A food aggregator company has stored the data of the different orders made by the registered customers in their online portal. They want to analyze the data to get a fair idea about the demand of different restaurants which will help them in enhancing their customer experience. The aim of this project is to answer important questions that will help the company to improve their business.
The data contains the different variables related to a food order. The detailed data dictionary is given below.
. order_id: Unique ID of the order placed
. customer_id: ID of the customer who ordered the food
. restaurant_name: Name of the restaurant
. cuisine_type: Cuisine ordered by the customer
. cost: Cost of the order
. day_of_the_week: Indicates whether the order is placed on a weekday or weekend (The weekday is from Monday to Friday and the weekend is Saturday and Sunday)
. rating: Rating given by the customer out of 5
. food_preparation_time: Time (in minutes) taken by the restaurant to prepare the food. This is calculated by taking the difference between the timestamps of the restaurant's order confirmation and the delivery person's pick-up confirmation.
. delivery_time: Time (in minutes) taken by the delivery person to deliver the food package. This is calculated by taking the difference between the timestamps of the delivery person's pick-up confirmation and drop-off information