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Consider the following table transaction _ id , customer _ id , timestamp,product _ category,quantity,price,numeric _ feature 1 , 1 0 1 , 2 0

Consider the following table
transaction_id,customer_id,timestamp,product_category,quantity,price,numeric_feature
1,101,2022-01-0108:30:00,Electronics,2,500,45
2,102,2022-01-0109:15:00,Clothing,1,120,30
3,103,2022-01-0210:00:00,Electronics,3,400,50
4,101,2022-01-0314:45:00,Home & Garden,1,200,20
5,104,2022-01-0411:20:00,Electronics,2,450,35
6,102,2022-01-0513:00:00,Clothing,1,100,25
7,103,2022-01-0616:30:00,Home & Garden,2,300,40
8,104,2022-01-0709:45:00,Electronics,1,550,55
9,101,2022-01-0812:15:00,Clothing,3,150,28
10,103,2022-01-0915:00:00,Clothing,1,130,32

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