# Informatics Practices Class 12 Commerce (English Medium) CBSE Topics and Syllabus

CBSE Syllabus For Class 12 Informatics Practices: Knowing the Syllabus is very important for the students of Class 12. Shaalaa has also provided a list of topics that every student needs to understand.

The CBSE Class 12 Informatics Practices syllabus for the academic year 2023-2024 is based on the Board's guidelines. Students should read the Class 12 Informatics Practices Syllabus to learn about the subject's subjects and subtopics.

Students will discover the unit names, chapters under each unit, and subtopics under each chapter in the CBSE Class 12 Informatics Practices Syllabus pdf 2023-2024. They will also receive a complete practical syllabus for Class 12 Informatics Practices in addition to this.

## CBSE Class 12 Informatics Practices Revised Syllabus

CBSE Class 12 Informatics Practices and their Unit wise marks distribution

## Syllabus

1 Querying and SQL Functions
• Introduction of Database Query Using SQL
• The following four relations:
1. Inventory
2. Customer
3. Sale
4. Employee
• Functions in SQL
• Single Row Functions
1. Math/ Numeric Functions: POWER(), ROUND(), MOD().
2. String Functions/ Text functions: UCASE ()/UPPER (), LCASE ()/LOWER (), MID ()/SUBSTRING ()/SUBSTR (), LENGTH (), LEFT (), RIGHT (), INSTR (), LTRIM (), RTRIM (), TRIM ().
3. Date Functions: NOW (), DATE (), MONTH (), MONTHNAME (), YEAR (), DAY (), DAYNAME ().
• Aggregate Functions: MAX (), MIN (), AVG (), SUM (), COUNT (); using COUNT
• GROUP BY Clause in SQL
• Querying and manipulating data using Group by, Having, Order by.
• Operations on Relations
• UNION (∪)
• INTERSECT (∩)
• MINUS (-)
• Cartesian Product (X)
• Using Two Relations in Query
• Cartesian product on two tables
• JOIN on two tables : equi-join and natural join
2 Data Handling using Pandas - I
• Introduction to Python Libraries
• NumPy, Pandas and Matplotlib
• Installing Pandas
• Data Structure in Pandas - Series and DataFrame
• A Series
• Creation of Series
(A) Creation of Series from Scalar Values
(B) Creation of Series from NumPy Arrays
(C) Creation of Series from Dictionary
• Accessing Elements of a Series
(A) Indexing
(B) Slicing
(C) Selection
• Attributes of Series
• Methods of Series: Head and Tail functions
• Mathematical Operations on Series
(A) Addition of two Series
(B) Subtraction of two Series
(C) Multiplication of two Series
(D) Division of two Series
• DataFrame
• DataFrame
• Creation of DataFrame
(i) Creation of an empty DataFrame
(ii) Creation of DataFrame from NumPy ndarrays
(iii) Creation of DataFrame from List of Dictionaries
(iv) Creation of DataFrame from Dictionary of Lists
(v) Creation of DataFrame from Series
(vi) Creation of DataFrame from Dictionary of Series
• Operations on rows and columns in DataFrames
(i) Adding a New Column to a DataFrame
(ii) Adding a New Row to a DataFrame
(iii) Selecting Rows or Columns from a DataFrame
(iv) Deleting Rows or Columns from a DataFrame
(v) Renaming Row Labels of a DataFrame
(vi) Renaming Column Labels of a DataFrame
• Accessing DataFrames Element through Indexing
(i) Label Based Indexing
(ii) Boolean Indexing
• Accessing DataFrames Element through Slicing
i) Filtering Rows in DataFrames
• Joining, Merging and Concatenation of DataFrames
i) Joining
• Attributes of DataFrames
• Head and Tail Functions
• Styling and formatting data
• Importing and Exporting Data between CSV Files and DataFrames
• Importing a CSV file to a DataFrame
• Exporting a DataFrame to a CSV file
• Pandas Series Vs NumPy ndarray
3 Data Handling using Pandas - II
4 Plotting Data using Matplotlib
5 Internet and Web
6 Societal Impacts
• Introduction of Societal Impacts
• Digital Footprints
• Digital Society and Netizen
• Etiquettes for Net surfing and for communicating through social media
• Net Etiquettes
(A) Be Ethical
(B) Be Respectful
(C) Be Responsible
• Communication Etiquettes
(A) Be Precise
(B) Be Polite
(C) Be Credible
• Social Media Etiquettes
(A) Be Secure
(B) Be Reliable
• Data Protection
• Intellectual Property Right (IPR)
(B) Patent
• Licensing
• Violation of IPR
(A) Plagiarism
• Public Access and Open Source Software/ Free and Open Source Software (FOSS)
• Creative Commons
• Cyber Crimes
• Cyber Crime
1. Hacking
2. Phishing and Fraud Emails
(A) Identity Theft
3. Ransomware
4. Combatting and Preventing Cyber Crime
• Indian Information Technology Act (IT Act)
• E-waste: Hazards and Management
• Impact of e-waste on the environment
• Impact of e-waste on humans
• Management of e-waste: Reduce, Reuse, Recycle
• E-waste Management in India
• Impact on Health
• Awareness about health concerns related to the usage of technology like effect on eyesight, physiological issues, and ergonomic aspects.
7 Project Based Learning

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