CBSE Class 12 Informatics Practices Important Questions with Solutions

Create a Pandas Series from the dictionary {'Jan':100, 'Feb':200, 'Mar':150} and display it.

import pandas as pd
d = {'Jan':100, 'Feb':200, 'Mar':150}
s = pd.Series(d)
print(s)

Solution: When a Series is built from a dictionary, the keys become the index and the values become the data. Series creation is a guaranteed 2-mark question.

A DataFrame df has columns Name and Marks. Display only the rows where Marks is greater than 75.

print(df[df['Marks'] > 75])

Solution: Use boolean filtering: df[df['Marks'] > 75] keeps only rows where the condition is True. This is one of the most repeated 2-3 mark questions in the paper.

Write code to add a new column 'Result' with the value 'Pass' to the DataFrame df.

df['Result'] = 'Pass'
print(df)

Solution: Assigning to a new column name creates it and broadcasts the value to every row.

Write code to plot a bar chart of Name against Marks from df, with a title and axis labels.

import matplotlib.pyplot as plt
plt.bar(df['Name'], df['Marks'])
plt.xlabel('Name')
plt.ylabel('Marks')
plt.title('Student Marks')
plt.show()

Solution: Import matplotlib.pyplot, call bar() with the two columns, then add labels, a title and show(). Adding the title and both axis labels usually carries a mark each.

Table PRODUCT(Pid, Pname, Category, Price). Show each category with its product count and average price, only for categories whose average price is above 500.

Solution: SELECT Category, COUNT(*), AVG(Price) FROM PRODUCT GROUP BY Category HAVING AVG(Price) > 500; GROUP BY groups by category; HAVING filters the groups on the aggregate, since WHERE cannot use AVG.

Display the names of all products that contain the letter 'a'.

Solution: SELECT Pname FROM PRODUCT WHERE Pname LIKE '%a%'; The % wildcard in LIKE matches any characters before and after the letter 'a'.

What is a digital footprint? It is the trail of data you leave online. An active footprint is data you deliberately share (posts, emails); a passive footprint is data collected without your knowledge (IP address, cookies, browsing history).

What is e-waste and how do you manage it? E-waste is discarded electronic devices; it is managed by reducing, reusing and recycling, and by handing devices to authorised recyclers rather than dumping them.

Common terms to memorise: IPR — Intellectual Property Rights, plagiarism — presenting someone else's work as your own, IT Act 2000 — India's law on cyber crime, phishing — tricking users into revealing personal data.