CBSE Class 12 Informatics Practices NCERT Exercise Solutions

CBSE Class 12 Informatics Practices — NCERT Exercise Solutions

Unit 1 — Python for Data Handling

Key Concepts — Pandas

MCQs

1. Which Pandas function is used to read a CSV file? (a) open() (b) read_csv() (c) import_csv() (d) load_csv()

2. What does df.shape return? (a) Number of rows only (b) Number of columns only (c) Tuple of (rows, columns) (d) Total number of elements

3. Which method removes rows with missing values? (a) dropna() (b) fillna() (c) drop() (d) remove_null()

4. To select rows where salary > 50000 in DataFrame df: (a) df[df['salary'] > 50000] (b) df.select('salary > 50000') (c) df.filter(salary > 50000) (d) df.query > 50000

Short Answer Questions

import pandas as pd

# (a) Create DataFrame
data = {
    'Name': ['Asha', 'Ram', 'Priya', 'Raj'],
    'Marks': [85, 78, 92, 65],
    'Grade': ['A', 'B', 'A', 'C']
}
df = pd.DataFrame(data)

# (b) First 3 rows
print(df.head(3))

# (c) Mean of Marks column
print(df['Marks'].mean())

import pandas as pd

df = pd.DataFrame({
    'Dept': ['IT', 'HR', 'IT', 'HR', 'IT'],
    'Salary': [60000, 45000, 70000, 50000, 65000]
})

# Average salary per department
result = df.groupby('Dept')['Salary'].mean()
print(result)
# Output:
# Dept
# HR    47500.0
# IT    65000.0

Unit 2 — Data Visualisation with Matplotlib

Key Concepts

Short Answer Questions

import matplotlib.pyplot as plt

students = ['Asha', 'Ram', 'Priya', 'Raj', 'Nita']
marks = [85, 72, 90, 65, 78]

plt.bar(students, marks, color='steelblue')
plt.title('Student Marks')
plt.xlabel('Students')
plt.ylabel('Marks')
plt.ylim(0, 100)
plt.show()

import matplotlib.pyplot as plt

scores = [45, 52, 60, 65, 68, 70, 75, 78, 80, 85, 90, 92]
plt.hist(scores, bins=5, color='orange', edgecolor='black')
plt.title('Score Distribution')
plt.xlabel('Score Range')
plt.ylabel('Frequency')
plt.show()

Unit 3 — SQL and Databases

Key Concepts

MCQs

1. Which SQL command removes a table's structure permanently? (a) TRUNCATE (b) DELETE (c) DROP (d) REMOVE

2. Which aggregate function returns the number of rows? (a) SUM() (b) COUNT() (c) AVG() (d) TOTAL()

3. The HAVING clause is used with: (a) WHERE (b) GROUP BY (c) ORDER BY (d) JOIN

Short Answer Questions

CREATE TABLE Student (
    RollNo INT PRIMARY KEY,
    Name VARCHAR(30) NOT NULL,
    Marks DECIMAL(5,2),
    Grade CHAR(1)
);

-- (a) Insert
INSERT INTO Student VALUES (101, 'Asha', 92.5, 'A');

-- (b) Filter
SELECT * FROM Student WHERE Marks > 75;

-- (c) Group and count
SELECT Grade, COUNT(*) AS Total
FROM Student
GROUP BY Grade;

-- (d) Update
UPDATE Student SET Marks = 95 WHERE Name = 'Asha';

-- WHERE: filter individual rows
SELECT * FROM Student WHERE Marks > 80;

-- HAVING: filter groups
SELECT Grade, AVG(Marks) AS AvgMarks
FROM Student
GROUP BY Grade
HAVING AVG(Marks) > 75;

-- Tables: Student(RollNo, Name, CourseID) and Course(CourseID, CourseName)

SELECT Student.Name, Course.CourseName
FROM Student
INNER JOIN Course ON Student.CourseID = Course.CourseID;

Unit 4 — Computer Networks

Key Concepts

MCQs

1. Which device connects a LAN to the internet? (a) Hub (b) Switch (c) Router (d) Repeater

2. What does DNS stand for? (a) Data Network System (b) Domain Name System (c) Digital Network Service (d) Dynamic Node Service

3. Which protocol is used for secure web browsing? (a) HTTP (b) FTP (c) HTTPS (d) SMTP

Short Answer Questions

Unit 5 — Cybersecurity

Key Concepts

Short Answer Questions

Worked Examples

Example 1 — Pandas operations on student data

import pandas as pd

df = pd.read_csv('students.csv')

# Find top scorer
print(df[df['Marks'] == df['Marks'].max()])

# Average marks by class
print(df.groupby('Class')['Marks'].mean())

# Students who passed (Marks >= 35)
passed = df[df['Marks'] >= 35]
print(f"Pass percentage: {len(passed)/len(df)*100:.1f}%")

Example 2 — SQL with aggregate functions

-- Highest marks per grade
SELECT Grade, MAX(Marks) AS Highest, MIN(Marks) AS Lowest, AVG(Marks) AS Average
FROM Student
GROUP BY Grade
ORDER BY Average DESC;

-- Students above class average
SELECT Name, Marks
FROM Student
WHERE Marks > (SELECT AVG(Marks) FROM Student);

Exam Tips

• Pandas questions always ask: create DataFrame, filter, groupby, or merge.
• SQL: GROUP BY + HAVING is a very common question — remember HAVING comes after GROUP BY.
• Networking: know which device works at which layer (hub=physical, switch=data link, router=network).
• Cybersecurity: always answer with examples — phishing example, ransomware example.
• Chart type selection: trend over time → line; categories → bar; distribution → histogram; relationship → scatter.