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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 5-7 of the Winter 2024 offering
of DSC 10.
Note (groupby / pandas 2.0): Pandas 2.0+ no longer
silently drops columns that can’t be aggregated after a
groupby, so code written for older pandas may behave
differently or raise errors. In these practice materials we use
.get() to select the column(s) we want after
.groupby(...).mean() (or other aggregations) so that our
solutions run on current pandas. On real exams you will not be penalized
for omitting .get() when the old behavior would have
produced the same answer.
The laptops DataFrame contains information on various
factors that influence the pricing of laptops. Each row represents a
laptop, and the columns are:
"Mfr" (str): the company that manufactures the laptop,
like “Apple” or “Dell”."Model" (str): the model name of the laptop, such as
“MacBook Pro”."OS" (str): the operating system, such as “macOS” or
“Windows 11”."Screen Size" (float): the diagonal length of the
screen, in inches."Price" (float): the price of the laptop, in
dollars.We’d like to visualize the distribution of the "Mfr"
column in the laptops DataFrame. Fill in the blanks so that
the code below draws an appropriate plot.
laptops.groupby(__(a)__).__(b)__.get([__(c)__]).plot(kind=__(d)__)Answer:
Answer (a): "Mfr"
The average score on this problem was 92%.
Answer (b): count()
The average score on this problem was 82%.
Answer (c): "Model", "OS",
"Screen Size", or "Price"
The average score on this problem was 56%.
Answer (d): "bar" or
"barh"
The average score on this problem was 68%.
Fill in the blanks so that rotten_apple evaluates to the
number of laptops manufactured by "Apple" that are priced
below the median price of all laptops.
x = __(a)__
y = __(b)__
rotten_apple = laptops[x __(c)__ y].__(d)__Note: (a) and (b) are interchangeable
Answer (a):
laptops.get("Mfr") == "Apple"
The average score on this problem was 71%.
Answer (b):
laptops.get("Price") < laptops.get("Price").median()
The average score on this problem was 71%.
Answer (c): &
The average score on this problem was 43%.
Answer (d): shape[0]
The average score on this problem was 43%.
Select all the true statements below.
When you set the index of a DataFrame, the specified column becomes the index, and the old index becomes a column.
After grouping a DataFrame, the resulting number of rows is less than or equal to the original number of rows.
The area of a density histogram is always equal to 1.
A scatter plot has one numerical axis and one categorical axis.
The height of the tallest bar in a density histogram is always less than 1.
Answer: Option 2 and Option 3
The average score on this problem was 84%.
A density histogram of "Screen Size" is shown below.
What percentage of computer models have a
"Screen Size" of at least 16 inches but less than 18
inches? Give your answer as an integer rounded to the nearest
multiple of 5.
Answer 35%
The average score on this problem was 72%.
Using groupby, write an expression that
evaluates to the average price of laptops with the "macOS"
operating system.
Answer:
laptops.groupby("OS").mean().get("Price").loc["macOS"]
The average score on this problem was 72%.
Without using groupby, write an
expression that evaluates to the average price of laptops with the
"macOS" operating system (the same quantity as above).
Answer:
laptops[laptops.get("OS") == "macOS"].get("Price").mean()
The average score on this problem was 71%.