Global Zomato Dataset

Overview of the Foody Dataset Everyone has trouble picking their favourite dish when you're out of your town here we have come up with a food delivery app dataset that can help you find your mouth-watering dishes within your pocket. The Zomato dataset provides restaurant information, including location, cuisines, price, ratings, and more. It enables analysis of factors affecting popularity, such as cuisine type, booking, and delivery, facilitating personalised restaurant recommendations and insights into the food delivery industry.

Problem Statements: To develop a restaurant recommendation system using the dataset to suggest personalized dining options based on user preferences, location, and restaurant attributes, enhancing the dining experience.

Columns

Here's a description of the columns in your dataset:

Restaurant ID: A unique identifier for each restaurant in the dataset. Restaurant Name: The name of the restaurant. City: The city where the restaurant is located. Address: The specific address of the restaurant. Locality: The locality or neighbourhood where the restaurant is situated. Longitude: The longitude coordinate of the restaurant's location. Latitude: The latitude coordinate of the restaurant's location. Cuisines: The type of cuisine offered by the restaurant. eg: Japanese, Thai, Chinese, Mughlai, etc. Average Cost for two: The average cost for a meal for two people at the restaurant. Currency: The currency in which the average cost is denoted. Has Table booking: Indicates whether the restaurant accepts table bookings (Yes/No). Has Online delivery: Indicates whether the restaurant provides online food delivery services (Yes/No). Is delivering now: Indicates whether the restaurant is currently delivering food (Yes/No). Price range: The price range category of the restaurant from 1 to 4. One being the less price and 4 being the high price. Aggregate rating: The overall rating of the restaurant based on user reviews. Rating colour: The colour representation of the rating (e.g., Dark green, Green, Yellow, orange, red, and white). Rating text: The text representation of the rating (e.g., Excellent, Very good, Good, Average, poor, and Not rated ). Votes: The total number of user votes or reviews received by the restaurant. Questions for solving:

Can the location (city or locality) of a restaurant influence its average cost for two people? Is there a relationship between the type of cuisine offered by a restaurant and its aggregate rating? How does the average cost for two people at a restaurant correlate with its aggregate rating? Does the presence of table booking and online delivery options impact a restaurant's aggregate rating? How does the number of votes/reviews received by a restaurant relate to its aggregate rating and popularity? Hoping that you would find insightful predictions for your text-long trip.

Happy Learning!!!!

Don't forget to Upvote my food lovers… Kindly, upvote if you find the dataset interesting. Thank you.

CC0 Original Data Source: Global Zomato Dataset