This is my first Data Science Nanodegree program project
- Installation.
- Project motivation.
- Description of the file.
- Results of the project.
- Licensing, Authors, Acknowledgements.
You need to install the following libraries,
- Numpy
- Pandas
- Seaborn
- matplotlib
- kepler-gl
The first four libraries are already installed in Anaconda distribution of Python. The installation guide for kepler-gl is given here
My primary motivations for studying the Airbnb Boston dataset are given below,
- What areas of Boston have the most and the least number of listings ?
- What areas of Boston are the costliest areas to stay ?
- What sets apart a super host from a normal host ?
- How the number of booked listing varies in the time of the year ?
Final_Airbnb_Boston_Project.ipynb : This jupyter notebook file contains the code from which I have analyzed and produced the results, which are discussed in the Blogpost
Readme.md : description of the repository
The files listings.csv,calendar.csv and reviews.csv are required Airbnb Boston datasets for running the Final_Airbnb_Boston_Project.ipynb file
The results of the project are discussed here.
Must give credit to Airbnb for the data. You can find the Licensing for the data and other descriptive information at the Kaggle link available here.