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Modifying DataFrames

Sometimes, we want to add a column to an existing DataFrame. We might want to add new information or perform a calculation based on the data that we already have.

One way that we can add a new column is by giving a list of the same length as the existing DataFrame.

Suppose we own a hardware store called The Handy Woman and have a DataFrame containing inventory information:

Product ID Product Description Cost to Manufacture Price
1 3 inch screw 0.50 0.75
2 2 inch nail 0.10 0.25
3 hammer 3.00 5.50
4 screwdriver 2.50 3.00

It looks like the actual quantity of each product in our warehouse is missing!

Let’s use the following code to add that information to our DataFrame.

``df['Quantity'] = [100, 150, 50, 35]``

Our new DataFrame looks like this:

Product ID Product Description Cost to Manufacture Price Quantity
1 3 inch screw 0.50 0.75 100
2 2 inch nail 0.10 0.25 150
3 hammer 3.00 5.50 50
4 screwdriver 2.50 3.00 35

### Instructions

1.

The DataFrame `df` contains information on products sold at a hardware store. Add a column to `df` called `'Sold in Bulk?'`, which indicates if the product is sold in bulk or individually. The final table should look like this:

Product ID Product Description Cost to Manufacture Price Sold in Bulk?
1 3 inch screw 0.50 0.75 Yes
2 2 inch nail 0.10 0.25 Yes
3 hammer 3.00 5.50 No
4 screwdriver 2.50 3.00 No