Table of Contents

1. Installations
2. Motivations
3. File Desriptions
4. Licensing and Acknowledgements
5. Results

Installations

This project was created and run using Python version 3.0.

Plugins and imports used were: Pandas, MatplotLib, Folium, Folium Plugins

Motivations

I have never been to Boston and was curious to see how certain neighbourhoods are reflected based on their reviews, price of rental and criminal incidents in the area.

Basically I wanted to break this down by looking at how:

1. reviews of current neighbourhoods and Airbnb accomodation were reflected differently in particular areas.
2. Cost and availability of accomodation over the seasons
3. crime comparison and how criminal activity reflects on the Airbnb accomodation.

File Desriptions

Files:

• .Pynb File contianing research and findings
• readme document
• crime, listings, reviews, calendars .csv files with raw data from Airbnb and Boston Police Dep.

Licensing and Acknowledgements

I would like to thank Udacity for their ideas and support for this project.

I would like to acknowledge the following for their licensing and open data:

1. Area Codes for Boston https://en.wikipedia.org/wiki/List_of_Massachusetts_area_codes
2. Police codes per area; https://bpdnews.com/districts
3. Kaggle Police Crimes https://www.kaggle.com/ankkur13/boston-crime-data/version/3

• AirBnb Data; https://www.kaggle.com/airbnb/boston

Results

Results and findings can be found here.