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DSBDA Mini-Project : Zomato-Restaurant-Rating-Prediction

Team Members:

     PIYUSH BRAHANPURKAR TI06
     ATHARVA DHAYAGUDE TI14
     ANAY DONGRE TI15 
     ANISHA KANGO TI27 
    

In this project we have performed exploratory data analysis on given dataset. And created a model that can predict the rating of the restaurant.

Logo

download the dataset from here

Main Objective:

The main agenda of this project is:

  • Perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset.

  • Build an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features.

Feature description :

  1. url contains the url of the restaurant in the zomato website

  2. address contains the address of the restaurant in Bengaluru

  3. name contains the name of the restaurant

  4. online_order whether online ordering is available in the restaurant or not

  5. book_table table book option available or not

  6. rate contains the overall rating of the restaurant out of 5

  7. votes contains total number of rating for the restaurant as of the above mentioned date

  8. phone contains the phone number of the restaurant

  9. location contains the neighborhood in which the restaurant is located

  10. rest_type restaurant type

  11. dish_liked dishes people liked in the restaurant

  12. cuisines food styles, separated by comma

  13. approx_cost(for two people) contains the approximate cost of meal for two people

  14. reviews_list list of tuples containing reviews for the restaurant, each tuple

  15. menu_item contains list of menus available in the restaurant

  16. listed_in(type) type of meal

  17. listed_in(city) contains the neighborhood in which the restaurant is listed

Conclusion :

  • From the analysis, 'Onesta', 'Empire Restaurant' & 'KFC' are the most famous restaurants in bangalore.

  • Most Restaurants offer options for online order and delivery.

  • Most restaurants don't offer table booking.

  • From the analysis, most of the ratings are within 3.5 and 4.5.

  • From the analysis. we can see that most of the restaurants located in 'Koramangala 5th Block', 'BTM' & 'Indiranagar'.Then least restaurants are located 'KR Puram', 'Kanakapura', 'Magadi Road'.

  • 'Casual Dining', 'Quick Bites', 'Cafe', 'Dessert Parlor' are the most common types of restaurant.And 'Food Court', 'Casual Dining', 'Dhaba' are the least common.

  • From the analysis, pasta & Pizza most famous food in bangalore restaurants.

  • From the analysis, we can see that North Indian Cuisines are most famous in bangalore restaurants.

  • Two main service types are Delivery and Dine-out.

  • From the analysis, we can see that 'Onesta', 'Truffles' & 'Empire Restaurant' are highly voted restaurants.

  • For the modeling part, i used LinearRegression, DecisionTree Regressor, RandomForest Regressor , Supprotvector Regressor & ExtraTree Regressor. From all these models ExtraTree Regressor perform well compared to the other models.So i selected ExtraTree Regressor for model creation.