/DS_ND_BLOG

This is a repository that contains a notebook concerning a jupyter notebook that was used to write a Data Science Blog.

Primary LanguageJupyter Notebook

Installations

The following packages (i.e., libraries) are necessary to finish this project:

  1. python >=3.6
  2. numpy >= 1.19.2
  3. pandas >= 1.0.1
  4. seaborn >= 0.10.0
  5. matplotlib >= 3.1.3

Project Motivation

The motivation of the current project is to get insights from a dataset from Airbnb dating from 2016.

Title: ANALYSIS OF AIRBNB DATA: THE INFLUENCE OF TIME, DAY OF WEEK, AND CLIENT DISTRIBUTION

Outline of the Data Analysis:

  1. How does the total price of Airbnb vary over the first and second semesters of 2016?
  2. How does the total price of Airbnb vary for each day of the week for the first and second semesters of 2016?
  3. How does the mean price by the client is distributed over the first and second semesters of 2016?

File Descriptions

  1. airbnb_seatle_verson1.ipynb: ipython notebook containing all the data analysis of the Medium blog: "ANALYSIS OF AIRBNB DATA: THE INFLUENCE OF TIME, DAY OF WEEK, AND CLIENT DISTRIBUTION";

How to interact to interact with your project

Just download this project and use it with anaconda :)

Summary of the results of the analysis

  1. For the first semester of 2016, the total sales of Airbnb was increasing fastly, but in the second semester, it reached a plateau.
  2. The analysis of the total price by day of the week showed that in the first semester the sales are evenly distributed, while in the second semester they are biased toward Monday and Tuesday.
  3. Analysis of the amount spent by a client showed that in the second amount the mean and maximum values were larger than in the first semester, however, also more spread (larger standard deviation).

Licensing

MIT License

Copyright (c) 2021 Vagner Zeizer C. Paes

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Acknowledgements

Udacity is strongly and the reviewers are highly acknowledged for this great experience of writting a Data Science Blog.

Author

  1. Vagner Zeizer Carvalho Paes