Question27 import pandas as pd df=pd.DataFrame({'Salary':[50,100,75]}) Which option(s) can sort the DataFrame df (defined as the above code) by the column Salary from lowest to highest and modify df directly? Select one or more alternatives: df.sort_values(by = 'Salary') df.sort_values(by = 'Salary', ascending = True, inplace = True) df.sort_values(by = 'Salary', ascending = False, inplace = True) df.sort_values(by = 'Salary', inplace = True) ResetMaximum marks: 3 Flag question undefined多项选择题
A
df.sort_values(by = 'Salary')
B
df.sort_values(by = 'Salary', ascending = True, inplace = True)
C
df.sort_values(by = 'Salary', ascending = False, inplace = True)
D
df.sort_values(by = 'Salary', inplace = True)

Question

Question27 import pandas as pd df=pd.DataFrame({'Salary':[50,100,75]}) Which option(s) can sort the DataFrame df (defined as the above code) by the column Salary from lowest to highest and modify df directly? Select one or more alternatives: df.sort_values(by = 'Salary') df.sort_values(by = 'Salary', ascending = True, inplace = True) df.sort_values(by = 'Salary', ascending = False, inplace = True) df.sort_values(by = 'Salary', inplace = True) ResetMaximum marks: 3 Flag question undefined多项选择题

A

df.sort_values(by = 'Salary')

B

df.sort_values(by = 'Salary', ascending = True, inplace = True)

C

df.sort_values(by = 'Salary', ascending = False, inplace = True)

D

df.sort_values(by = 'Salary', inplace = True)

BlackTom AI · Accepted Answer

To determine which options sort the DataFrame df by the Salary column in ascending order and modify df in place, I’ll evaluate each choice against how pandas sort_values behaves.

Option 1: df.sort_values(by = 'Salary')
This call specifies the column to sort by but omits the inplace parameter, which defaults to inplace=False. That means it returns a new, sorted DataFrame and leaves the original df unchanged. Therefore, it does not modify df in place, so this option is not suitable for the requirement.

Option 2: df.sort_values(by = 'Salary', ascending = True, inplace = True)
Here, the sort is performed on the Salary column with ascending order explicitly requested and inplace set to True. This directly updates df to the sorted result in place, fulfilling both criteria: sorting from lowest to highest and modifying df. This option is correct.

Option 3: df.sort_values(by = 'Salary', ascending = False, inplace = True)
This option sorts by Salary in descending order (highest to lowest) because ascending is False, and it modifies df in place due to inplace = True. Since the goal is sorting from lowest to highest, this option does not meet the required direction of sorting, so it is incorrect.

Option 4: df.sort_values(by = 'Salary', inplace = True)
Omitting ascending leaves it at the default ascending=True, and with inplace = True it does modify df in place. This results in a sort from lowest to highest and changes df accordingly, so this option is also correct.

Summary: Among the provided choices, options 2 and 4 both achieve in-place sorting in ascending order by Salary, while options 1 and 3 do not meet the in-place modification or the required ascending direction. The answers align with the goal of sorting from lowest to highest and mutating df directly.