Project Overview:

The goal of the project is to use python to get data from Yelp API on Ann Arbor's restaurants information and store the data into database for query/management. There will also be an interactive map built by Tableau and HTML for users to interact with.

Data Source: Yelp

Yelp is an application that provides restaurants' information/reviews. It is supported by multiple languages and is widely used in many countries such as the U.S. and Japan. After users pick a location(and other possible criteria), Yelp will return satisfying restaurants search results.

Yelp @ Ann Arbor: https://www.yelp.com/search?find_desc=&find_loc=Ann+Arbor%2C+MI&ns=1

Tool to get the data: Yelp Fusion API, which uses OAuth 2.0 as Authentication.

• API documentation homepage: https://www.yelp.com/developers/documentation/v3/get_started

• Search API documentation: https://www.yelp.com/developers/documentation/v3/business_search

• Reviews API documentation: https://www.yelp.com/developers/documentation/v3/business_reviews

IMPORTANT UPDATES: From December 8, 2017, Yelp simplifies the API process and change from using OAuth 2.0 to API key. However, this code will still work until Yelp completely stops using OAuth 2.0 starting March 1, 2018.

Outcome:

We will get information on 40 best restaurants in Ann Arbor ordered by some sorting function by Yelp(taking both review counts and ratings into account), plus the corresponding 3 review extracts for each restaurant we retrieved.

CSV files

There are two csv files that contain the information we have gained. Each csv's column names are provided below.

• restaurants.csv (saves restaurant basic information on name, category, rating, price level and location)

  • restaurant_id: the registered id of the restaurant

  • restaurant_name: the name of the restaurant

  • category: which categories the restaurant belongs to, eg. Coffee & Tea. can be multiple categories. stored in a list.

  • price_leve: range from $ to $$$$

  • ratings: range from 1 to 5, on a 1/2 interval

  • review_counts: total number of reviews

  • state: the location of the restauant

  • city

  • street_address

  • latitude

  • longitude

--> Search API documentation: https://www.yelp.com/developers/documentation/v3/business_search

• reviews.csv

  • restaurant_id: the registered id of the restaurant

  • reiview_1: one review of the customer

  • review_2: one review of the customer

  • review_3: one review of the customer

--> Reviews API documentation: https://www.yelp.com/developers/documentation/v3/business_reviews

Note: This file only stores the three reviews extract returned by the API endpoints. At this time, the API does not return restaurants without any reviews.

Database:

There will be three tables stored in the database:

• Table1: Restaurants

  • id: PRIMARY KEY

  • restaurant_name

  • price_level

  • ratings

  • reviews_count

  • logitude

  • latitude

  • category id: FOREIGN KEY points to Table2 Category(id)

  • review id: FOREIGN KEY points to Table3 Reviews(id)

• Table2: PriceLevel

  • id: PRIMARY KEY

  • price_level

• Table3: Reivews

  • id: PRIMARY KEY

  • review_1

  • review_2

  • review_3

Visualization: An Interactive Map