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Software ==>	Python (34 exercises)
Topic ==>	Overview of NUMPY (2 exercises)
Level ==>	Relatively easy
Subject ==>	Python training

Create a NumPy array of the Tokyo Olympics medal table, then slice and sum it

This exercise is provided to allow potential course delegates to choose the correct Wise Owl Microsoft training course, and may not be reproduced in whole or in part in any format without the prior written consent of Wise Owl.

Total medals won by the top 5 countries at the Tokyo 2021 Olympics are shown below:

Medal table Tokyo 2021

Go Great Britain!

Import the numpy module, and create a NumPy array to hold this information (including the country number) using the np.array command:

# create a table to hold the medals table

medal_table = np.array(

[

[1,39,41,33],

[2,38,32,18],

[3,27,14,17],

[4,22,21,22],

[5,20,28,23]

]

)

Here's what this should look like if you print it out:

NumPy array of medals

The array should show the gold, silver and bronze medal count in columns (there's no need to store the total medal count - we can calculate that).

Use slicing to create (and then print) another array holding all of the rows from the first one, but excluding the first column giving the country number:

Excluding countries

The same information but omitting the country number.

Sum the array along the second axis to return the total number of medals won by each country:

Total number of medals won

Japan won more gold medals than the UK and the ROC, but less overall medals.

Close your program down!

You can unzip this file to see the answers to this exercise, although please remember this is for your personal use only.

You can find other training resources for the subject of this exercise here:

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