Consider the following graph. Write the Python code to plot it. Also add the Title, label for X and Y axis. Us

Question

Q. Consider the following graph. Write the Python code to plot it. Also add the Title, label for X and Y axis. Use the following data for plotting the graph smarks = [10, 40, 30, 60, 55] sname = ["Sahil", "Deepak", "Anil", "Ravi", "Riti"] [Figure: line graph titled 'Marks secured by students in Term-1', X-axis label 'Student Name' (Sahil, Deepak, Anil, Ravi, Riti), Y-axis label 'Marks Scored'; all plotting data is given above in text]

(OR)

Write Python code to draw the following bar graph representing the total sales in each quarter. Add the Title, Label for X-axis and Y-axis. Use the following data for plotting the graph: sales = [450, 300, 500, 650] qtr = ["QTR1", "QTR2", "QTR3", "QTR4"] [Figure: bar graph titled 'Sales each quarter', X-axis label 'Quarter' (QTR1-QTR4), Y-axis label 'Sales'; all plotting data is given above in text]

CBSECBSE Class XII Board 2023Subjective· 5mImportance★★★★★

🔒 Locked · start free trial →

You're viewing a preview — the full solution, concept, methods & PYQ mapping are locked.

Start your 14-day free trial to unlock the full solution →

Part (a)Concept understanding — Data Visualization

Data Visualization: Seeing the Story in Numbers

Imagine you are given a long table of numbers — monthly sales figures for a year, or marks scored by students in a class. Reading row after row of digits is tiring, and patterns are hard to spot. Now imagine instead a simple bar chart: one bar for each month, rising and falling with sales. In a single glance, you see which months were strong and which were weak. That shift — from a list of numbers to a picture — is the heart of data visualization.

What It Really Means

Data visualization is the technique of presenting numerical information in a visual form — graphs, charts, maps, or diagrams — so that patterns, trends, and comparisons become immediately visible. It is not decoration. It is a tool for thinking. The human brain processes images far faster than it processes tables of text. A well-made chart lets you grasp the big picture without getting lost in individual numbers.

The NCERT textbook for Class 11 Economics (Statistics for Economics) introduces this idea in the chapter on presentation of data. It explains that data can be presented in three ways: textual (in sentences), tabular (in rows and columns), and diagrammatic/graphic (as pictures). The third way — diagrammatic and graphic presentation — is what we call data visualization. The textbook emphasizes that visual presentation makes data more attractive, easier to understand, and quicker to compare.

Why It Matters for a Commerce/Humanities Student

You will encounter data everywhere — in business reports, government budgets, economic surveys, newspaper articles, and research papers. Being able to read a chart is as important as being able to read a sentence. And being able to choose the right chart for your data is a skill that sets you apart.

Here are the main reasons data visualization is essential:

Clarity: A complex set of numbers becomes simple when turned into a bar chart or a pie diagram. You can see the largest and smallest values at a glance.
Comparison: Two or more sets of data can be compared side by side — for example, sales in different years, or expenditure across different heads.
Trend identification: Line graphs show how something changes over time — rising, falling, or staying steady. This is crucial in economics and business studies.
Memory: People remember visual information longer than text or tables. A striking chart stays in the mind.
Communication: When you present your findings — in an exam answer, a project, or a business meeting — a chart speaks faster and more powerfully than a paragraph of numbers.

Note

In your NCERT syllabus, you will learn specific types of diagrams: bar diagrams (simple, multiple, and subdivided), pie diagrams (also called circle charts), and line graphs (for time series data). Each type has a purpose. For instance, a pie chart shows parts of a whole — like how a family spends its monthly income across food, rent, education, and savings. A bar chart is better for comparing separate categories — like the population of different states.

A Simple Everyday Example

Think of your monthly pocket money. Suppose you spend ₹500 on food, ₹300 on travel, ₹200 on entertainment, and ₹100 on savings. A table of these four numbers is fine, but a pie chart shows instantly that food takes up the biggest slice — half of your money. A bar chart lets you compare the amounts directly: the food bar is tallest, savings bar is shortest. You don't need to calculate percentages or differences; the picture does the work.

