Project Overview

This project utilized data “The Instacart Online Grocery Shopping Dataset 2017” or the instacart dataset from package p8105.datasets to explore the trends of offerings and purchases in online grocery shopping. The project utilized R version 4.3.1 and R packages dplyr, ggplot2, tidyverse, and p8105.datasets.

The instacart dataset has 1384617 observations and 15 variables, including:

• order_id: order identifier, class integer.
• product_id: product identifier, class integer.
• add_to_cart_order: order in which each product was added to cart, class integer.
• reordered: 1 if this prodcut has been ordered by this user in the past, 0 otherwise, class integer.
• user_id: customer identifier, class integer.
• eval_set: which evaluation set this order belongs in (Note that the data for use in this class is exclusively from the “train” eval_set), class character.
• order_number: the order sequence number for this user (1=first, n=nth), class integer.
• order_dow: the day of the week on which the order was placed, class integer.
• order_hour_of_day: the hour of the day on which the order was placed, class integer.
• days_since_prior_order: days since the last order, capped at 30, NA if order_number=1, class integer.
• product_name: name of the product, class character.
• aisle_id: aisle identifier, class integer.
• department_id: department identifier, class integer.
• aisle: the name of the aisle, class character.
• department: the name of the department, class character.

Visualizations and EDA