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

Question

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.

查看解析

登录即可查看完整答案

类似问题

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'])

Assume the file "data_file.csv" exists and that it contains a column with the heading "age", and you run the following code snippet: import pandas as pd data = pd.read_csv("data_file.csv") sorted_data = data.sort_values(by="age") Which one of the following statements is TRUE?

In a consumer society, many adults channel creativity into buying things

Economic stress and unpredictable times have resulted in a booming industry for self-help products

People born without creativity never can develop it

A product has a selling price of $20, a contribution margin ratio of 40% and fixed cost of $120,000. To make a profit of $30,000. The number of units that must be sold is: Type the number without $ and a comma. Eg: 20000

Which of the following statement regarding cost is correct:

更多留学生实用工具

考试浏览器助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单