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Exploring NYC Food Ordering/Delivering Data

✓ Published4🌍 Public
Jjjlaber
Last edited Feb 13, 2023
Created on Jan 30, 2023

This visualization explores NYC food ordering and delivery patterns from a Foodhub dataset, initially showing the full data as a JSON preformatted block. The pie chart displays the distribution of orders by cuisine type, with each slice labeled and colored using a categorical color scale. Built with D3 v7, it uses `d3.pie` to compute arc angles and `d3.arc` to generate the pie paths, alongside `flatRollup` to aggregate order counts from the CSV data fetched from a GitHub gist.

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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