https://github.com/lucasbotang/seattle_airbnb
Data analysis for Airbnb in Seattle
https://github.com/lucasbotang/seattle_airbnb
airbnb data-science python
Last synced: 3 months ago
JSON representation
Data analysis for Airbnb in Seattle
- Host: GitHub
- URL: https://github.com/lucasbotang/seattle_airbnb
- Owner: LucasBoTang
- License: mit
- Created: 2019-02-02T21:40:31.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-02-16T10:32:26.000Z (over 7 years ago)
- Last Synced: 2026-01-03T21:14:32.613Z (6 months ago)
- Topics: airbnb, data-science, python
- Language: Jupyter Notebook
- Homepage:
- Size: 36.9 MB
- Stars: 1
- Watchers: 0
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Data Scientist Nanodegree
# Write A Data Science Blog Post
## Project 4: Seattle Airbnb
### Table of Contents
1. [Installation](#Installation)
2. [Project Motivation](#Project-Motivation)
3. [Data](#Data)
4. [File Descriptions](#File-Descriptions)
5. [Result](#Result)
6. [Blog](#Blog)
### Installation
This project requires **Python 3.x** and the following Python libraries installed:
- [SciPy](https://www.scipy.org/)
- [NumPy](http://www.numpy.org/)
- [Pandas](http://pandas.pydata.org/)
- [matplotlib](http://matplotlib.org/)
- [seaborn](https://seaborn.pydata.org/)
- [scikit-learn](http://scikit-learn.org/stable/)
You will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)
We recommend students install [Anaconda](https://www.continuum.io/downloads), a pre-packaged Python distribution that contains all of the necessary libraries and software for this project.
### Project Motivation
> For this project, you will pick a dataset. Inspired by Robert, there are a few public datasets from Airbnb available below, but you may also choose a dataset similar to what was used in the lessons, or an entirely different dataset. Using your dataset, you will choose 3 questions you aspire to answer from the data.
I chose Airbnb data in Seattle, and have the following three questions:
- What is the seasonal pattern of Airbnb in Seattle?
- What kinds of Airbnb homes are popular?
- What are the most influential features about the rental price?
### Data
The data about Airbnb in Seattle can be downloaded from **Kaggle**:
[Seattle Airbnb Open Data](https://www.kaggle.com/airbnb/seattle/data)
### File Descriptions
Jupyter Notebook ([seattle_airbnb.ipynb](https://github.com/LucasBoTang/Project_Seattle_Airbnb/blob/master/seattle_airbnb.ipynb)) works related to the above questions.
### Result
- Because of the weather, spring and summer are the busy season with higher rental price. But there still remains a question, why dose January have the highest occupancy rate?
- Airbnb homes which have entertainment nearby, a soon response from host or flexible cancellation policy are more popular.
- About rental price, the number of bedrooms and bathrooms, neighborhood and type of properties play important roles.
### Blog
[What Seattle Airbnb Data Can Tell Us](https://medium.com/@lucastang1994/what-seattle-airbnb-data-can-tell-us-263fbff8581a)