NCERT Class 12 Computer Science Book Informatics Practices: What’s Inside Each Chapter

The Class 12 computer science book Informatics Practices is the NCERT Informatics Practices textbook: seven chapters across 210 printed pages, with the official PDF of every chapter in the table below. Its practical stream runs from SQL through Pandas and Matplotlib to networks and digital society.

The PDFs give you the book; this page tells you what is inside it. Below the download table is a chapter-by-chapter breakdown measured from the book itself — how many named sections, activities, figures and exercise questions each chapter carries, plus the page where every topic starts. That is the part a bare link page never tells you.

Official NCERT PDFs, chapter by chapter

The table below links NCERT’s own PDF files, hosted on ncert.nic.in — the same files the NCERT website serves for this book. The direct link to the first chapter’s official PDF is worth opening first, because every query in Chapter 1 runs against the CARSHOWROOM schema printed at its start.

The Class 12 Computer Science book PDF: what this volume holds

The shape of the whole book, measured from the text:

• 7 chapters across 210 printed pages, from SQL functions (p. 1) to the project chapter (p. 195).
• 131 named sections — NCERT’s own numbered headings, from “Single Row Functions” (p. 4) to “Impact on Health” (p. 186).
• 48 verified numbered figures indexed from the textbook, from the CARSHOWROOM schema (Fig 1.1, p. 2) to the project barchart (Fig 7.2, p. 208).
• 34 activities spread across the book; every chapter except the project chapter sets at least three.

Every chapter has its official NCERT PDF linked in the table above. Use the directory below to see these totals chapter by chapter — where the activities concentrate, which chapter runs on diagrams, and where the exercise load sits.

What each chapter contains: sections, activities, figures, questions

Four counts need defining before the walk-throughs. A section is one of NCERT’s own numbered headings (1.1, 1.2, …); a figure is a numbered figure printed in the book; an activity is a hands-on task set inside the chapter; a question is an end-of-chapter exercise. Page references in the walk-throughs point to the official PDF.

Chapter 1: Querying and SQL Functions (pp. 1–26)

One idea carries this chapter: a function performs a particular task and returns a value as a result. Single-row functions return one value per row; multiple-row (aggregate) functions work on a set of records as a whole. The chapter then applies that split to grouping rows, set operations and combining two relations in a query.

1. Functions in SQL (p. 4) — Single Row Functions (p. 4), Aggregate Functions (p. 12)
2. GROUP BY in SQL (p. 14)
3. Operations on Relations (p. 16) — UNION (p. 16), INTERSECT (p. 17), MINUS (p. 18), Cartesian Product (p. 18)
4. Using Two Relations in a Query (p. 19) — Cartesian product on two tables (p. 19), JOIN on two tables (p. 20)

Fig 1.1, the schema diagram of database CARSHOWROOM (p. 2), is the table every query in this chapter runs against; Figs 1.3–1.5 (pp. 16–18) are the set diagrams behind UNION, INTERSECT and MINUS.

With 13 named sections, 6 activities, 5 figures and 5 questions, the activity blocks outnumber the questions — the activities carry much of the real practice load in this chapter.

Chapter 2: Data Handling Using Pandas – I (pp. 27–62)

NumPy, Pandas and Matplotlib are Python libraries for scientific and analytical use, and pip install pandas is the command that installs Pandas. A data structure is a collection of data values together with the operations that go with them. Chapter 2 builds the two structures everything later depends on — Series and DataFrame — then moves data between CSV files and DataFrames.

1. Introduction to Python Libraries (p. 27)
2. Series (p. 29) — Creation (p. 29), Accessing Elements (p. 31), Attributes (p. 34), Methods (p. 35), Mathematical Operations (p. 36)
3. DataFrame (p. 40) — Creation (p. 40), Operations on rows and columns (p. 44), Accessing through Indexing (p. 49), Joining/Merging/Concatenation (p. 52), Attributes (p. 53)
4. Importing and Exporting Data Between CSV Files and DataFrames (p. 55) — Import (p. 55), Export (p. 56)
5. Pandas Series vs NumPy ndarray (p. 57)

17 named sections, 8 activities, no numbered figures and 11 questions make this a chapter best practised by reading Python output rather than diagrams. Section 2.5 (p. 57) is the classic trap: take the Series-versus-array confusion into Chapter 3 and the grouping chapter gets harder.

Chapter 3: Descriptive Statistics, Grouping and Missing Values in Pandas (pp. 63–104)

Descriptive statistics quantitatively summarise the given data, and Pandas provides statistical functions for the job — the chapter names max(), min(), mean(), median(), mode() and std(). It then moves from individual calculations to aggregations, sorting, grouping, altering the index, handling missing values, and finally exchanging data with MySQL.

