Writing Procedures to Process Datasets Quick Check
2 of 52 of 5 Items
Question
Use the image to answer the question.
A table with the results for 10 men in a 100-meter sprint including their place, name, country, and time, including:
1 Kim Collins SKN 10.01
2 Leonard Scott USA 10.10
3 Michael Frater JAM 10.11
4 Jason Gardener UK 10.12
5 Marlon Devonish UK 10.13
6 Darrel Brown TRI 10.14
7 Marc Burns TRI 10.15
8 Ainsley Waugh JAM 10.31
9 Daniel Plummer UK 10.46
DQ Maurice Greene USA DQ
Source: Oxford Designers & Illustrators Ltd. Pearson Education Ltd
Consider the relation race. Which code would display the number of runners from each country?
(1 point)
Responses
race["country"].value_counts()
race["country"].value_counts()
race["country"].info()
race["country"].info()
race.value_counts()
race.value_counts()
country.value_counts()
country.value_counts()
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race["country"].value_counts()
To answer the question, you can use the code `race["country"].value_counts()`. This code will display the number of runners from each country by counting the occurrences of each country in the "country" column of the "race" dataset.
Here is an explanation of the code step by step:
1. Start with `race["country"]`: This portion of the code accesses the "country" column of the "race" dataset.
2. Use the `value_counts()` function: This function counts the occurrences of each unique value in the selected column.
3. The final code is `race["country"].value_counts()`, which combines the dataset and the function to display the desired information.
Therefore, using this code will provide you with the number of runners from each country in the "race" dataset.
The correct code to display the number of runners from each country in the 'race' relation is:
race["country"].value_counts()