f94c208186d485e5d624eca3c6675f5"">https://medium.com/@nkibrislioglu/need-to-know-for-airbnb-hosts-5165320d1447?sk=2f94c208186d485e5d624eca3c6675f5

Licensing, Authors, and Acknowledgements

Airbnb data set is used in this project. You can find additional information about the data here: https://www.kaggle.com/airbnb/seattle/data

Note: This repository is part of Udacity Data Science Nano degree program projects