1. Introduction (p. 63)
2. Descriptive Statistics (p. 65) — Maximum (p. 65), Minimum (p. 67), Sum (p. 68), Number of Values (p. 69), Mean (p. 70), Median (p. 71), Mode (p. 72), Quartile (p. 73), Variance (p. 74), Standard Deviation (p. 75)
3. Data Aggregations (p. 75)
4. Sorting a DataFrame (p. 77)
5. Group By Functions (p. 79) — Fig 3.1, “A DataFrame with two columns” (p. 79)
6. Altering the Index (p. 82)
7. Other DataFrame Operations (p. 84) — Reshaping Data (p. 84)
8. Handling Missing Values (p. 89) — Checking (p. 91), Dropping (p. 94), Estimating (p. 96)
9. Import and Export of Data Between Pandas and MySQL (p. 98) — Import (p. 99), Export (p. 100)

At 42 pages this is the book’s longest chapter, and its 25 named sections, 6 activities, 1 figure and 14 questions make the ten “Calculating…” sections the place where the numerical Pandas work concentrates. Notice the book separates dropping missing values (p. 94) from estimating them (p. 96) — that is the decision students most often rush.

Chapter 4: Plotting Data using Matplotlib (pp. 105–136)

A plot is a graphical representation of a data set — a graph or chart — used to show the relationship between two or more variables. The chapter starts with Matplotlib’s plotting tools, shows how to customise marker, colour, line width and line style, then works chart by chart through the Pandas plot function.

1. Introduction (p. 105)
2. Plotting Using Matplotlib (p. 106) — incl. Fig 4.1, “Components of a plot” (p. 106)
3. Customisation of Plots (p. 108) — Marker (p. 109), Colour (p. 110), Linewidth and Line Style (p. 111)
4. The Pandas Plot Function (Pandas Visualisation) (p. 112) — Line chart (p. 113), Bar chart (p. 116), Histogram (p. 119), Scatter chart (p. 124), Quartiles and Box plot (p. 126), Pie chart (p. 130)

With 13 named sections, 3 activities, 21 figures and 16 questions, it is the book’s most visual chapter: more than two-fifths of the 48 figures sit here, and nearly every one is the printed output of a numbered program. Revise it by reading a chart and reconstructing the code that produced it.

Chapter 5: Computer Networks, Internet and the Web (pp. 137–166)

A group of two or more similar things interconnected with each other is a network, and a computer network is an interconnection among two or more computers to share data and resources. The chapter moves outward from that definition — types of networks, devices, topologies — then to the internet and the web: applications, websites, hosting and browsers.

1. Introduction to Computer Networks (p. 137) — incl. Fig 5.1 (p. 138)
2. Types of Networks (p. 139) — LAN (p. 139), MAN (p. 140), WAN (p. 141)
3. Network Devices (p. 142) — Modem (p. 142), Ethernet Card (p. 143), Repeater (p. 143), Hub (p. 143), Switch (p. 144), Router (p. 144), Gateway (p. 145)
4. Networking Topologies (p. 146) — Mesh (p. 146), Ring (p. 147), Bus (p. 147), Star (p. 148), Tree or Hybrid (p. 148)
5. The Internet (p. 148)
6. Applications of Internet (p. 149) — WWW (p. 149), Email (p. 151), Chat (p. 151), VoIP (p. 152)
7. Website (p. 153)
8. Web Page (p. 154) — Static and Dynamic (p. 154)
9. Web Server (p. 156)
10. Hosting of a Website (p. 157)
11. Browser (p. 158) — Settings (p. 159), Add-Ons and Plug-ins (p. 161), Cookies (p. 162)

The book’s largest section count — 36 named sections — comes with 5 activities, 14 figures and 17 questions, making this a concept-and-diagram chapter: Figs 5.3–5.9 show networks, devices, hubs and switches, and no numerical work appears anywhere in it.

Chapter 6: Digital Society, Cyber Crime and E-Waste (pp. 167–194)

A digital footprint is the trail of data we leave behind when we visit a website or use an online application to fill in data or perform a transaction.

A user of digital technology needs to follow the etiquette and legal framework this chapter lists — the thread running from footprints through data protection, cyber crime and the IT Act to e-waste and health.

1. Introduction (p. 167)
2. Digital Footprints (p. 168) — incl. Fig 6.1 (p. 168)
3. Digital Society and Netizen (p. 169) — Net Etiquettes (p. 169), Communication Etiquettes (p. 171)
4. Data Protection (p. 174) — Intellectual Property Right (p. 174), Violation of IPR (p. 176)
5. Creative Commons (p. 178)
6. Cyber Crime (p. 179) — Hacking (p. 180), Phishing and Fraud Emails (p. 180)
7. Indian Information Technology Act (IT Act) (p. 182)
8. E-Waste: Hazards and Management (p. 183) — environment (p. 183), humans (p. 184), management (p. 185), India (p. 185)
9. Impact on Health (p. 186) — incl. Fig 6.5, “Correct posture while sitting in front of a computer” (p. 187)

19 named sections, 6 activities, 5 figures and 21 exercise questions — the largest question block in the directory — and every answer here is conceptual (definitions, etiquettes, provisions of the IT Act) rather than computational.

