Melbourne Airbnb Analysis

Installations

• NumPy
• Pandas
• Seaborn
• Matplotlib
• Sklearn

Project Motivation

I wanted to understand the lanscape of Airbnb bookings but unfortunately were not able to find any relating to Malaysia. The closest region (which I also hope to visit soon) would be Melbourne and fortunately there is up to date open-sourced information in Inside Airbnb.

I have targetted this analysis towards Airbnb hosts.

Questions

• What is the lanscape of Airbnb listings in Melbourne?
• What factors influences the price of my stay?
• How can I improve my Airbnb listing to yield more customers?
• What are period on period trends? (YoY/MoM/DoD)

Files

• melbourne_airbnb.ipynb

Blog post

• Medium blog post link

Acknowledgements.

• Acknowledgements to Inside Airbnb, who have done an amazing job scraping and collating Airbnb data throughout the world.

References

• Airbnb - Stackeholders of Airbnb
• Towards Data Science - Using InterQuartile Range for identifying outliers
• Kaggle - Guide for using GeoPandas