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Creating, Loading, and Selecting Data with Pandas

Selecting Multiple Columns

When you have a larger DataFrame, you might want to select just a few columns.

For instance, let’s return to a DataFrame of orders from ShoeFly.com:

id	first_name	last_name	email	shoe_type	shoe_material	shoe_color
54791	Rebecca	Lindsay	[email protected]	clogs	faux-leather	black
53450	Emily	Joyce	[email protected]	ballet flats	faux-leather	navy
91987	Joyce	Waller	[email protected]	sandals	fabric	black
14437	Justin	Erickson	[email protected]	clogs	faux-leather	red

We might just be interested in the customer’s last_name and email. We want a DataFrame like this:

To select two or more columns from a DataFrame, we use a list of the column names. To create the DataFrame shown above, we would use:

new_df = orders[['last_name', 'email']]

*Note: *Make sure that you have a double set of brackets ([[]]), or this command won’t work!

Now, you want to compare visits to the Northern and Southern clinics.

Create a variable called clinic_north_south that contains ONLY the data from the columns clinic_north and clinic_south.

When we select multiple columns, do we get a Series or a DataFrame?

After you’ve created the variable, enter the command:

print(type(clinic_north_south))

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