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This quiz was administered in-person. It was closed-book and closed-note; students were not allowed to use the DSC 10 Reference Sheet. Students had 20 minutes to work on the quiz.

This quiz covered Lectures 8-11 of the Winter 2024 offering of DSC 10.

The DataFrame flights contains information about recent flights, with each row representing a specific flight and the following columns:

• "flight num" (str): The unique code of the flight, consisting of a two-character airline designator followed by 1 to 4 digits (e.g., "UA1989").
• "airline" (str): The airline name (e.g., "United").
• "departure" (str): The code for the airport from which the flight departs (e.g., "SAN").
• "arrival" (str): The code for the airport at which the flight arrives (e.g., "LAX").

Problem 1

Suppose the function first_two takes as input a string and returns a string with the first two characters only. For example first_two("panda") is "pa". Using this function, write an expression that evaluates to a Series containing the two-character airline designator for each flight in flights.

Problem 2

Problem 2.1

Fill in the blanks below so that grouped is a DataFrame showing how many flights on each airline departed from each airport.

    grouped = flights.groupby(___(x)___).___(y)___.get(["flight_num"])

Problem 2.2

Suppose the expression grouped.shape[0] == flights.shape[0] evaluates to True. Select all true statements below.

• No two flights in flights were on the same airline.

• No two flights in flights had the same departure and arrival airports.

• Among all flights in flights that were on the same airline, no two had the same departure airport.

• Among all flights in flights from the same departure airport, no two were on the same airline.

Problem 3

Suppose we have another DataFrame more_flights which contains the same columns as flights, but different rows. Define merged as follows.

        merged = flights.merge(more_flights, on = "airline")

Suppose that in merged, there are 108 flights where the airline is "United", and in more_flights, there are 12 flights where the airline is "United". If flights has 15 rows in total, how many of these rows are not for "United" flights? Give your answer as an integer.

Problem 4

Problem 4.1

Fill in the blanks below so that prob evaluates to the probability that a randomly selected flight from the flights DataFrame arrives at "SAN" given that it departs from "LAX".

san = flights.get("arrival") == "SAN"
lax = flights.get("departure") == "LAX"
prob = flights[san___(x)___lax].shape[0] / ___(y)___

Problem 4.2

Write an expression that evaluates to the probability that a randomly selected flight from the flights DataFrame is not on the airline "Delta".

Problem 5

Use the function defined below to answer the questions on the right.

def discount(duration, price):
    if duration > 6:
        price = price * 0.9
    if duration > 4:
        price = price * 0.95 
    elif duration > 3:
        price = price * 0.98
    else:
        price = price * 0.99 
    price = price - 5 
    return price

Problem 5.1

What is the output of discount(7, 100)?

• 100 * 0.9 * 0.95 * 0.98 - 5

• 100 * 0.9 * 0.95 - 5

• 100 * 0.9 - 5

• 100 * 0.9

Problem 5.2

Find x and y such that discount(x, y) evaluates to 97 * 0.98 - 5.

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