Q14 I ran the code below and the df was unchanged. How can I make sure the sorting is applied to the df?

df.sort_values(['date', 'storeid'])

A: df.sort_values(['date','storeid'], inplace=True)

B: df = df.sort_values(['date','storeid'])

C: df.sort_index(['date','storeid'])

Question

Q14 I ran the code below and the df was unchanged. How can I make sure the sorting is applied to the df?

df.sort_values(['date', 'storeid'])

A: df.sort_values(['date','storeid'], inplace=True)

B: df = df.sort_values(['date','storeid'])

C: df.sort_index(['date','storeid'])

BlackTom AI · Accepted Answer

Analyzing the question, we’re asked which statements about making sorting apply to a DataFrame are correct given the code snippet.
Option 1: All (A, B, and C) are correct. This would require A, B, and C to all be valid ways to apply sorting in place. However, C uses df.sort_index(['date','storeid']), which is not how sort_index works; sort_index sorts by the index, not by a list of column values. Since C is not a valid way to sort by the specified columns, this option cannot be entirely correct.
Option 2: B and C Only. This would claim that B is correct and C is correct while A is not. We know A is a valid in-place sort, so excluding A makes this option inaccurate.
Option 3: A and c only. This asserts that A is correct and C is correct while B is not. As noted, C is incorrect because sort_index does not take a list of column names to sort by columns; it sorts by the index. Therefore this option is also incorrect.
Option 4: A and B only. This claims that both A and B are correct and C is not. A performs an in-place sort, modifying the original DataFrame, which is a valid approach. B assigns the sorted DataFrame back to df, which is also a valid approach to apply the sorting to df. Since C is invalid for sorting by the given columns, this option aligns with the correct understanding that A and B are the correct methods.
Option 5: None (A, B, and C) are correct. Given that A and B are valid, this cannot be true, so this option is false.
In summary, the reasoning shows that A correctly sorts in place, B correctly assigns the sorted result back to df, and C does not sort by the specified columns because sort_index operates on the index rather than arbitrary column lists. Therefore, the pair of valid approaches are A and B, while C is not appropriate for the described goal.

ISBA2401 - Data Analytics with Python (MW 05:45 PM, MW 7:35 PM, TTh 7:35PM) Midterm Multiple Choice (FA2025 - MW735) - Requires Respondus LockDown Browser

Q14 I ran the code below and the df was unchanged. How can I make sure the sorting is applied to the df? df.sort_values(['date', 'storeid']) A: df.sort_values(['date','storeid'], inplace=True) B: df = df.sort_values(['date','storeid']) C: df.sort_index(['date','storeid'])

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