Seattle-Airbnb-Market-Analysis

Analysis of Kaggle's Seattle Airbnb Dataset for Udacity's Data Scientist Nanodegree (Project 1)

Using Kaggle's Seattle Airbnb Open Dataset with the aid of Python and Power BI, this project seeks to answer the following questions:

• What is the average listing Price based on Location/Seattle Neighborhood?
• What is the occupancy pattern based on Weekday and season?
• How do hosts with high performance compare to hosts with low performance? Based on this, how can hosts with low performance increase their performance ratings?
• What are some of the factors that determine price?

Requirements

You need to have xgboost, scikit learn alongside it's dependencies and standard anaconda packages to reproduce this analysis. Visualization was created using Microsoft's Power BI Software.

Power BI Report

The Power BI report can be found here

Medium Post

A detailed post explaining the results of the analysis can be found here

License

The contents of this repository are covered under the MIT License