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| Syllabus | Source | Download |
|---|---|---|
| CBSE Class 12 Informatics Practices Syllabus 2025-26 | CBSE | Available Soon |
| CBSE Class 12 Informatics Practices Syllabus 2024-25 | CBSE | PDF Download |
| CBSE Class 12 Informatics Practices Syllabus 2023-24 | CBSE | PDF Download |
INFORMATICS PRACTICES (SUBJECT CODE 065)
CLASS – XII (SESSION 2024-2025)
Total Marks: 100 (Theory 70 Marks + Practical 30 Marks)
| UNIT NAME (UNIT 1 TO 4) | 70 MARKS |
| Unit 1: Data Handling using Pandas and Data Visualization | 25 Marks |
| Unit 2: Database Query using SQL | 25 Marks |
| Unit 3: Introduction to Computer Networks | 10 Marks |
| Unit 4: Societal Impacts | 10 Marks |
| PRACTICAL MARKS DISTRIBUTION | 30 MARKS |
| Programs using Pandas and Matplotlib | 8 Marks |
| SQL Queries | 7 Marks |
| Practical file (minimum of 15 programs based on Pandas, 4 based on Matplotlib and 15 SQL queries must be included) | 5 Marks |
| Project Work (using concepts learned in class XI and XII) | 5 Marks |
| Viva-Voce | 5 Marks |
| GRAND TOTAL | 100 MARKS |
Unit Wise syllabus
Unit 1: Data Handling using Pandas – I
Introduction to Python libraries – Pandas, Matplotlib.
Data structures in Pandas – Series and Data Frames.
Series: Creation of Series from – ndarray, dictionary, scalar value; mathematical operations; Head and Tail functions; Selection, Indexing and Slicing.
Data Frames: creation – from dictionary of Series, list of dictionaries, Text/CSV files; display; iteration; Operations on rows and columns: add, select, delete, rename; Head and Tail functions; Indexing using Labels, Boolean Indexing;
Importing/Exporting Data between CSV files and Data Frames.
Data Visualization
Purpose of plotting; drawing and saving following types of plots using Matplotlib – line plot, bar graph, histogram
Customizing plots: adding label, title, and legend in plots.
Unit 2: Database Query using SQL
Revision of database concepts and SQL commands covered in class XI
Math functions: POWER (), ROUND (), MOD ().
Text functions: UCASE ()/ UPPER (), LCASE ()/ LOWER (), MID ()/ SUBSTRING ()/ SUBSTR (), LENGTH (), LEFT (), RIGHT (), INSTR (), LTRIM (), RTRIM (), TRIM ().
Date Functions: NOW (), DATE (), MONTH (), MONTHNAME (), YEAR (), DAY (), DAYNAME ().
Aggregate Functions: MAX (), MIN (), AVG (), SUM (), COUNT (); using COUNT (*).
Querying and manipulating data using Group by, Having, Order by.
Working with two tables using equi-join
Unit 3: Introduction to Computer Networks
Introduction to networks, Types of network: PAN, LAN, MAN, WAN.
Network Devices: modem, hub, switch, repeater, router, gateway
Network Topologies: Star, Bus, Tree, Mesh.
Introduction to Internet, URL, WWW, and its applications- Web, email, Chat, VoIP.
Website: Introduction, difference between a website and webpage, static vs dynamic web page, web server and hosting of a website.
Web Browsers: Introduction, commonly used browsers, browser settings, add-ons and plug-ins, cookies.
Unit 4: Societal Impacts
Digital footprint, net and communication etiquettes, data protection, intellectual property rights (IPR), plagiarism, licensing and copyright, free and open source software (FOSS), cybercrime and cyber laws, hacking, phishing, cyber bullying, overview of Indian IT Act.
E-waste: hazards and management.
Awareness about health concerns related to the usage of technology.
Suggested Practical List (as CBSE)
1. Data Handling
- Create a panda’s series from a dictionary of values and a ndarray
- Given a Series, print all the elements that are above the 75th percentile.
- Create a Data Frame quarterly sales where each row contains the item category, item name, and expenditure. Group the rows by the category and print the total expenditure per category.
- Create a data frame for examination result and display row labels, column labels data types of each column and the dimensions
- Filter out rows based on different criteria such as duplicate rows.
- Importing and exporting data between pandas and CSV file
2. Visualization
- Given the school result data, analyses the performance of the students on different parameters, e.g subject wise or class wise.
- For the Data frames created above, analyze, and plot appropriate charts with title and legend.
- Take data of your interest from an open source (e.g. data.gov.in), aggregate and summarize it. Then plot it using different plotting functions of the Matplotlib library.
3. Data Management
- Create a student table with the student id, name, and marks as attributes where the student id is the primary key.
- Insert the details of a new student in the above table.
- Delete the details of a student in the above table.
- Use the select command to get the details of the students with marks more than 80.
- Find the min, max, sum, and average of the marks in a student marks table.
- Find the total number of customers from each country in the table (customer ID, customer Name, country) using group by.
- Write a SQL query to order the (student ID, marks) table in descending order of the marks.