Question21 Which of the following correctly describes a Series in Python using the Pandas library? Select one alternative: A table with rows and columns A fixed-size 2D array A 3D matrix holder A one-dimensional labeled array ResetMaximum marks: 2 Flag question undefined单项选择题
A
A table with rows and columns
B
A fixed-size 2D array
C
A 3D matrix holder
D
A one-dimensional labeled array

Question

Question21 Which of the following correctly describes a Series in Python using the Pandas library? Select one alternative: A table with rows and columns A fixed-size 2D array A 3D matrix holder A one-dimensional labeled array ResetMaximum marks: 2 Flag question undefined单项选择题

A

A table with rows and columns

B

A fixed-size 2D array

C

A 3D matrix holder

D

A one-dimensional labeled array

BlackTom AI · Accepted Answer

Let’s break down what a Pandas Series is and evaluate each option against that concept.
Option 1: 'A table with rows and columns' — this describes a DataFrame, which is a 2D labeled data structure with rows and columns. A Series is not a table with rows and columns, so this option misidentifies the data structure.
Option 2: 'A fixed-size 2D array' — a 2D fixed-size array would imply a matrix-like structure (and typically corresponds to something like a NumPy 2D array). Series in Pandas are not 2D nor fixed-size 2D arrays; they are 1D. This makes the option incorrect.
Option 3: 'A 3D matrix holder' — Pandas Series is not a 3D container. It holds a single 1D array of values with an index. A 3D structure would be more akin to a 3D array or a Panel (in older Pandas) rather than a Series. Therefore, this is inaccurate.
Option 4: 'A one-dimensional labeled array' — this matches the canonical definition of a Pandas Series: it is a one-dimensional array-like object with an associated index that provides labels for each element. The labeling (index) is a key feature that differentiates it from a plain NumPy array, and the one-dimensional aspect distinguishes it from DataFrames.
In summary, the correct characterization is that a Series is a one-dimensional labeled array, whereas the other options describe higher-dimensional or table-like structures that are not Series. The nuance rests on dimensionality (1D) and labeling (indexed) aspects that set Series apart from DataFrames, NumPy arrays, and 3D containers.

Question21 Which of the following correctly describes a Series in Python using the Pandas library? Select one alternative: A table with rows and columns A fixed-size 2D array A 3D matrix holder A one-dimensional labeled array ResetMaximum marks: 2 Flag question undefined单项选择题

类似问题

What type of data structure is a Pandas Series exactly?

What type of data structure is a Pandas Series?

Q11 .apply operation will perform more efficiently when applied to which of the following pandas data structures?

True or False? While Series.head() will return us the first five rows of the Series by default, Series.nlargest() will return us the five rows corresponding to the largest values in the Series by default.

Which of the following can you use to obtain the maximum value in a Pandas Series, s? Assume there are no missing values in s.

Question18 What is the structure of ‘ser3‘ after executing the following Pandas code: Select one alternative: A 5.0B 7.0C 9.0 AD 5BC 7CB 9 A 1.0B 8.0C 8.0D 4.0 A NaNB 8.0C 8.0D NaN None of the above ResetMaximum marks: 3 Flag question undefined

Question15 Which of the following is a key feature of a Pandas Series? Select one alternative: (a) Multidimensional structure (b) Labeled index (c) Mixed types in a single column (d) SQL integration ResetMaximum marks: 3 Flag question undefined

Question7 Pandas automatically aligns Series by index when performing arithmetic. Select one alternative: True False ResetMaximum marks: 2 Flag question undefined

更多留学生实用工具

智能学习助手

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