An-exploratory-data-analysis-of-AIRBNB-in-Asheville

EDA of AIRBNB in Asheville

Overview -

The goal of the project was to perform an exploratory analysis of Airbnb's in Asheville to find,analyze trends to gain insights in to questions like -

How do prices of listings vary by location? What localities in Asheville are rated highly by guests? What makes a host Super host? Which features of a listing are highly rated by guests?

Dataset Source -

The dataset was sourced http://insideairbnb.com/get-the-data.html

Analysis/Visualizations -

The following are the analysis done to answer the above questions:

1. Price analysis - Visualizations to analyze why and how prices vary by locations. Seasonality in prices(By months/ By days)

2. Growth analysis - Visualizations to to analyze the growth of Airbnb's in Asheville since it's inception.

3. Superhost analysis - To find out what features make a host in to superhost.

4. Location analysis - Visually analyze the concentration of airbnb rentals in map to find out which rentals are rated best by guests.

5. Review analysis - Analyze the review by guests to find out which features are important to get a good review/rating from a guest using Machine Learning. Generate a word cloud to view the positive and negative reviews.

Deployment -

The app was deployed using Heroku and FLASK.