Transforming data into transactions

Before using any rule mining algorithm, we need to transform data from the data frame format into transactions. In this example, we demonstrate how to transform a purchase order dataset into transactions with the arules package.

Getting ready

Download the purchase_order.RData dataset from the https://github.com/ywchiu/rcookbook/raw/master/chapter9/product_by_user.RData GitHub link.

How to do it…

Perform the following steps to create transactions:

1. First, install and load the arules package:

   > install.packages("arules")
   > library(arules)
   

2. Use the load function to load purchase orders by user into an R session:

   > load("product_by_user.RData")
   

3. Last, convert the data.table (or data.frame) into transactions with the as function:

   > trans = as(product_by_user $Product, "transactions")
   > trans
   transactions in sparse format with
    32539 transactions (rows) and
    20054 items (columns)
   

How it works…

Before mining a frequent item set or association rule, it is...