NYC Food Ordering/Delivering Data

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NYC Food Ordering/Delivering Data

✓ Published1🌍 Public

Last edited Apr 6, 2023

Created on Jan 23, 2023

This example visualizes NYC food ordering and delivery data from Foodhub, showing raw order records including restaurant names, cuisine types, costs, ratings, preparation times, and delivery times. The visualization initially displays the dataset as formatted JSON text in a `<pre>` element. It uses D3 v7’s `csvParse` to load and parse data from a remote CSV file, converting numeric fields with unary plus operators. The code employs D3 selections with `.selectAll().join()` to bind and update the display, and manages asynchronous data loading through a state-based render cycle using `fetch`.

AI-generated description

Loading a dataset that has information on food orders/deliveries in NYC through the app Foodhub.

(Dataset from: https://www.kaggle.com/datasets/ahsan81/food-ordering-and-delivery-app-dataset)

Column Description/Data Types

order_id: unique id that is connected to each order (Ordinal)

customer_id: unique id that is connected to the customer ordering the food (Ordinal)

restaurant_name: name of the restaurant that the order is from (Categorical)

cuisine_type: type of food ordered (Categorical)

cost_of_the_order: how much the order cost (Quantitative)

day_of_the_week: either Weekend or Weekday, indicates when the order took place (Categorical)

rating: rating that customer gave on order (out of 5) (Quantitative)

food_preparation: time (in minutes) that it took the restaurant to prepare the order to be delivered (Quantitative)

delivery_time: time (in minutes) that it took for the order to be delivered to the customer (Quantitative)

MIT Licensed

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