The main goal of this project is to answer questions related to becoming an Airbnb Superhost. Seattle's and Boston's Airbnb open datasets were used for this purpose, both datasets are available in kaggle
-pandas
-numpy
-matplotlib
-seaborn
Airbnb analysis.ipynb: The main notebook in which the analysis was performed appying the CRISP-DM methodology
boston: Directory with the Boston's Airbnb datasets
seattle: Directory with Seattle's Airbnb datasets
Throughout this article, we answered 3 different questions:
-How correlated is the Superhost status with the number of properties listed on Airbnb?
We determined that there was a negative correlation between the Superhost status and the number of properties listed on Airbnb.
-What are the most common property types managed by Superhosts?
Apartments and houses are the most common property types owned by Superhosts.
How long does a Superhost take to answer guests/leads messages through the platform?
Good customer service is a standard among Superhosts since most of them are answering messages inside the platform within one hour.
The main results of this analysis can be read in this medium post