Chapter 7: Project-Based Learning and the Four Project Briefs (pp. 195–210)

The closing chapter turns the book’s skill set into a team project. Its two halves: the approaches for solving projects, and the four project descriptions that ask for working output.

1. Approaches for Solving Projects (7.2, p. 196) — including Components of Teamwork (p. 198) and the steps of project-based learning shown in Fig 7.1 (p. 197)
2. Project Descriptions (7.4, p. 199) — Project I: Online Shopping Platform (p. 199); Project II: Automating a Books Donation Camp (p. 200); Project III: a survey of the effect of social networking sites on behaviour of teenagers (p. 201); Project IV: utilising an open data source at national, state or district level (p. 201), the kind of dataset whose output appears in Fig 7.2, “Barchart showing population in different categories” (p. 208)

8 named sections across 16 pages, no activities and no end-of-chapter question block — the zero in the question column is what a project chapter is supposed to look like. Its product is a working team project built on the Pandas and Matplotlib skills of Chapters 2–4, not written answers.

Chapter study pages

Each row in the PDF table above opens the official chapter file; the study pages below are where the chapter-wise walk-throughs on this site live.

How to use the Class 12 computer book for revision

A workable order for this specific book, chapter by chapter:

1. Work the Pandas track first: Chapters 2, 3 and 4 in order. Chapter 2 builds Series (p. 29) and DataFrame (p. 40); Chapter 3 assumes both for descriptive statistics, grouping and missing values; Chapter 4 plots the same structures. The three chapters share one set of data structures, so reading them as a block sticks better than revisiting each cold.
2. Do Chapter 1 separately, schema first. The SQL chapter is self-contained. Learn the CARSHOWROOM schema (Fig 1.1, p. 2) before attempting the queries — every query in the chapter runs against it.
3. Treat Chapters 5 and 6 as reading chapters. Together they carry 55 of the book’s 131 named sections and almost no program output, so they suit spaced reading and late revision rather than code practice.
4. Start Chapter 7 last. The four project briefs (pp. 199–201) demand the Pandas and Matplotlib skills of Chapters 2–4, so begin them only after that track is done.

The two data chapters are closer than they look. The book never prints the comparison below; it is a quick mapping to help you see the pattern.

The mistake that costs students the most time is treating SQL and Pandas as unrelated subjects. Both do grouping and aggregation; once the mapping above clicks, the two chapters reinforce each other instead of feeling like double work. The table below collects the other traps students hit with this book.

One caution before deciding what to skip: textbook contents and the examinable syllabus are not always identical. Check the current official CBSE syllabus before dropping any chapter.

Related pages on this site

• Other Class 12 NCERT books — the rest of the Class 12 shelf indexed here.
• NCERT books by class and subject — the hub for every book this site covers.
• Class 11 NCERT books — the same subject areas a year earlier, useful when a topic continues across classes.

Sources and data verification

This listing is maintained for the 2026-27 academic session using the NCERT textbook information available to us. NCERT remains the authority for confirming the latest edition.

• The figures, section titles and page references on this page describe the NCERT Informatics Practices textbook for Class 12, in the official NCERT edition hosted on ncert.nic.in (chapter PDFs leip101–leip107).
• This page covers that one book — the seven chapters of Informatics Practices — and not the other NCERT textbooks of Class 12.
• The listing is maintained for the current academic session using the NCERT information available to us.
• NCERT settles textbooks, editions and PDFs; CBSE settles the curriculum, syllabus and examinations.

Reference: NCERT Class 12 Informatics Practices textbook, official edition on ncert.nic.in. Figure captions and section titles quoted from the textbook; page references are to the official PDF.

Questions students ask about this book

How many chapters are in the Class 12 Computer Science (Informatics Practices) book?

Seven chapters across 210 printed pages. In order: SQL functions (pp. 1–26), Pandas I (pp. 27–62), descriptive statistics and grouping (pp. 63–104), Matplotlib plotting (pp. 105–136), computer networks and the web (pp. 137–166), digital society and cyber crime (pp. 167–194), and the project chapter (pp. 195–210).

Is the Class 12 Computer Science (Informatics Practices) book PDF free and official?

Yes. The table above links NCERT’s own PDF files hosted on ncert.nic.in, and downloading them costs nothing. The chapter links run from leip101 to leip107.

Which chapter covers SQL functions, GROUP BY, joins and set operations?

Chapter 1 (pp. 1–26). Single-row functions start at p. 4, aggregate functions at p. 12, GROUP BY at p. 14, UNION/INTERSECT/MINUS at pp. 16–18, and JOIN on two tables at p. 20.

Where do Pandas Series and DataFrames start, and where does plotting begin?

Series start at p. 29 and DataFrames at p. 40 of Chapter 2. Descriptive statistics fill Chapter 3 from p. 65, and Matplotlib plotting begins in Chapter 4 at p. 106.

Is this the Computer Science (083) textbook?

No — this page covers the NCERT Informatics Practices textbook. NCERT publishes a separate Computer Science textbook for Class 12; if your subject is Computer Science (083), that is the book you need, and it is not the one described here.