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Working with Multiple DataFrames
Inner Merge I

Suppose we have the following three tables that describe our eCommerce business:

  • orders — a table with information on each transaction:
order_idcustomer_idproduct_idquantitytimestamp
12312017-01-01
22232017-01-01
33112017-01-01
43222017-02-01
53332017-02-01
61422017-03-01
71112017-02-02
81412017-02-02

  • products — a table with product IDs, descriptions, and prices:
product_iddescriptionprice
1thing-a-ma-jig5
2whatcha-ma-call-it10
3doo-hickey7
4gizmo3

  • customers — a table with customer names and contact information:
customer_idcustomer_nameaddressphone_number
1John Smith123 Main St.212-123-4567
2Jane Doe456 Park Ave.949-867-5309
3Joe Schmo798 Broadway112-358-1321

If we just look at the orders table, we can’t really tell what’s happened in each order. However, if we refer to the other tables, we can get a more complete picture.

Let’s examine the order with an order_id of 1. It was purchased by Customer 2. To find out the customer’s name, we look at the customers table and look for the item with a customer_id value of 2. We can see that Customer 2’s name is Jane Doe and that she lives at 456 Park Ave.

Doing this kind of matching is called merging two DataFrames.

Instructions

1.

Examine the orders and products tables.

What is the description of the product that was ordered in Order 3?

Give your answer as a string assigned to the variable order_3_description.

2.

Examine the orders and customers tables.

What is the phone_number of the customer in Order 5?

Give your answer as a string assigned to the variable order_5_phone_number.

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