CUET-UG SERIES Computer-science
Data Handling Using Pandas
4 previous year questions.
Volume: 4 Ques
Yield: Medium
High-Yield Trend
2
2025 2
2023 Chapter Questions 4 MCQs
01
PYQ 2023
easy
computer-science ID: cuet-ug-
Temperature, Rainfall, and Humidity Data for 5 States
Using the above data frame answer the questions:
| State | Avg Temp (°C) | Rainfall (in cm) | Humidity |
|---|---|---|---|
| Assam | 20 | 150 | 10.6 |
| Delhi | 30 | 70 | 7.5 |
| Kerala | 20 | 120 | 10.9 |
| Rajasthan | 35 | 50 | 5.6 |
| Telangana | 28 | 90 | 8.7 |
Using the above data frame answer the questions:
02
PYQ 2023
medium
computer-science ID: cuet-ug-
Match List I with List II
| LIST I | LIST II |
|---|---|
| A. DataFrame.std() | IV. Standard Deviation |
| B. DataFrame.describe() | III. Descriptive statistical values |
| C. DataFrame.var() | I. Variance |
| D. DataFrame.mode() | II. Value that appears most |
1
A-IV, B-III, C-I, D-II
2
A-III, B-IV, C-II, D-I
3
A-IV, B-I, C-II, D-III
4
A-I, B-II, C-IV, D-III
\textbf{Correct Answer:} (1) A-IV, B-III, C-I, D-II
\textbf{Correct Answer:} (1) A-IV, B-III, C-I, D-II
03
PYQ 2025
medium
computer-science ID: cuet-ug-
Arrange the following statements to create a series from a dictionary.
(A) Print the series
(B) Import the pandas library
(C) Create the series
(D) Create a dictionary
(A) Print the series
(B) Import the pandas library
(C) Create the series
(D) Create a dictionary
1
(A), (B), (C), (D)
2
(A), (C), (B), (D)
3
(B), (D), (C), (A)
4
(C), (B), (D), (A)
04
PYQ 2025
medium
computer-science ID: cuet-ug-
The plot function of pandas matplotlib uses 'kind' argument which can accept a string indicating the type of graph to be plotted. Which of the following are valid plots?
1
(A), (B) and (D) only
2
(A), (B) and (C) only
3
(A), (B), (C) and (D)
4
(B), (C) and (D) only
About Data Handling Using Pandas - CUET-UG
Data Handling Using Pandas is a vital chapter for CUET-UG aspirants. Mastering the concepts covered in this chapter is essential for securing a top rank.
By rigorously practicing the previous year questions associated with this chapter, you can identify high-yield topics, understand the examiner's perspective, and boost your confidence during the actual exam.
Frequently Asked Questions
Why focus on Data Handling Using Pandas PYQs?
Analyzing PYQs for this specific chapter reveals the most frequently tested concepts and the typical complexity of questions, allowing you to tailor your study plan efficiently.
How to best use this analysis?
Review the topic breakdown to see which sub-topics within Data Handling Using Pandas carry the most weight. Then, tackle the questions iteratively to solidify your understanding.