https://github.com/foxriver76/airbnb_analysis
Analysis of AirBnb data of Boston and Seattle
https://github.com/foxriver76/airbnb_analysis
airbnb jupyter udacity
Last synced: 7 months ago
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Analysis of AirBnb data of Boston and Seattle
- Host: GitHub
- URL: https://github.com/foxriver76/airbnb_analysis
- Owner: foxriver76
- Created: 2022-10-12T11:54:27.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-10-18T09:18:55.000Z (over 3 years ago)
- Last Synced: 2025-01-04T17:46:01.980Z (over 1 year ago)
- Topics: airbnb, jupyter, udacity
- Language: Jupyter Notebook
- Homepage:
- Size: 35 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# AirBnB Analysis
### Table of Contents
1. [Installation](#installation)
2. [Project Motivation](#motivation)
3. [File Descriptions](#files)
4. [Results](#results)
5. [Licensing, Authors, and Acknowledgements](#licensing)
There should be no necessary libraries to run the code here beyond the Anaconda distribution of Python. The code should run with no issues using Python versions 3.*.
For this project, I was interestested in using the AirBnb data of Boston and Seattle to better understand:
1. At which time are the AirBnbs most busy?
2. Is the price higher in busy months?
3. Does a more expensive AirBnb lead to better reviews?
Datasets are available in this repository in the `data` folder.
The `analyze` notebook is, the only file needed. The data is read inside the notebook and analysis of all 3 questions is done in there.
## Results
You can find the results on [IoT Blog](https://iot-blog.net/2022/10/18/get-the-most-out-of-your-money-on-airbnb/)
## Licensing, Authors, Acknowledgements
The dataset is obtained from Kaggle [Boston](https://www.kaggle.com/datasets/airbnb/boston) and [Seattle](https://www.kaggle.com/datasets/airbnb/seattle). Thanks to AirBnb for providing the data.