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Restaurant Listings Notebook

Webscraping restaurant listings from Yelp

This project is a part of the Zero to Data Analyst Bootcamp by Jovian

Yelp is a San Fransisco, CA headquartered directory listing service. Its USP is user reviews, recommendations and ratings to find nearby restaurants, shopping, nightlife, food, entertainment, things to do and other services.

Problem Statement: In this notebook we will write python functions that will create a CSV file containing details of
restaurants that are listed for the city of New York, USA on

    Name: Name of the restaurant
    Cuisine: Type of food
    Stars: Rating based on user inputs for this restaurant
    Reviews: Number of users who rated this restaurant
    Address: Address of the restaurant
    Contact: phone number
    Website: Yelp url for the restaurant

Why is this data important?

Restaurant listing services are extremely helpful whether you are a foodie looking to explore world cuisine, a travellor in the city looking for the comforts of home or celebrating an occasion with your friends and family.

But did you know?

  • The restuarant business in the US recorded sales of \863billionin2019andemploys12.5millionpeople?(863 billion in 2019 and employs 12.5 million people? (\\659 billion in 2020 due to the pandemic) This is about 4% of the US GDP.

  • 1 in 10 Americans are employed in the restaurant industry. Nearly one in three Americans had their first job at a restaurant

  • Consumers spent 49% of their food budget in restaurants before the pandemic in 2019.

Who will find this data useful?

1) Diners/Customers: Seek the best restaurant in an area or offering a cuisine based on user reviews, compare prices

2) Restaurants: Use the data for various kinds of decision making.

  • customer profiling, site selection, forecasting, customer relationship management, menu design
  • improve the brand, evaluate whether to open new branches, offer franchises
  • understand changing customer behaviour post pandemic
  • upgrade to newer technology to improve social engagement, integration of tech into delivery service

3) Startups in the restaurant space: Research trends to select suitable location, cuisine, menu design etc.

4) Investors:

  • Identify the upstream and downstream business uch as restaurant aggregation to food delivery.e.g., zomato, swiggy
  • Evaluate brand and social impact of the business, analyse competition
  • New investing opportunites based on trends

How to run the code

Anushree6 months ago