The Core Principle: Choose the Right Visual …

Part (b)Concept understanding — Data Visualization

Data Visualization: Seeing the Story in Numbers

What It Really Means

Why It Matters for a Commerce/Humanities Student

Here are the main reasons data visualization is essential:

Clarity: A complex set of numbers becomes simple when turned into a bar chart or a pie diagram. You can see the largest and smallest values at a glance.
Comparison: Two or more sets of data can be compared side by side — for example, sales in different years, or expenditure across different heads.
Trend identification: Line graphs show how something changes over time — rising, falling, or staying steady. This is crucial in economics and business studies.
Memory: People remember visual information longer than text or tables. A striking chart stays in the mind.
Communication: When you present your findings — in an exam answer, a project, or a business meeting — a chart speaks faster and more powerfully than a paragraph of numbers.

Note

A Simple Everyday Example

The Core Principle: Choose the Right Visual …

Start your 14-day free trial to unlock the full solution →

Part (a)

Line graph of student marks — plot names on X, marks on Y.

import matplotlib.pyplot as plt

smarks = [10, 40, 30, 60, 55]
sname  = ["Sahil", "Deepak", "Anil", "Ravi", "Riti"]

plt.plot(sname, smarks)
plt.title("Marks secured by students in Term-1")
plt.xlabel("Student Name")
plt.ylabel("Marks Scored")
plt.show()
``` …

Start your 14-day free trial to unlock the full solution →

Part (a): draw a line graph of student marks with plt.plot(sname, smarks) plus title and axis labels.

Part (b): draw a bar graph of quarterly sales with plt.bar(qtr, sales) plus title and axis labels.

Part (a)

A line graph joins the data points with a line and suits an ordered set of readings. Put the student names on the X-axis and their marks on the Y-axis.

import matplotlib.pyplot as plt

smarks = [10, 40, 30, 60, 55]
sname  = ["Sahil", "Deepak", "Anil", "Ravi", "Riti"]

plt.plot(sname, smarks)
plt.title("Marks secured by students in Term-1")
plt.xlabel("Student Name")
plt.ylabel("Marks Scored")
plt.show()
``` …

Start your 14-day free trial to unlock the full solution →

Same / Similar Concept — real previous-year questions on the same or a closely similar concept, not this exact question.

CBSE 2026Set 90/1/11 markMCQ
$Q. In which scenario is a bar chart preferred over a line chart ? (A) To visualise monthly temperature trends over a year. (B) To compare the number of students in different classes. (C) To show stock price movements over time. (D) To analyse trends in website traffic over days.$
›Reveal solutionSolution
A bar chart is best for comparing discrete categories, while a line chart excels at showing continuous trends over time. For comparing the number of students in different classes (distinct groups), a bar chart is the clear choice.

The core idea here is the nature of the data you are trying to display. Charts are not interchangeable; each has a specific strength.

A line chart connects data points with a continuous line. This is perfect for showing trends over time — how something changes from one moment to the next. Think of temperature, stock prices, or website traffic: you want to see the direction and rate of change.

A bar chart uses separate, non-connected bars. This is ideal for comparing discrete categories — distinct groups that have no natural, continuous order between them. You are not looking for a trend; you are comparing the size or quantity of each category against the others.

Let's apply this logic to each option.

Option (A): Monthly temperature trends over a year.

Months have a natural, continuous order (Jan → Feb → Mar …). You want to see how temperature flows from one month to the next. A line chart is the standard choice here. A bar chart would work, but it would hide the smooth trend.

Option (B): Number of students in different classes.

Classes (e.g., Class 6, Class 7, Class 8) are discrete categories. There is no continuous "trend" between them — you are simply comparing the height of each bar. A bar chart is the perfect tool for this. A line chart would be misleading because it would imply a connection between the classes that doesn't exist.

Option (C): Stock price movements over time.

Time is continuous, and the goal is to see the trend (up, down, volatile). This is a textbook case for a line chart.

Option (D): Website traffic over days. …
Start your 14-day free trial to see the full solution →

Part (a)

🎓Unlock everything free for 14 days

Unlock everything free for 14 days