A table with the results for 10 men in a 100-meter sprint including their place, name, country, and time, including:

Question

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. What is displayed by len(race)?

(1 point)
Responses

9
9

4
4

10
10

3

Answer 1

The len(race) function in a programming context typically returns the number of elements in the race object, which in this case seems to represent the results of a race.

In the table provided, there are 10 entries (including the disqualified participant, Maurice Greene). However, if we are considering the number of competitors who actually completed the race (those who finished without disqualification), then there would be 9 valid entries.

Therefore, if race is defined to include all entries (including disqualified) and we're counting the total number of entries, len(race) would return 10.

If it's counting only those who finished the race, then len(race) would return 9.

Thus, the potential answers would be:

• 9 (if counting only those who finished)
• 10 (if counting total entries).

Based on the question choices, the answer displayed by len(race) should be 10.

Answer 2

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()

country.value_counts()
country.value_counts()

race["country"].info()
race["country"].info()

race.value_counts()

Answer 3

To display the number of runners from each country based on the provided context, you would typically use the value_counts() method on the "country" column of the DataFrame (assuming race is a DataFrame).

The correct options to achieve this would be:

1. race["country"].value_counts()

The second option you provided, race["country"].value_counts(), is a repeat and also correct, but it essentially represents the same function.

Other options such as country.value_counts(), race["country"].info(), and race.value_counts() are not appropriate for counting the number of runners from each country.

So the correct responses are:

• race["country"].value_counts()

Since both race["country"].value_counts() and race["country"].value_counts() are the same, either would be fine to select as the answer. If only one can be chosen, go with the first one.