The goal of this analysis is to understand the types of businesses that use Yelp and the qualities of those that perform well. Another objective is to understand the types of end users on Yelp and how they interact with the platform, such as leaving tips for restaurants.

This project uses data obtained from Kaggle, courtesy of Yelp, and can be downloaded here: https://www.kaggle.com/yelp-dataset/yelp-dataset/data

It includes information on 174,000 businesses globally and spans from business attributes to checkins and tips. Exploratory data analysis is conducted to get an overview of the types of businesses using Yelp, suggest improvements for particular restaurants, and understand how people are using Yelp to interact with businesses.

The 'Business' dataset contains business ID, address, number of stars, number of reviews, and other business-specific fields for each business. The 'Business Attributes' dataset contains common features and offerings of each business, such as parking availability, dogs allowed, wifi, and credit card acceptance. The 'Checkins' dataset contains the business, day, and hour associated with each Yelp user checkin. The 'Tips' dataset contains the tip date, text, Yelp user ID, number of likes, and business it was left for.